DatatWare Housing

Informatica is something that you may have heard of before or maybe have not. However, if you have not heard of it you are truly missing out on this great bit of knowledge. Informatica is a software which allows the user to create a data warehouse with ease. It makes the process of designing, ETL and maintaining the data warehouse a breeze as well. Informatica training brings a new, simple approach to the term "Data warehousing."

Informatica training: What is data warehousing?

The use of data warehousing is an innovative way for a business to lower their operating costs, raise the production rates and push their sales through the door by using the management of information. It allows for the support of intelligence through the business, management of the relationship with the customer plus lots of other beneficial business uses.

Informatica training: How can Informatica help with data warehousing?

Data warehousing is not always the simplest of tasks especially when it comes around to accountability however, Informatica consists of an easy to use interface that allows you to create and control your warehouse effectively leaving, next to no room for the possibility of error. The bulk of the warehouse design is done by performing simple click and drag methods. This method, allows you to easily comprehend the tasks which you are performing. Informatica also has a unique ability to connect with any other major database that exists. This means that information is easily transported in between each of the databases including, the large volume information files.

Informatica has the ability to do this by performing throttle tasks or, performing huge tasks broken into smaller ones so as not to bog down the log. This is all done in a very effective yet secure way. Additionally, thanks to the server which is used by Informatica and a plug in server manager application, you are able to connect tables from any other server or database in existence. This in turn, helps you to effectively create, run and manage your data warehouse without frustration.

Informatica training: How does the software work?

The design is created in the designer portion of the program. It clues you into where you will put the tables and sources, what the specific targets which you will have are as well as how you should go about moving the information. With Informatica, you get your own repository manager which helps you to maintain the repository portion of the program. The repository is the database which is used by Informatica in order to keep track of all the data which is stored there for use.

Informatica training: What do I get with Informatica?

You have several different options when it comes to Informatica. This includes a number of varied packages and extras that are available. The Informatica Power Center allows you access to every option available which includes meta data. With this, you are able to keep all of your repositories in one place which is, a domain through the data mart. This also allows you to share the meta data throughout other repositories. The Power Mart option is a license which is slightly more limited however, still provides you the ability to do everything with the exception of the meta data.

An integrated set of software and hardware that is designed to meet a specific use is what constitutes a data warehouse appliance. This generally is made up of many servers, data storage devices, operating systems etc being very affordable and effective has emerged as a vital part of the data warehousing market. This appliance can be used to optimize different areas of data processing. Many appliances use languages like the SQL for interacting with the appliance on a database request level. Generally a true appliance requires no indexing or fine tuning and like other ordinary household devices is very easy to use and maintain. This makes it possible to set up a big data center warehouse in just a short span of time.

A data warehouse tool draws power from Massive Parallel Processing nodes and can deploy countless query processing nodes in a single appliance package. An appliance is capable of giving performance advantage that is practically a hundred times faster than general-use data warehouses. This amounts to low costs and low maintenance and automatically lesser power and cooling requirements since processors are not made to handle voluminous data. Data warehouse appliances are advantageous because they allow big companies to staff their warehouses better and help smaller organizations to resolve business challenges. Data center warehouse is therefore largely responsible for the manner in which businesses operate today.

Business intelligence implies activities that a company undertakes to get data about their competitors covering areas like market analysis, industry analysis and competition analysis. Even industrial espionage, it is believed, is a part of business intelligence. Here either an organization hires an outside agency or builds its own intelligence group to get inside information about the company's performance and areas that need improvement. It may then go through records of other businesses in the same field and customer surveys and at times also employ a spy to discreetly gather data. Unlike classic information gathering techniques, business intelligence systems make use of advanced technologies in data mining. Here all segments are interconnected and help to inform each other about their insights to get the complete picture. Business agility grows with business intelligence allowing an organization to exploit constantly changing market conditions.

Business intelligence in Australia is highly developed with the country ranking amongst the top five IT nations in the world. It can boast of good broadband connectivity, great internet security and strong government backing. It services are found to be taking control over nearly all spheres of the economy here ranging from social services and education to business, engineering projects to media and computing applications.

Most of the enterprises used custom coding processes or first or second generation ETL solutions to increase access to their data. Nevertheless, custom scripting does not endorse litheness and continued development in the significant business processes essential for enhanced efficiencies. General problems with a legacy ETL solution comprise:

• High operating prices - Most likely are needed to pay for each mainframe processing cycle you consume, and using a mainframe for ETL processes will consequence in excessive cycle utilization by your business element.
• Use of outdated technology - no vendor support, busy skillfulness in the job market, and no platform support
• Insufficient documentation - legacy code is text-based, the comments in code are for developers, and the knowledge rests (and leaves) with the developers
• Probable performance issues - older technologies be unsuccessful to make use of new technology capabilities such as parallelism

ETL solutions responsible for running batch jobs at scheduled periods to confine data from flat files and relational databases and merge it into a data warehouse database directed by a relational DBMS. Over few years, commercial ETL solution vendors have made a broad range of enhancements and additions in to their ETL software product.

Most of the ETL Tool are specializes in data warehousing solutions, with profound proficiency and practical skills, every company need the leading ETL tools to solve business problems. ETL tool help the companies to migrate the ETL processes from a legacy mainframe setting to a current ETL solution.

An ordinary enterprise ETL tools need is to extract data from apps like Oracle, PeopleSoft, and SAP and migrate it in to other applications like ERP, CRM etc. These ETL software products comprise enterprise application connectivity free of charge. These connectors - if available - are usually a paid option. They are not compatible with open source principles but common revenue source.

Use of business intelligence solutions and software will help you collate various data from various sections of your business so being able to make more informed decisions can be carried out a lot easier.

Although you may find initially when it comes to setting up data warehousing and business intelligence systems is a challenge. It is time and money spent that you will have invested in your business wisely as it can help to impact positively on how your business does in relation to your competitors.

Today there are many different types of data warehousing systems that a business can employ. These provide an effective all in one solution to gathering business intelligence and then allowing you to analyze it.

So just what are the benefits to be thinking about installing data warehousing and business intelligence systems for your business? Below we take a look at a just a number of these benefits.

Benefit 1 - These systems actually allow you to identify and resolve any inconsistencies in the data being collated before it is loaded. As a result it makes the whole process of reporting and analysing the business intelligence gathered much simpler.

