Just like an iceberg, the data collection, provision and blending process is under the water’ and unseen by the business consumer. However, these processes set the foundation and account for 75% of the effort in an analytics project.

Why

What’s the foundation of a successful data analytics & reporting project? Getting access to your data, blending it together and making it available to the right people in the organisation? In the past these seemingly simple steps often became insurmountable. You can’t find, let alone access, the data that you own or the IT team requests a 25 page business requirements document before they even start to discuss your project.

What

Business requirements are a thing of the past because people don’t know what they don’t know. We challenge the old school.  We love technology and we love innovation. We combine technology like in-memory analytics and modern project management approaches like agile and prototyping to shake up the data extraction and blending process.

Forget about defining and building a cube over a two month period. Sit down with us, extract, review and load all the data into a data lake in days. Start prototyping in hours.

Who

IT play a key role in any business; to enable the strategy from a technology perspective. That’s why we work closely with IT to enable our rapid approach to data analytics. We’ve invested heavily in partnerships with the leading cloud providers i.e. if it doesn’t exist right now then lets spin it up in the cloud. We also recommend using software that was designed for modern computing e.g. in-memory analytics.  IT can help to facilitate these things.

The business needs to also come on the journey.  It is your responsibility to understand enough of the technology to “be dangerous”.   You can interpret the data, you know the business processes, strengths, opportunities and weaknesses.  These insights inform the data collection and blending process and eventually the business as usual data analytics and reporting.

The BI iceberg

Business intelligence iceberg
Visualisation & analytics (what the user sees)
Data modelling & manipulation
Raw data extraction & transformation
Server setup, database connectivity & infrastructure