Data Lens

You may have noticed from our site that the Data Lens is in beta.  It’s a lens that we’ve developed because we’ve been continually told that people don’t have control of their data.

In our EA consulting, we have seen:

  • Organisations that were unwittingly reporting incorrect MI figures because data was inaccurate or incomplete
  • Projects that intended to master and duplicate data that already existed in the organisation
  • Inconsistency in what people thought certain data was
  • Differing views on where data was sourced from
  • Projects repeating the same data collection work, asking the same questions again

The Data Lens looks to address this by bringing transparency and coherence to your data estate.  It is aimed at supporting the demands of people wanting to use data, such as:

  • Data Lake or Analytics efforts, which need to know information such as where data is sourced from, what terms are used for the same data, e.g. client and customer, how good the data is in terms of quality and completeness, etc.
  • Platform projects need to know where data masters exist, where data flows, how data is transformed, etc.
  • Any data rationalisation project needs to know where master sources of data exist, where duplication exists and how data is used.
  • Plus, Data Scientists need to understand the sources of data available for their analysis

The lens addresses these needs by providing a number of views and tools.

The Data Definition views provide data definitions, summaries and dynamically produced data models.

The Data Architecture Analysis views are geared towards you understanding sources of data, data flows, where duplication exists, etc.

Data Management is where the lens excels.  You are able to understand data quality across a number of criteria and see sources of data.  The Quality Dashboard shows the quality of the key data required to support your strategic objectives and business capabilities, and also the initiatives impacting that data.  This allows you to identify where your data initiatives may need to be focused to improve your business data output and enable your strategy.  The Data Quality Analysis page lets you pick the data you need and it then shows you where to source it from, plus the quality, completeness and accuracy of that data. This is really useful if you are using the data for other purposes, e.g. MI reporting or analytics. The data dashboard provides and summary view of your data which you can drill down into.

We see the Data Lens acting as the bridge between the tools that are more focused on the physical data layer, and which typically meet the needs of the technical teams but not the business users or the data scientists.  Equally, where you have conceptual data in a tool, the lens can act as the bridge to the physical data, removing the gap between the conceptual and physical layers, bringing context and meaning to the data.

The lens is currently in beta but we are allowing organisations to register an interest and we would love to get any feedback on the lens.