Business Intelligence: A need for transaction processing systems

Why is Business Intelligence required? In short: transaction processing systems do not provide adequately for the analytical and reporting requirements of business people.

There is often a lack of ways to analyze and report on all the valuable data that is embedded in our every day applications (also referred to as transactional processing systems or OLTP). It is true that without our OLTP systems our businesses cannot function. OLTP systems are essential for the business to drive the daily operations. However the key focus of such systems are “getting the data in”, in other words making sure that the transactions are stored securely and making sure that each individual transaction can be traced. On the other hand finding the best way of “getting the data out” for analytical or reporting purposes poses a challenge that many organizations disregard.

The difference between Business Intelligence and Online Transaction Processing Systems

OLTP systems drive the day-to-day business and are based on business processes that are translated into computerized systems; Enterprise Resource Planning (ERP) being one example of such a system.

If we compare the differences in the Information Value Chain – from an operational or OLTP perspective, we realise that the focus is on a series of events. In other words it takes a microscopic view, based on transactions. It plays a very important role: without a detailed picture of individual orders, sales, shipments, banking transactions and so on, the business can not run.

However this approach is not suited for answering questions such as “Show me the best selling product line of last month/last quarter/last year” or “compare current month’s returned-orders to the same period over the last 2 years”. This is where Business Intelligence (Analytical systems / the Data Warehouse) steps in – it fills the gap as it reflects the way people look at their business over time. Business Intelligence is process driven not data driven – it takes a broader view of the entire process making it possible to analyse data from different perspectives (for example: by Region, Year, Quarter, Branch, etc.). It provides effective methods of storing historical data, structured in such way that it can be retrieved in acceptable time frames.

What is Business Intelligence actually? The definitions are vast and varied but in a nutshell Business Intelligence (BI) is a concept for delivering specific and useful information in the midst of the data-explosion organisations are facing today.

BI is a corporate weapon to fight fraud, waste, and abuse. It empowers decision making at all levels of management. It provides quick notification of business exceptions, advanced reporting and analysis capabilities and the ability to compare data to improve tactical and strategic management.

Underpinning Business Intelligence is a consolidated base of information (also called a Data Warehouse), which is shared amongst interested parties and structure in such a way that it can return correct information quickly and easily. The process that enables Business Intelligence entails clear definition of business requirements, translated into technical terms by means of Extracting, Transforming, Loading / Presenting data, often referred to as ETL or ETP. Transformation of data into meaningful information requires the application of specific context, derived in a flexible manner.

Complimentary Method
One of the biggest challenges in developing a data warehouse is determining the value of the data you keep. Wrestling with just the sheer quantity of data could destroy productivity. The successful data warehouse will be the result of a balancing act – volumes vs. value of the data.

A complimentary approach which speeds up the traditional way of collecting data is Enterprise Information Integration (EII). Rather than adding unnecessary data, Business Analysts, BI Project Managers and business stakeholders can systematically assess the value of new information created through EII. If the selected information proves to have lasting value, it can then be added to the data warehouse, ideally using the same software that is used for EII.

Unfortunately it frequently happens that great emphasis is placed on the physical design of data storage during the analysis and design phases, while paying less attention to the definition of high-level business requirements. Ultimately resulting in a physically well-designed data store but one that fails to connect with the organisations’ strategic objectives and user requirements. Once this mistake was made, attempts to use technologies such as reporting tools or analytical applications are invariably problematic and cumbersome.

This scenario can be addressed by adopting the use of technology sooner in the process, using it as a communication tool and enabling the Business Analyst and Business User to jointly define the requirements while at the same time discovering the data required to connect with strategic objectives. Time and effort can be greatly reduced by adopting this technique, demonstrating the value of technology early in the process whilst making sure that the business requirements can be accommodated by the available data.

The Business Analyst can be instrumental in avoiding costly mistakes and help the BI initiative (or data warehouse project) to remain on track. By using technology early in the process they can attempt to understand how data will be used prior to designing and loading it into a data warehouse.

Besides clear definition of Business Requirements, the design too will greatly determine the success of the data warehouse – since it will contribute to how easy (or difficult) it is to retrieve data for query and reporting, or any deployment purposes. It will also determine the degree of flexibility to gracefully allow for change. It is therefore very important to first of all have a solid understanding of the business and its processes, how people work, what kind of information they need, the kind of questions they are most likely to ask. This means a combination of business knowledge and the technical know-how on how to implement a solution.

There are a number of key drivers fuelling renewed interest in Business Intelligence for more effective use and delivery of information. These include:

1. Obtaining an overall view of business in order to facilitate more informed and faster decision-making.
2. Avoiding data collection from various places to enable efficient data analysis, thereby increasing staff productivity
3. To speed up reaction time to respond to events, in highly competitive environments.
4. To empower the knowledge worker.
5. To ensure transparency for Corporate Governance

It should be recognized that a consolidate base of information is required which:

1. Is modeled from a business user and query usage perspective
2. Offers support for aggregate management
3. Offers explicit techniques for tracking history precisely
4. Offers simplicity i.e. few tables, fewer joins

To date, becoming Business Intelligent has been largely problematic therefore making it difficult for management to obtain an overall view of their business. The problem of derisory reporting is not solved by slapping on some glitzy front-end reporting tool, as many BI vendors tend to do. Unless the underlying challenges of how you collect, clean and restructure your data is addressed, inadequacies of the reporting capabilities of operational systems will intensify.

In summary the focus of the consolidated base of information, that acts as the Business Intelligence enabler:

• should be designed for analytical efficiency, not operational efficiency
• should be designed for accessibility not for speed of update performance
• embrace historical data, not overwrite it
• be concerned more for time-related integrity
• designed to manage data content and data context (meta data)
• architected data delivery structures for multiple user communities, not just a single one.

In our quest of finding the most appropriate way to make information available it further highlights the complexity of determining and defining what business users require from an analytical system which may be one of the reasons that Business Intelligence initiatives are sometimes deemed overly complex or unsuccessful.

The correct approach to delivering information to the business requires innovative thinking and flexible designs. Your business may survive without applying Business Intelligence but you should not be surprised to be outsmarted by the competitors that do embrace this business approach successfully.

Written by: Susan Andrè, Managing Director, Alicornio Africa

About Alicornio Africa
Alicornio Africa has been a distributor of Group 1 Software in Southern Africa and other parts of Africa since 1999. Offering Sagent Data Flow and other software products from the Group 1 stable, as well as consulting service and training covering the entire spectrum of information integration, data profiling, data deduplication, data quality, data warehousing, business intelligence, data mining and customer communications management. For more information visit www.alicornio.co.za