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Real Learnings From Real BI Implementations

There is a lot written on best in class practices for deploying BI in operational business intelligence projects. For some real world examples with more specifics on ‘How To’, this post on CIO.com India offers insights from several companies.

Two key requirements in most projects focus on moving data closer to the business and monitoring all data though a single system. However, in reality most projects have found that processes don’t fit neatly into single systems.

Data is still consolidated into a single data warehouse where formats can be transformed and analytic rules applied. For example, time-critical information such as production data is gathered more frequently and often supplemented with other types of operational data, however rather than using the data warehouse as the platform for real-time data analysis discrete software tools are used to analyze transactional data.

Attempting real time analyses typically requires a big infrastructure upgrade that may not be economically justified in many companies. Not all processes — or even most — need to be monitored in real-time. Latency schedules should not be driven from the data availability end, but rather from the information consumption perspective. Most businesses struggle to conume information on more than a daily basis. Unless the data relates to mission critical transactions, real time is not required.

Selecting the right kind of data for real-time analysis, is based around what information provides insight into completion rate baselines. Data providing insight into how customers are using products or how to optimize business processes is not always required in real time.

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