Benefit 2 - Another benefit of using such systems is that the information being collected is controlled by the people using the system. Even so the system can still be purged over time and any information that has been collected can be safely and easily stored for a lot longer.

Benefit 3 - As this differs from other operational systems you will find that it allows the users to retrieve data without it causing the operating system to slow down.

Benefit 4 - Businesses that choose to install any kind of data warehousing and business intelligence gathering systems will find that they can improve the relationship not only between the various departments, but also their customers. Such improvements will then ensure that they find it easy to identify the needs of their customers and can work on ways to make sure that this will be met.

Benefit 5 - Through the use of such systems a business will be able to make sure that support system applications like execution and trend reports are functioning correctly. So the production of the reports that they then use to analyse their businesses performance are more accurate.

Benefit 6 - As mentioned above the use of data warehousing and business intelligence gathering systems can help a business to be more competitive. This is because it allows them to identify areas of the business where improvements can be made much more quickly.

Many companies today rely on the general ledger as key part of their management reporting, well beyond the obvious financial information.

The current practices in many organisations, and the architecture of their systems, and even the very structure of the software they buy have often been shaped by the history of the adoption of information technology in the firm.

In many firms, their management reporting systems reflect the fact that as information technology began to be used extensively by business, often the very first functional area to be automated was accounting.

Because finance and accounting are of course at the heart of any enterprise often the first automated reports and the first database within an enterprise was the general ledger.

In many companies, the general ledger became the clearing house for all information- not just financial, and in effect became a data warehouse before the concept of data warehousing had even evolved.

Lets look at the example of a manufacturing enterprise.

The company invested in a mainframe computer at some time in the seventies. Management was thrilled with the new capability they had in financial reporting. It didn't take long for them to ask to have manufacturing data in the reports as well.

Eager to please, the accounting department added lots of additional accounts into the Chart of accounts (COA), adding entries that were "non-financial" storing sales quantities, volumes consumed, things like energy consumption, raw material quantities, wastage and defect counts.

This made sense at the time, because otherwise the information would not have been stored digitally. The manufacturing plants used hard wired relay logic to control their equipment, and recorded instrumentation readings on chart recorders.

A chart recorder is a device that uses a physical pen to record temperatures, pressures, position, speed, etc. of equipment on paper which is physically pulled past the pen at a predefined rate. As these rolls of paper were used up, the operator would change them. The rolls of paper with the information on them then got stored in filing cabinets.

The shift workers wrote information into formated pages in a shift book, and then at the end of the month, administrative staff added journal entries to capture the information. Many factories didn't have a computer, or if they did, it was a mini-computer that was specified by and operated by the information technology department- which was part of the finance organisation. Companies didn't have CIOs, only CFOs.

The final result was, it was possible to generate management reports with both financial and manufacturing information. How many liters of paint did we buy? How many kilowatt hours of electricity, for how many units produced. In some ways, this might have been the brief golden age of management reporting. (Or is it just that time makes memory blur?)

Then, as computers started to arrive everywhere, no longer just the domain of the finance and accounting department, the trouble started.

The manufacturing plants installed automation systems. Chart recorders gave way to distributed control systems, and SCADA (supervisory control and data acquisition) systems, and pretty soon they had their own databases. They kept having to supply numbers for the bean counters to enter into the now aging mainframe, but they used their own reports and eventually spreadsheets to actually manage their process.

Manufacturing organisations began to include "automation engineers" which, in fact, were information technology professionals, and multiple IT departments began to form in all but name. Standards for data format, coding and methods for calculating key performance indicators evolved slowly, or not at all. Finances definition of how to calculate things tended to win because they held the keys to the general ledger, where the report that went to the CEO came from.

Then came the ERP. The ERP may or may not have included the manufacturing operations, but it almost always included the general ledger. Regardless of if the manufacturing modules of the ERP were used or not, the trouble with getting management reports just got worse. Manufacturing had all sorts of detailed information they needed, and keeping the central, general ledger reports up to date meant creating more and more accounts, more and more cost centers. The concept of a separate data warehouse where information from multiple systems (finance, manufacturing, sales) could be combined was born, and the general ledger, in theory, returned to its roots as a repository for financial transactions.

The problem is, in some organisations, the data warehouse didn't come. The general ledger kept its place as the central repository for not just financial, but also management reporting.

Huge amounts of non-financial information is still stored in many general ledgers. Here are just three important reasons why your general ledger should NOT be your data warehouse.

1) It forces you to compromise on level of detail and drill down, and history

No general ledger can hold the level of detail available in many source systems. As a result, any interface from the sales system, manufacturing system etc. feeding into the GL will have to create journal entries that summarize a great deal of information.

While the detail of course will still exist in the source system, if your management reporting is all from a general ledger based system, upper management will tend to use this single source- and as a result important granularity may be lost to the decision making process.

This summarization also makes it very difficult (or impossible) to have drill down into the details, giving up some of the greatest benefits of modern business intelligence systems.

Finally, general ledger based data storage does not usually allow for the tracking of reference data changes over time. As sales regions are modified, and territories shift, comparing one period to another becomes increasingly difficult. Data warehouses, designed from the beginning to store this type of slowly changing reference information, can provide a much more insight and historical analysis.

2) It results in an overly complex chart of accounts and may even affect month end close

As the source systems become more and more capable of collecting data, the tendency is to want to increase the amount of management reporting. If this is being done in the general ledger, it means that further charts of account must be added, and an increased number of journal entries need to be done. Depending how the overall process is setup, its even possible that the increased complexity might affect the speed at which month end closing can be completed, if for no other reason that the same finance resources must both tend to the financial and the management reporting needs.

3) It discourages cross functional definitions and collaboration on analysis

By making one of the functional areas (finance) the center and owner of management reporting, a general ledger based reporting architecture can actually increase the severity of the information silos it is most likely trying to eliminate.

Because the general ledger reporting does not require all the detail available, each department only needs to provide the summarized information required by finance. While every department has to coordinate with finance, there is no requirement for sales and manufacturing, for example to compare or coordinate their information definitions. While at a high level data is integrated, any benefit from more tightly integrating information across silos that a data warehouse can bring is lost.

In a very real way, a successful general ledger based management reporting system is in fact an impediment to progress for an enterprises business intelligence and data analysis evolution.

