The people who understand their data best are the users of it. Working together with the users we can recommend which BI products are the most suitable ways of viewing your data.

Data in itself is usually not that useful until we are able to analyse it and thereby use it to make decisions and to give us insights into patterns and trends. Data analysis turns raw data into meaningful information. In Business Intelligence terms if often involves KPIs (key performance indicators), measures and metrics. First you decide what your measures are, then you can build them into your metadata, either building a data warehouse or modelling the data directly into a product such as Cognos Framework Manager.

Measures help you analyse your data, but the data itself is often spread out across different systems, perhaps even different countries and even keyed directly into different spreadsheets and flat files. By using data warehousing techniques you can gather all this data together so it can be effectively analysed and so add value to your organisation.

The analysis itself can be done in a number of different ways. For example, metrics can be viewed month-on-month in a scorecard, KPIs can be tracked in a personalised dashboard. Data can be summarised using dimensional modelling, which puts it into hierarchies on which you can drill up or down. OLAP cubes are a popular way of presenting dimensionally modelled data.