BI tools for datawarehousing

Datawarehousing process comprises of different analysis phases and one such phase is the Business Intelligence (BI) phase. While, data warehousing comprises the whole gamut of activities required to extract, transform, cleanse, and organize data in a manner that supports decision support or business intelligence requirements, Business Intelligence (BI) is the real objective and the outcome of a data warehousing system.

A classic example is the US-based supermarket chain Wal-Mart. With an estimated 1 terabyte of raw data, which is captured on a regular basis from its stores across the world, the data warehouse of Wal-Mart holds approximately 65 weeks of historical data classified by item, merchandisers, geographies etc. This data is then analyzed to understand buying patterns of the products carried by the supermarket, the sourcing patterns, the inventory carrying patterns etc, which would have a direct impact on the cost structure. This in turn would help the company to remain one of the largest and, more importantly, profitable chains in the world.







Generally, a data warehouse is where integrated and historical corporate as well as granular data is housed. According to many experts, the datawarehouse serves many corporate purposes and has no bias towards any one user or any one application. The data warehouse contains atomic data that can be shaped and reshaped at will - this data is small and granular, like atoms.

According to Bill Inmon, the Guru of data warehousing, "Data warehouse data represents the bedrock 'single version of the truth' data that corporations need." On the other hand, BI is a set of applications that can extract from the warehouse, information that is relevant to a department or a user for his or her decision making or monitoring purpose.

Explains Gaurav Varma, Oracle 9i Marketing Manager, Oracle (India), " BI draws data from the operation systems as well, as some of the intelligence is on day to day operations like daily cash flows, cash positions. For ex: average daily outstanding by product division or by sales person, top 10 contributors to margin by product-channel-time period forecasted cash-flow projections, etc". From OLAP to ROLAP and from neural nets to data mining, BI tools have come a long way.

The following three types of tools are referred to as Business Intelligence Tools:

Multidimensional Analysis Software - also known as OLAP (Online Analytical Processing)

— Software that gives the user the opportunity to look at the data from a variety of different dimensions. It is a process of analysis that involves organizing and summarizing data in a multiple number of dimensions. People can comprehend a far greater amount of information if that information is organized into dimensions and into hierarchies. The wide use of spreadsheets and graphs illustrates the need for people to have their information organized.

Query Tools

- Software that allows the user to ask questions about patterns or details in the data.

Data Mining Tools

- Software that automatically searches for significant patterns or corelations in the data. The process of finding hidden patterns and relationships in the data. Analyzing data involves the recognition of significant patterns. Analysts can see patterns in small data sets. Specialized data mining tools are able to find patterns in large amounts of data. These tools are also able to analyze significant relationships that exist only when several dimensions are viewed at the same time.

 

Different BI tools in the Indian market

In India, the market for BI tools is just at the basic level. As discussed earlier, often it is the enterprises that had implemented ERP or SCM solutions and who were sitting on a vast pile of data and information have gone for BI solutions.

Says StorageTek, General Manager, Vijay Pradhan, "Business intelligence can also be used to monitor key performance indicator (KPI) and its trends, to send alert messages when KPIs go beyond user defined limits. BI tools can be enlisted as modeling tools to aid in forecasting, business planning, data mining and prepare common reports like balance sheets."

Various BI tools are available in the market today. Cognos has four products in its suite-Powerplay, Scenario, Impromptu and 4Thought. While Impromptu is a simple query tool, PowerPlay is an enterprise wide analytical tool. Besides, the family of project management suites from Microsoft includes Project Server 2002 application and project management tools like Project Professional 2002 and Project Standard 2002 are also offered as integrated business intelligence solutions across multiple enterprise applications.

It has a web-based version also. Scenario is a datamining tool. Scenario reveals the relation between various sorts of data that is available. Oracle also has a whole set of tools. Oracle provides the data extraction and transformation tools, the database for storing the warehouse data, the query and analysis tools, and the reporting tools to create the business intelligence. At the same time Oracle Reports and Oracle Discoverer can drill straight into the operational systems to provide real time intelligence. By the same token, Oracle also provides ready to use business intelligence applications for the intelligence residing in the transactional modules of the Oracle E-Business Suite. More information on different datawarehouse vendors can be found here.

Research estimates say that it has grown nearly 4-5 times the market since the last 3 years when in 1999 the BI tools market was just Rs. 20 crores. To tap this emerging market, many companies have started bundling BI tools with their ERP packages. For instance, PeopleSoft bundles Cognos with its solution. And, this may become a common feature not only across the ERP segment but also in the data-warehousing segment.

According to Gaurav, "Availability of new technologies like massively-parallel processing system, and parallel database technology from vendors such as IBM and Oracle, and new intuitive query and reporting tools like MS Excel, Cognos and Brio are driving the data warehousing segment from the technology standpoint".

Different kinds of business intelligence

which are extensively used are

• Finance Intelligence

• Financial Profitability - Revenue, expense, profit margin, contribution margin, current ratio analysis



• Cash Flows - Key collection indicators, trading partner activity, supplier and invoice and payment activity.



• Cash Positions - Forecast

Purchasing Intelligence

• Purchase to Sales Ratio, Supplier Performance, Contract Leakage, Contract Savings, Purchases

Manufacturing Intelligence

• Process manufacturing, Production efficiency, Inventory, Product analysis

Sales Intelligence

• Product / profitability analysis, Sales force / channel analysis, Customer/win-loss analysis

Marketing Intelligence

• Campaign / event analysis, Real time personalization

Service Intelligence

• Problem/ resolution analysis, Scheduling analysis. There are other similar intelligence requirements for other areas.