Because management reporting is available, the justification or need for a data warehouse is not felt as strongly. However, as needs continue to evolve, the effort expended in the constantly growing general ledger, and its impact on the financial processes, and the companies overall information management culture will become increasingly damaging.

Ironically, companies who failed to ever establish a general ledger based management reporting system could leapfrog their more financially focused competitors, as they embrace the modern data warehouse, the the tools available for data analysis.

A true data warehouse is not an easy road, and is only one component of a broader data analysis strategy. In the short term, using the general ledger for management reporting can seem easier, and could put off the challenges of additional hardware and software, as well as the need to coordinate between departments.

However, despite its historical place as the center of all data storage, in a modern architecture the general ledger should be used only for accounting as it was originally intended.

Analytics jobs are in great demand in today's industry. Some of the popular careers in this field include positions of a Data Analyst, Business Analyst, Marketing Analyst and Systems Analyst.

Data Analyst

The demand for data analysts is high in the Information Technology market. The main job of a data analyst is to search the particular needs of the client and evaluate data that meets those needs. A data analyst is required to search raw data and make comparisons with other related data, statistically. The solution to a particular problem has to be presented to the client in a simple and effective manner.

A freshman in this industry starts out as a Junior Analyst and moves up the ladder to Senior Data Analyst and Data Analysis Project Manager. Both technical skills as well as strong interpersonal skills are required in order for a person to succeed in this career.

Business Analyst

Business analysts are required in all spheres - healthcare, marketing, biotechnology and Information technology. Their main function is to understand that needs of the specific businesses and enhance the areas that need improvement. These professionals test and gauge the technical issues and implement changes, if required, keeping the company's objective in mind.

The qualifications required to apply for this position include a Bachelors' degree in business administration with a specialization in the concerned field such as Marketing, IT, biotechnology and so on. Other than these qualifications, these individuals need to have other analytical and problem solving skills, communication skills and must be able to work as a team and under high pressure.

Marketing Analyst

A Marketing Analyst is also vital for the growth of a company. Professionals in this field analyze, compare product prices, study the spending pattern of customers and other competitors to help develop a marketing strategy for a company. The changes in the marketing, strategy, product line and sales force are made based on the report provide by Marketing Analysts and thus is important for the growth of a company.

Systems Analyst

A System Analyst is responsible for analyzing the present system in the company and determining the future requirements. These include determining the limitations in the softwares and suggest alternatives to the company. These professionals usually act as a liaison between the IT group of a company and the vendor.

A person aspiring to make a career in this filed should be prepared to interact with technical team of the vendor and be familiar with different programming languages, have a knowhow about computer hardware and operating systems.

Lease Negotiation

An oil and gas lease is a legally binding contract for both parties involved. In most cases, a lease is set for a duration of 2-5 years if the energy company doesn't drill. Once a well is drilled and found economically viable, the lease continues in perpetuity so long as the wells inside the lease are economically viable. If the well is not viable, the lease expires after 2-5 years depending on the lease terms.

Terms of an oil and gas lease can be difficult to understand. There are many clauses and stipulations that must be addressed.

Entering into a contract with a large oil company can be daunting especially when a binding contract is involved. For a smoother facilitation of establishing a contract, energy companies usually assign a landman to the initial negotiations between a mineral owner and their company. The landman is also responsible for performing the basic groundwork of determining the correct mineral right owners.

It is imperative that the mineral owner review the oil and gas lease in detail to make sure that the terms set forth are agreeable. If there are items in the contract that are unsatisfactory to the mineral owner, it is necessary to negotiate terms with the landman that will be acceptable. Sometimes these terms are simply adjusted while other times the items are altered completely. There are even times when an agreement can not be reached by either party.

Mineral owners are highly encouraged to seek legal counsel when entering an oil and gas lease. Energy companies have entered into many oil and gas leases and are very familiar with the process. However, a mineral owner may be completely unfamiliar with a lease and the negotiations necessary to create a lease that is mutually beneficial. It is important to remember that at times a mineral owner may feel distrust or hostility after reviewing the lease or during the negotiation process. Again, It is highly encouraged for the mineral owner to retain an experienced oil and gas lawyer to review the lease in order for the negotiation process to run more smoothly.

Lease Components

At the top, usually the right hand corner there is a date. This date is known as the date clause. It establishes the commencement date of the lease.
The names of both parties that are legally bound to the lease are in the first paragraph. The lessor, who is the mineral rights owner, and the lessee, which is the energy company.

A legal description of the land is outlined. So that both parties may establish the exact plot of land that will be bound by this agreement.

The duration of the primary term is mentioned in months. A clause that allows for a secondary term can also be added to a lease.

The royalty clause is usually a lengthy paragraph. This clause states the percentage or share of production proceeds the leasor receives. How the royalty is received is also mentioned in this paragraph as well.

A granting clause is included in all leases. The granting clause outlines the rights of the lessee and the property that is binding to the lease. The lessee's rights include drilling, delay rental, pooling, shut-in royalty, unitization and additional drilling clauses.

The lease also outlines the course of action that will be taken by the lessee if any such problems arise during the term of the lease like what happens when a dry hole is drilled within the primary terms. A damage clause is also included in the lease as well.

Another important clause in an oil and gas lease is an assignment clause. During the term of the lease if either party should choose to transfer ownership, the assignment clause outlines the stipulations that must be met. This is important to the energy company, as many energy companies transfer ownership of their leases.

The force majeure clause touches upon the state and national laws that it is necessary for any drilling rig to adhere to. They are clearly outlined and give the Lessee freedom from non-performance that could possibly be implicated in the lease.

Like many standard contracts there is a warranty clause. A warranty clause states that the mineral owner guarantees their legal right to the land to the Lessee if he or she should later be discovered to not be the true legal mineral right owners.

IBM and CIO Insights have recently conducted surveys with CIOs regarding their top priorities for 2010. Top Analysts from Gartner gave their opinion about IT budgets and IT spending for 2010 and beyond. The IBM study revealed that Business Intelligence and Analytics are the top priorities for more than 83% of all interviewed CIOs. The CIO Insights survey show business productivity, cost reduction and IT/Business Alignment as top priorities. According to Peter Sondergaad, VP Research, Gartner, 2009 was the most challenging and interesting year for CIOs. He quotes "The IT market is exiting its worst year ever".

