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Becoming a Data Driven ${Job Name Here}

Many areas and business functions are asking how to become data driven. While there is some tailoring involved due to the specific focuses of business units and job functions, it boils down to the same principles.

Understanding How The Role Fits

While all data generated by a business has to move towards an Enterprise Data Warehouse model for true data driven success, not every employee will consume every data element. The danger of information overload – also known as ‘analysis paralysis’ – is great in potential data driven individuals. It is important to not only understand what data is critical for the given role and business unit but how it impacts the enterprise-wide picture. Having someone trained in gathering business requirements (known formally as a business analysis) that can perform data discovery is key for any team.

Knowing Your Quality Data Sources

One would think that this is a no-brainer, but data that is not fit for purpose is being used for decision-making. Having a data source that grades on data quality parameters that is of concern is a critical first step on the path of becoming data driven. Ignoring the fact that a data source is incomplete or misrepresenting the subject might lead to the wrong choices being made in the decision-making process.

Data quality discovery also helps data consumers understand their data sources even more. As processes and source systems increase in complexity, so does the data! There are quite a few different avenues to determine quality. On the more technical side is data profiling, which is the process of learning the statistics behind the data set. Some typical measurements in data profiling range from the number of values that are all uppercase or lowercase to more complicated logic like date gap analysis or business rule application analysis. There are many other processes that involve the business as well as IT, such as rules engines and metadata repositories. Rules engines store the logic and formulas required for the business to operate in such a manner as to allow technical processes to use them without much extra processing or coding. Metadata repositories follow the same kind of logic as rules engines, but act as a central repository for data quality metrics.

Regardless of how it starts, once data quality is understood and managed the decisions being driven off of that data will become more valuable.

Knowing Your Data Tools

Equally important in the quest for becoming data driven is to know the tools available. Being able to deftly work around in the chosen tool set of your business will allow focus to be given on learning the data and finding the trends. The danger here is that there are many flashy wiz-bang tools and the marketing departments behind them to make each one of them attractive options. If every business area has their own tools then there is the potential for there to be a different answer from every area for a given question! Unification of tools across the business is key to helping the business become data driven.

Other Areas

There are many other areas like Data Governance and Metadata storage that can pave the path to becoming data driven. Let me know if there is an area of interest and I will be sure to cover it in a further post.

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