BI or Business Intelligence

BI CubeSome time ago I started this series of blog posts on Information Management. Just to recall we are talking about People, processes, content, and technology. Today I’d like to dive a bit into the content aspect.

Big Data

has a number of components, namely volume, variety, velocity and lifespan.

The volume of information we create and capture has increased exponential over time. Using electronic systems has made that a lot easier than just 60 years ago. And sensors everywhere – thinking “Internet of Things” will continue to push that volume up. Although, volume is no substitute for quality. Finding the information that has value for you (or your business) is critical.

Many data sources are now from automated systems. If you ever watched “Person of Interest” you know what I mean. But simple things add to the variety of information that is collected and created. Think SmartPhone (location based data), wearables (heartrate, …), optical sensors, pressure sensors, and so on. Not everything is standardised and that makes it challenging from a technical perspective to sort, analyse and generally make sense of it. Just have a quick look at the different standards for spatial information.

10 years back doing a daily back up was acceptable and monthly ones were kept for a long time to cover regulatory compliance. Just a few years later many organisations couldn’t complete a full back up every day. The schedule timeframe was too short. Incremental back ups were necessary to cover just the changes. Velocity driven data management started then. Today sensor created data and the multitude of people providing information are updating the knowledge of many domains continuously.

Quality

All 3 factors provide us with up to date information. It’s just the question to find the relevant information for our specific challenge. BI or Business Intelligence is the key buzzword for some time to address this. ETL or Extract – Transform – Load are the processes BI employs to provide actionable information from the big bucket of collected data. BI relies heavily on the accuracy of the source data and their actuality. Hence 2 processes are consistently applied, one that ensures outdated information is archived or reviewed and another that qualifies the data on its source reputation.

BI can then be applied to provide 4 stages of information

(1) hind sight – an explanation why something has happened

(2) summary – a condensed version what is happening right now

(3) foresight – an exploratory view of what might happen

(4) influence – a set of possible actions to achieve a certain result in the future

Challenges and Opportunities!

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