In 2009 enterprise IT spending will end up to be 2,3 trillion dollars compared with 2,5 trillion dollars in 2008. Spending has actually declined in all markets, so CIOs have saved across hardware, software, telecommunication services and IT services. 2010 will not see a huge increase in IT spending, as budgets are still tight. The largest increase spending in IT will happen in health care, utilities and government.

The 2010 CIO spending budget is therefore done on the background of the worst year ever in the IT industry. 2010 is about balancing cost, risk and growth. IT has to be prepared to carefully plan for growth. So CIOs are facing a dilemma: How can they reduce cost while improving services? How can they balance the need to influence business strategies with the need to provide top notch IT support?

Using information technology to produce greater business value is vital, bundled with an ongoing focus on lower cost and higher efficiency. This is why an improved business intelligence solution combined with a great analytics tool with excellent visualization is so important.

Storekeeper jobs are in demand in those organizations where material management is required. Storekeepers, also known as watchdogs, are the in charge of the store department and are expected to perform various warehousing duties of receiving, arranging and issuance of goods. They are not only accountable for receiving and issuing of goods but sometimes they also have to act as a inspector, supervisor and manager to ensure that there is proper handling/stacking of goods, inspection of stocks, warehouse maintenance and cleaning, wastage disposal and proper documentation and record-keeping. Store administrator is the one, who efficiently look/supervises after all the things at the store from inspecting stocks to warehouse cleaning and maintenance.

Candidates looking for such kind of role must have sound knowledge of policies and procedures related to receipt, storage and issuance of materials, good communication skills, physically strong etc. Computer literacy would be an added advantage. Material Management Jobs plays a critical role in an organization because production of goods is primarily dependent on the availability of materials. A Material Manager has to identify the vendors for materials, supplies and equipments well in time, maintain records of goods ordered and received, identify quality goods at the lowest possible price etc. An aspiring candidate in this field should have adequate knowledge of the market to identify the suitable vendors, must have good communication skills for getting better deals, and must be well versed with the computer skills as they are expected to work on the inventory database.

Likewise storekeeper jobs, Warehouse Management Jobs also plays an important role in a production oriented organization. A warehouse manager has to plan, organize and control overall operations of the warehouse, setup layout and space management, manage stock control, plans out for development of staff through trainings etc. These jobs require individuals, who have the ability to work effectively without much supervision and communicate effectively. These individuals must also possess good health and physical stamina to handle the daily warehousing activities.

Resource Management jobs play an integral role in every organization because every organization hire resources/employees who work for them and for managing them resource management jobs comes into picture. They are the link between the management and employees who help resolving work related problems, administers benefits and performance management systems, analyze and modify compensation and benefit policies to establish competitive programs and ensure compliance with legal requirements etc.

Store keepers are not only the caretakers but they are also the supporters who have the ability to establish and maintain effective working relationships to ensure smooth running of the business. Surely storekeeper jobs have become an indispensable part of work culture in any organization.

Writing a web application is straight forward once you've mastered the fundamentals of a server-side scripting language and a database system. Though it is not obvious, developing a website that caters to thousands of users and one that caters to millions of users require a different set of tricks.

This new scenario must take into careful account the server resources that is utilized to ensure that only optimal coding practices are used when information storage and retrieval goes up to a massive scale. Instead of thinking in terms of a single web server, you must use variable configuration in your application to cater for multiple web servers that can be added-on at any future date. Your programming logic must know how to distribute content and processing work across the added servers.

More servers are needed when the CPU load utilization spikes to a high level that eventually affects the performance of your website. Your web server takes longer time to respond to user request and pages that took seconds to load are now taking much longer. This could happen when the number of simultaneous website visitors increase or that a certain processing tasks in your application is highly intensive, such as video conversion process, real-time image file manipulation or sorting of huge datasets that are fully loaded into memory.

One strategy is to clearly separate different aspects of your application functionality to different servers, such as news.yourserver.com and video1.yourserver.com or music3.yourserver.com. Hence, when your users are using different services of your website, they are bounced to different subdomains that are pointed to different web servers. If it's a membership page, there will be a challenge to maintain user session across the different servers, as session information are usually stored in each local server in the /tmp folder. In PHP, the session handler needs to be configured to utilize a common database instead of the local filesystem to cater for cross server session tracking.

This strategy also require that 'shared files' are stored in a common area so that the different servers has access to them and that there are APIS written for reading or writing to these common files. When multiple users on multiple servers are able to write to a common file, the file access API must ensure that proper file locking mechanism is in place to maintain file integrity.

Since the database backend is usually accessed by a local socket/network connection, it is by default that all web servers are able to access a common data pool without further complexities. However in almost every case, the bottleneck of a website lies with the database storage, especially when the amount of data stored has gone into tens of millions of rows and that heavy server usage is causing thousands of database records to be updated every second.

Highly matching database indexes must already be in place to ensure an instantaneous retrieval of data. This being said, it is never as easy as it seems and because we are discussing scalability, there must also be a solid plan in place to add more database servers when necessary. As with the multiple web servers, your application logic must also which database server to retrieve data from, if you're splitting different partitions of data into different database servers.

The other trick is to deploy Database Replication, whereby every database system contains the exact copy of data (as opposed to partitioning different sets of data to different db servers), and that the overall load of each database server is spread across the group of servers. More than just a method of database load balancing, this method also ensures data redundancy, and that your application would be running smoothly in the event of one or more database crash.

The other methods to think about is the caching of often read data that is rarely updated. File based caching or memory based caching can be used, and it has proven that these methods can improve performance by nearly two thousand percent. This is due to the high cpu utilization when sockets communication is involved and that local file or memory access takes a tiny fraction of the cpu resource instead.

When planning for a high performance system, do think of using lookup tables that has values already pre-calculated for frequent use, as well has utilize hashing algorithms for the lookups of cached data. Avoid data intensive real-time processing at all cost and try to use pre-generated tables that is incrementally built instead of a full regeneration every day. Reduce access to the database as much as possible and use local file access instead.

Lastly, always take a peek into your database process list, to get a glimpse of which query is taking too long to respond. These are the queries that locks the database tables for a long periods and denying access to other queries from completing its task. These are the major points of planning a high performance and scalable web application. It's something that's not widely documented in books, and you will need to experiment and to create benchmarks for comparison.

