August 24, 2020

Data Warehouse – your company’s intellectual capital

Back to blog

Based on the visualisation of data, BI solutions provide answers to questions. These can be straightforward questions, such as “How much did we earn last month?” But there are also more complex questions, such as “Which products have growth potential relative to the coming year’s market development?”

Based on the visualisation of data, BI solutions provide answers to questions. These can be straightforward questions, such as “How much did we earn last month?” But there are also more complex questions, such as “Which products have growth potential relative to the coming year’s market development?”

Let me go straight to the heart of the matter. Data is knowledge, and hence the company’s data represent a certain intellectual capital, the value of which only very few companies will be able to assess. People may well refer to BI, Big Data, AI etc., though not many companies actually succeed in providing such insights. Often the reason is related to the way in which a company’s data is made available and how it is structured. For instance, unstructured data needs to be structured to provide useful information.

This is where Data Warehousing (DW) enters the picture. DW is the structuring and storage of data, using an approach that enables the cleaning, structuralising, aggregation, and connection of data in ways that facilitate sharing across data sources and financial accounting, thus creating new insights and knowledge. Some hold the opinion that DW simply contains all data required in the support of a company’s decision processes, and thus the go-to-repository-for-answers facility is practically considered to be akin to a bible.

BI solutions are focused on providing answers on the basis of data visualisation. There are trivial questions, such as “How much did we earn last month?” But there are also more complex questions, such as “Which products have growth potential relative to the coming year’s market development?”

A study of a company’s decision processes will reveal such data sources as will most effectively support each decision and the way in which data should be made available. Next, a DW data model containing required data is established on the basis of a preceding prioritisation. The basic structure of the data model is fairly simple because it is divided into two groups: dimensions and facts. Dimension tables include keys, IDs, and attributes. Facts include dimension keys, attributes, and values.

In principle, I am no hug fan of the idea that a BI solution should support business operations and thus become a kind of report generator for the ERP system. I do acknowledge, though, that the BI solution is often a “better” data presentation feature – in particular with respect to data logging across business solutions. The update frequency of the DW can often be challenging if you require the BI solution to be updated at short intervals, say one hour.

Now BI elements are incorporated in all modules of the Dynamics365 Finance & Operations (FO365). An Entity Store is regularly updated with data from the ERP. Power BIs are applied and, in multiple areas, they are fully integrated with various workspaces together with other objects such as tiles. Good descriptions and documentation of what the built-in BI covers in terms of dimensions and values are available. The built-in Power BIs can be individually adjusted, albeit, in some instances, this will require FO365 development work.

So, is the BI built into the FO365 a sufficient foundation for an overall BI solution? Probably not, since the BI solution must be able to connect data from different data sources, save historical data and accumulate data. If required, the optimal solution may be a combination of a built-in BI with a DW-solution, with the DW storing data at the tactic/strategic level and in a historical perspective.

Lars Errebo, BI consultant/developer Daxiomatic