Useful skills to have include the understanding of file read/write locking access, sockets communication, what a hash is compared to a sequential search and memory based caching - Memcache. Lastly, always think of delegating tasks to different servers and plan for future data partitioning. Good luck with your tasks at hand, for it's not an entirely easy one.

In concept, the more robust enterprise resource planning solutions (ERP) combine data and processes by using integrated software and hardware components and a unified database to capture information from all areas of an organization. Of course, the most immediate use of ERP solutions in business is found in applications for manufacturing (discrete and process). An ERP solution must be many things to many people within an organization, but at its base it should be both scalable and flexible, as well as transparent to end users even as it continuously works in the background.

ERP functions through the ordering of business processes that are themselves organized according to common business flows (i.e., lead-to-order, order-to-cash, purchase-to-pay, etc.). Such unified and consistently flowing business processes are produced through core applications that are usually built, in ERP, on a single platform to help consolidate information and reduce IT costs. Doing business today-particularly manufacturing business-without ERP is tough, and is at best much less efficient when viewed through the very focused lens of bottom-line metrics.

What does ERP do? It helps to organize the various factors found within emerging and present opportunities, and can:

• Improve productivity
• Enhance financial performance
• Streamline processes and workflows
• Improve reliability of tracking and forecasting
• Lower production costs
• Improve customer service (CRM)

To these ends, a good ERP solution offers a strategic link between business objectives and IT. As well, it can be justified to management in very measurable returns. A robust ERP solution is configurable at the business-process level so that as company objectives change, the ERP solution changes right along with them. Therefore, ERP implementation can be seen as way organizations build relationships; to perform effective, repeatable processes; to drive efficiency into every process; and to share information accurately and as needed. And, of course, to drive profits to greater success.

In short, top-tier ERP applications will directly link the specific attributes that inform the positive financial performance of the business. By connecting the application functionality to business-process improvements in all areas of the manufacturing operation (including finance, production, supply chain management, customer relationship management, data warehousing, and human resources), the entire organization benefits in terms of operational and actionable intelligence. In this regard, ERP is more than just business communication.

With the power of the comprehensive inclusion of business data, ERP becomes an organizing force for manufacturing, and ultimately provides efficiency solutions that are otherwise difficult to imagine. To the extent that ERP is a totalizing tool designed that easily integrates diverse data, the single source solution approach offers the best and most efficient method for organizing and interpreting such data.

Summary: A good ERP solution can offer a strategic link between business objectives and IT, and do it in such a way that drives profitability and productivity. ERP organizes real time data from all areas of the manufacturing operation. In doing so, it provides the capability of making informed decisions rapidly, and with information that is both timely and relevant. In turn, such decision-making capabilities resulting from ERP produce improved productivity, improved financial performance, lower production and administration costs, enhanced forecasting, and improved customer service.

Royalties vs Mineral Rights

Oil and gas royalties are not as complex as most people think. They are actually fairly simple, and I'll explain clearly what they are and how they generate cash.

If you own a farm, then you own the land also known as the surface rights. Often, when you bought the farm, your deed conveyed the mineral rights under the farm along with the surface rights. Owning the mineral rights means you legally have the right to explore, extract, and sell any oil, gas, coal, uranium, helium or other mineral that rests beneath your land.

Most landowners, however, don't have the geological knowledge or training to understand the potential minerals under their land. In fact, many landowners forget they own the mineral rights under their land. Further, the average landowner does not have the multi-million dollar budgets to explore for hydrocarbons, or the social networking skills to raise a multi-million dollar exploration fund.

Energy companies do have the knowledge and funding to explore for oil and gas. So when they identify a region that likely contains hydrocarbons, they negotiate with the landowners to lease their mineral rights for exploration. This lease gives the energy companies permission to explore for petroleum and to produce and sell it if they find petroleum in economic quantities.

The Bonus and the Royalty

The mineral owner receives two forms of compensation for leasing his mineral rights. The first is called a 'Bonus Payment' which is a signing bonus that is paid on a per acre basis. Typically $200-$500 per acre. The bonus will be paid once at the time of the signing of the lease, and it may be the only money the owner will get.

The second is the royalty which is the percent of the money generated by the oil and gas from his property. Traditionally 12.5%, but more recently around 18% - 25%. The percentage varies upon how well the mineral owner negotiated and how expensive the oil company expects the extraction of oil and gas to be.

However, if the oil company finds no oil or gas, or not any in economic quantities, then they abandon the prospect, and the lease expires which reverts the mineral rights back to the mineral owner. In this case, the Bonus was the only money the owner received.

In the event hydrocarbons are found and the wells produce, then the royalties kick in. So if the well produces 100 barrels a day, and the price of oil is $80 per barrel that month, then the cash flow is 100x$80 = $8,000/day The royalty owner, who agreed to 15% royalty, would receive $8,000 x 0.15 = $1,200/day. Over a month, that brings in $36,000 per month to the mineral owner, who in this case, is the landowner. Now you see why oil is a big business!

Royalties Dwindle Over Time

Royalties paid to the mineral rights owner will often last for decades. The wells will deplete, however, so over time the money received from royalties will drop considerably. The average well is thought to last 35 years. Eventually, the royalty dies, and all the owner has is the mineral rights. Which may get leased again in the future.

Finding Mineral Rights to Buy is Hard

Because of the reliable cash flow stream, oil and gas royalties make for a good investment. Finding mineral right owners who want to sell their royalties is the tough part. The only available data on royalty owners currently is Blackbeard Data Services, and they have all the owners in Texas and Kansas.

Most companies make use of their own dashboard in order for them to gather and manage real time information. Their dashboards are often connected to the Internet or their own network so that they can disperse their data easily to everyone working in their organization. With the dashboard they can determine how well they are performing based on different issues that they want to concentrate on. These include the customers and the processes in their company most of the time. At times, they find this a hard thing to do and this is why they seek the help of the solutions presented to them by BI dashboard consulting.

Such consulting service can vary from one company to another as well as with the service provider. In general though, they are well known for giving guidance, advice and recommendations to their clients regarding the use, design and the function of the business intelligence dashboard that they are exploiting. Availing of the said service will truly benefit your company. First is the fact that the pieces of advice that you gain are those that come from experts in the field. Even though this is the case, you should keep in mind that there are predators out there waiting for you to pay for their bogus services. This is why you have to be careful and research first so that you will not be tricked by these kinds of people.

The people behind the reliable company that offers BI dashboard consultancy can help you particularly for those that make use of an executive dashboard, which is the most common dashboard for businesses. They focus on the needs of your company including both for the business and the technology of the organization. On your part, it is important that you know the demands and the requirements of your company so that the consulting services provider will be able to help you deal with your business situation.

After providing them with the details of your company, you can now choose the kind of service that you need and also discuss other matters including the cost and the team that will be working with you. Among the services that are commonly offered by them include the assessment of your current business intelligence solutions, designing the data warehouse, identification of the data source, data cleaning, assessment of the quality of the data and the management of metadata. With the great number of services that they present to their clients, you will be able to find the ones that suit your needs.

With the consulting services for business intelligence, you will be able to explore and ensure that the key areas of your company will be taken care of. These include the identification of the key performance indicators and the other supporting indicators that will keep you up to date regarding the condition of your company. You will also benefit from the fact that they ca help you optimize the data gathering processes and also assist you in assessing the systems so that you can manage your company's performance effectively.

These days a company lives and dies on how fast it can store, retrieve and analyze information. As such, database administration (DBA) has become one of the most important aspects of a corporation's MIS department. Because of this, a fast growing occupation inside the department is the Data Warehouse Manager.

The DB manager is the person responsible for the loading, storing, maintenance and extraction of all files stored within a business intelligence system. People in this field have done their share of time in the working world, and it's becoming quite common for them to not only have a few years experience under their belts, but also have gotten an MS in some form of Computer Science, with a strong emphasis on DBA.

Anyone interested in pursuing this line of work should be of a meticulous nature. They should also possess strong analytical and logical skills. Good communications capability is also essential as part of the job is explaining how the warehouse system works to those who aren't as adept at storing and retrieving data.

There are many good on campus and online colleges that offer good undergraduate programs in Computer Science and Information Technology. As businesses are the primary employers of warehouse managers, taking some basic courses in the field is oft times beneficial. Once past the basic core a student should try to put in some courses in on basic database construction and architecture.

Upon achieving a Bachelor's, it's time to specialize in Database Architecture and Network information systems. Another Master's level degree that is quite popular is an MBA with an MIS core. At the same time, it should not be too difficult to find a solid job as a database analyst or assistant DBA position. With some time at the company it should be more than willing to help pay the tuition for you sticking around.

Upon achieving either an MS or MBA, there will be one last step in the education process, and that's attending the last few courses or seminars needed to be certified as a Database Warehouse Analyst or Manager. Again, most companies include continued education benefits as part of their employment package. They really have to as this is a position where professionals have to constantly go back for the latest updates and innovations in the field.

Salaries are commensurate with this level of education. According to a recently published report inside the industry, a Warehouse Analyst earns $77,000 to $106,000 a year, depending on industry, location and experience. A Warehouse Manager earns even more, from $92,000 to $125,000 a year. Both jobs are expected to see their salaries grow over 4% in the next year alone. Those with knowledge of IBM DB2, SQL and Oracle are at a premium, and can earn an extra 10% for their knowledge.

Use of business intelligence solutions and software will help you collate various data from various sections of your business so being able to make more informed decisions can be carried out a lot easier.

Although you may find initially when it comes to setting up data warehousing and business intelligence systems is a challenge. It is time and money spent that you will have invested in your business wisely as it can help to impact positively on how your business does in relation to your competitors.

Today there are many different types of data warehousing systems that a business can employ. These provide an effective all in one solution to gathering business intelligence and then allowing you to analyze it.

So just what are the benefits to be thinking about installing data warehousing and business intelligence systems for your business? Below we take a look at a just a number of these benefits.

Benefit 1 - These systems actually allow you to identify and resolve any inconsistencies in the data being collated before it is loaded. As a result it makes the whole process of reporting and analysing the business intelligence gathered much simpler.

Benefit 2 - Another benefit of using such systems is that the information being collected is controlled by the people using the system. Even so the system can still be purged over time and any information that has been collected can be safely and easily stored for a lot longer.

Benefit 3 - As this differs from other operational systems you will find that it allows the users to retrieve data without it causing the operating system to slow down.

Benefit 4 - Businesses that choose to install any kind of data warehousing and business intelligence gathering systems will find that they can improve the relationship not only between the various departments, but also their customers. Such improvements will then ensure that they find it easy to identify the needs of their customers and can work on ways to make sure that this will be met.

Benefit 5 - Through the use of such systems a business will be able to make sure that support system applications like execution and trend reports are functioning correctly. So the production of the reports that they then use to analyse their businesses performance are more accurate.

Benefit 6 - As mentioned above the use of data warehousing and business intelligence gathering systems can help a business to be more competitive. This is because it allows them to identify areas of the business where improvements can be made much more quickly.

Data warehousing software's have a great demand in the market because of the ease that they offer to an organization for handling various projects. There are many data warehousing consultants present in the market, who offer customized solutions to clients. But what is the scope of being a data-warehousing consultant? Read the article.

The data warehousing market has many warehousing consultants who provide resources and services to meet the requirements of warehouse owners. These consultants provide totally integrated solutions that will help business owners in handling the company and database more efficiently.

The data warehousing vendors offer tools, technology and methodologies to help you in constructing, managing, using and maintaining software & hardware that are used in a data warehouse. They understand the business of customers and provide them with services that meet and even exceed their expectations.

The daily duties of a data-warehousing consultant are never the same. They design data extraction, transform and load routines. Using a programming language, script, tool or the combination of all the three helps in developing all this. Here are some duties of the consultant:

o A data warehouse consultant creates documents.
o Interfaces with other team members and the supervisors.
o Conduct different tests of data warehouse batches.
o Talk to users, business analysts, technical coordinators, server administrators, database administrators and many other people working on the system.

Do You Want to be a Data Warehouse Consultant?

The must-have technical skills a data warehouse consultant should have include a thorough knowledge of databases that are being used, the operating systems which are used, script that would be required to write code and expertise in a programming language. Another must have skill is the knowledge of data warehouse tool, which the organization would be using. If you have enough information of the tool, it will lead to a seamless merging of one technology with another to finish the ETL tasks. Some of the common tools are DOS batch script, UNIX shell scripts, DataStage, advanced SQL and Informatica.

Apart from this, one should also have keen observations skills to find out fine details or any mismatches in the numbers. Those with an ability to do analysis are also fit for the job of a warehousing consultant. However, there will be separate analysts for creating technical specifications and mapping all the documents.

Those new into the field of data warehousing will love the excitement of working on projects and in facing the challenges that are crucial for the growth of an organization. Most of the data warehousing projects will be fast paced, so you need to invest a lot of time and manage things properly. Handling a data warehousing project means working on multiple technologies and teams. A data-warehousing consultant gets good exposure and there is a lot of scope for newcomers in this field.

An integrated set of software and hardware that is designed to meet a specific use is what constitutes a data warehouse appliance. This generally is made up of many servers, data storage devices, operating systems etc being very affordable and effective has emerged as a vital part of the data warehousing market. This appliance can be used to optimize different areas of data processing. Many appliances use languages like the SQL for interacting with the appliance on a database request level. Generally a true appliance requires no indexing or fine tuning and like other ordinary household devices is very easy to use and maintain. This makes it possible to set up a big data center warehouse in just a short span of time.

A data warehouse tool draws power from Massive Parallel Processing nodes and can deploy countless query processing nodes in a single appliance package. An appliance is capable of giving performance advantage that is practically a hundred times faster than general-use data warehouses. This amounts to low costs and low maintenance and automatically lesser power and cooling requirements since processors are not made to handle voluminous data. Data warehouse appliances are advantageous because they allow big companies to staff their warehouses better and help smaller organizations to resolve business challenges. Data center warehouse is therefore largely responsible for the manner in which businesses operate today.

Business intelligence implies activities that a company undertakes to get data about their competitors covering areas like market analysis, industry analysis and competition analysis. Even industrial espionage, it is believed, is a part of business intelligence. Here either an organization hires an outside agency or builds its own intelligence group to get inside information about the company's performance and areas that need improvement. It may then go through records of other businesses in the same field and customer surveys and at times also employ a spy to discreetly gather data. Unlike classic information gathering techniques, business intelligence systems make use of advanced technologies in data mining. Here all segments are interconnected and help to inform each other about their insights to get the complete picture. Business agility grows with business intelligence allowing an organization to exploit constantly changing market conditions.

Business intelligence in Australia is highly developed with the country ranking amongst the top five IT nations in the world. It can boast of good broadband connectivity, great internet security and strong government backing. It services are found to be taking control over nearly all spheres of the economy here ranging from social services and education to business, engineering projects to media and computing applications.

Data Warehousing was an innovation from the 90's that promised to change the data landscape for good. How far have we come? Many vendors have entered the marketplace because it makes sense to bring together data from throughout the organization, and this will continue to make sense in the future.

How large the Data Warehouse market will grow nobody knows yet. But for sure it is still growing fast, and currently is estimated at 4,5 billion dollar per year (IDC).

1. Why Do Data Warehouse Projects Run Into Scope Creep?

To quote Bill Inmon (guru and author of several great books on Data Warehousing) "Traditional projects start with requirements and end with data. Data Warehousing projects start with data and end with requirements." As soon as the project gets under way, users will find new applications, and with it will come new requests for data. Interestingly, these projects often are justified by moving Q&R work away from the 'data people'. What we've seen is that the first thing that happens as soon as the project delivers is that more requests for special queries are submitted to these same 'data people'. This may appear to undermine the initial business case but actually signals the onset of value creation from the DWH project.

2. Star Schema Versus Entity Relation Model?

There has been enormous debate in the community about the merits of different data models. At the risk of over simplifying: ER models tend to have better performance (processing time) for the end user, and are often perceived as "easier" to understand by end users. Drawbacks are that ER models require more disk space, and, because of the intrinsic redundancy in the data, have consistency problems from a maintenance perspective. Having said this, the practice seems to be that often some combination of the two is unavoidable in the practical setting, despite preferences (ER or Star) of the chief architects. Overall, Star models seem to have gained the most ground.

3. The Importance of a Data Warehouse Business Case

Much has been written about the business case for a Data Warehouse. What goes in to a good business case? IT savings are ubiquitous in DWH business cases. The important point is to not limit this to 'pure' savings, but to connect to primary business processes as much as possible. As an example, faster turnaround cycles for list selections are fine (when quantified in hourly rates), but it is even better if the revenue from more customer acquisitions that follow from these selections can be tied in. Not only will the relation to revenue growth rather than savings make for a more balanced business case, more important is the intrinsic business buy-in that results from a direct connection to the company bottom line. These days, changes in legislation (in particular Sarbanes-Oxley) play a major role in justifying business cases. This may be either through a higher company valuation for its transparent information gathering, or, less sleepless night for the CEO, which is of course priceless...

4. Why Do Data Warehouse Projects 'Never' Go Wrong?

Actually, Data Warehouse projects do sometimes fail. But, they fail so rarely, that it is actually very hard to believe... Especially after having talked to so many disgruntled end-users. And there are many ways a Data Warehouse project can go wrong. Delivering on time, data administration issues, and unavoidable data quality issues in feeding systems. Corporate politics (see Tip 7) are probably the best explanation for this phenomenon of near 100% success rates on DWH projects. In my experience, the reason why a failure or 'semi-failure' can go unnoticed is either because senior management is not aware, or, let's say "unmotivated" to talk about misspending of company funds. As a result, not enough is learned. Maybe we as consultants have a stake in this as well, as this assures the industry plenty of ongoing business... J

5. What is Different About Warehousing Web Data?

Kimball & Merz (2000): "Although this clickstream data in many cases is raw and unvarnished, it has the potential of providing unprecedented detail about every gesture made by every human being using the Web medium". The subatomic nature of clickstream data poses unique challenges. There are fewer built in feedback mechanisms to ensure data quality, compared to other data streams. The relation between user mouse clicks and server log records is not as tight as in "traditional" transaction processing due to technical issues like proxy servers and caching. Because of these differences, IT people need to adapt to the web process flow, rather than having the process adapt to IT needs as is common for most other DWH interfaces.

6. Which Data Should Be loaded In The Data Warehouse?

The data that enter the DWH ultimately determine its place in the organization. A "let's load all data, to be safe"-attitude is a sure fire way to derail your DWH project. Choices as to what should and should not be included need to be made early on, to keep the project manageable. After proven success of the delivered, deployed, and profitably exploited DWH, there always will be funding somewhere to include previously ignored interfaces. Given the anticipated lifecycle of the DWH, it makes perfect sense to consciously exclude certain sources. The choice as to what data to include needs to be driven by business considerations, and in particular reference to the company bottom line. If it can't be shown how data will be put to use profitably, they stay out! See also tip #3.

7. Data Warehousing & Company Politics

Data Warehouses have an impact on the company bottom line. Hence, they are likely candidates for turf battles, and are also at risk of becoming "small change" in budget allocation negotiations. None of these considerations benefit corporate long term goals. Managing a DWH project is hard enough as it is, and budget issues shouldn't make it any harder than it already is. Because DWH investments are in the present and revenues lie in the future, it is even more important to secure funding through a sound business case and buy-in from the appropriate (high) management level. See also Tip #3. Access to data means power, and talking about power is one of the greatest management taboos, still around. Sensitive as they are, even budgets are more readily discussed...

8. Data Warehouse Projects Traps

Some commonly recurring 'roadblocks' on the path to timely delivery of a Data Warehouse project:

• ETL processes have eaten up so much time (and still need "babysitters"), that little if any time is left to develop applications needed to exploit the DWH
• Some data are needed, but turn out not to be unavailable, or not in a timely fashion
• Maintenance required for tuning, indexing, and backup and recovery is severely underestimated
• Different ways of calculating the same phenomenon lead to different results, and nobody is able to conclusively explain the difference(s)
• The data that is loaded (and recombined) turn out to contain previously unknown inconsistencies in the source systems, the 'classic' data quality issues that trip DWH projects
• Metadata were lacking, and developers spend inordinate amounts of time finding out what a field really 'means'

In Data Warehousing, it is not about hardware, and not about software: it is about the perfect integration of these two. Those who begin their project from either end, will pay dearly for this mistake. Reasons are:

· in terms of price/performance, new, pre-integrated hardware-software combinations are taking the lead

· from a project management perspective, you never want to be caught between vendors when a proposed solution doesn't work as expected

· database tuning and indexing is very important and a hugely complex job, necessarily left to specialists (in-house trained)

10. Performance is Key

Although I don't often find technology factors to be this important, in Data Warehouse acceptance, no other factor will be as important as performance. As size increases over time, this factor becomes even more important. There are three reasons for this:

1. performance has a huge impact on the development speed (initial load is always very time consuming), and hence the overall maturity of the DWH at delivery time
2. performance can make or break end-user acceptance, in particular the predictability of performance
3. performance has a tremendous impact on end user productivity, the ultimate driver of the business pay-off

Source Data Warehousing - Tom's Ten Data Tips

If you want to get information on all the techniques of designing, maintaining, building and retrieving data, Data warehousing is the ideal method. A data warehouse is premeditated and generated for supporting the decision making process within an organization. When the production databases are copied in the warehouse, it becomes easier to answer all the queries without hampering the consistency of the production system.

A data warehouse is actually a set of new concepts and important tools evolved into a technology. With the help of data warehousing, it becomes easy for an organization to counter all the problems faced during providing key information to concerned people.

Over the last two decades, a number of experiences and technologies incorporated together to evolve the new field of Data warehousing. You can say it as a well organized and resourceful method of managing & reporting data non uniform and scattered sourced throughout an organization.

Because of hundreds of gigabytes of transactions, it is necessary for a data warehouse to be vast. Therefore, "data marts" are often designed for individual department or a product line. A data warehouse system is an influential and necessary platform for merging data from old and new applications. You can transfer rules to a warehouse without making much efforts. The prime features of a data warehouse is that it records, collects, filters and provides basic data to different systems at higher levels.

Here are some of the benefits of a data warehouse:

o With data warehousing, you can provide a common data model for different interest areas regardless of data's source. In this way, it becomes easier to report and analyze information.

o Many inconsistencies are identified and resolved before loading of information in data warehousing. This makes the reporting and analyzing process simpler.

o The best part of data warehousing is that the information is under the control of users, so that in case the system gets purged over time, information can be easily and safely stored for longer time period.

o Because of being different from operational systems, a data warehouse helps in retrieving data without slowing down the operational system.

o Data warehousing enhances the value of operational business applications and customer relationship management systems.

o Data warehousing also leads to proper functioning of support system applications like trend reports, exception reports and the actual performance analyzing reports.

Precisely, a data warehouse system proves to be helpful in providing collective information to all its users. It is mainly created to support different analysis, queries that need extensive searching on a larger scale.

What makes a data warehouse important for a company is its ability to gather information from different parts and then making them a single part of a centralized database. It is a collection of data, which is further used by employees for an easy and smooth working process. Know more about data warehousing by reading the article.

Data warehouse is an asset for an organization because it maintains the efficiency, profitability and competitive graph. A company collects data from sources like inventory manageable, call center, sales leads etc., which is then passed through the Data Life Cycle Management policy. It is this policy of the organization that determines the design and methodology of the data warehouse.

The main motive of a data warehouse is to create front-end analytics that will support the operation staff and other employees of the organization. Here are some of the elements of a data warehouse:

Pre-Data Warehouse

This zone provides data for the data warehousing and the team of designers filters out the data that contains business value for insertion. Operational data is stored in OLTP database, which resides in transactional software applications like supply chain, ERP etc. OLTP's are designed for high transaction speed and accuracy.

It is the metadata that ensures accuracy of data that will be entered into the warehouse. Most of the organizations reduce cost for the ETL stage by opting for a metadata policy.

Data Cleansing

Data cleansing is the extraction, transformation and cleaning process that are done to ensure the quality of the data before it is entered in the warehouse.

Data Repository

Data repository is a database where active data of an organization is stored. It is then optimized for data analysis.

There are two types of data warehouses - ODS and Data Marts. Although data marts are no different from data warehouses in physical terms but they can be smaller and are built on departmental level instead of company level.

One drawback of data warehouse is that it collects data and has older data as well, which means you will not get an up-to-date analysis. Operational Data Stores can be useful when it comes to storing recent data before migrating to the data warehouse.

Front-End Analysis

Front-end application that will be used by employees is the most critical part of a data warehouse. They will use it to extract information and interact with the data stored in the repositories.

Data Mining

It is the discovery of many useful patterns in the data. Data mining is used for analyzing and the classification process.

Data Visualization Tools

These tools are used for displaying the data from the data repository. Designers often combine it with data mining and OLAP tools. The process of data visualization helps users in manipulating data as per its relevancy and pattern.