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How was the data curated and what business logic was applied to produce the end result ?
Can I drill down and see those business rules to verify it accurately represents my business function ?
Most if not all executives have , at some point , been presented with a graph or Excel sheet during a meeting and been skeptical about what is projected in front of them . While the information may appear in a clear and attractive format , we remain skeptical because we don ’ t trust the data .
This is the real crux of the issue – the business logic built on the data is the crucial asset for organisational success . For any long-standing company , there are decades of business rules deeply embedded into the data systems that the executive team and their respective teams rely upon every day .
Yet trying to adjust , shift , double down and ask different questions of those datasets is a major constraint because those business rules are not transparent , easily accessible or adaptable . Imagine a world where all that business logic and the data models describing the business have been centralised , made transparent , understandable to business people and eminently reuseable .
Before losing hope and accepting the mediocrity of how we use data , consider this fundamental paradigm shift that is both conceptually simple and a true game changer in productivity – allowing your organisation to “ be brilliant ” with the data they already have .
The most valuable asset your organisation ’ s data holds are not the collection and storage of that data , nor is it in the visualisation or reporting that the data generates – it is in the ‘ business logic and business rules ’ that are built around the data . Any company can collect and store data as in the modern world , where data systems have proliferated .
Now imagine further that irrespective of which specific application , database , data warehouse or cloud systems are being used – or irrespective of which analytical tool is being used – everybody can now understand what business rules have been applied and track data lineage confidently .
Imagine the control , versatility , trust and agility now available to the business . The key to making this shift a reality lies in creating a data fabric using a logical approach , which allows you to leave the data wherever it is and connects to it virtually by applying a unified data access layer with common business semantics applied across all datasets . You can leverage this capability to build custom-tailored data stores to meet your particular needs , again without affecting the underlying data .
Vendors such as AWS , Azure , Google , Teradata , DataBricks , EMC , IBM , NetApp , Oracle , Cloudera , Hitachi and HP , to name a few , have made significant investments to help organisations collect , store and compute data more efficiently . Inversely , Microsoft , IBM , SAP , SalesForce , Qlik and Microstrategy have focused their investments on mastering how to visualize that data .
But what is missing here ? Asking two simple questions of the organisation can provide that answer .
Users no longer have to spend most of their time collecting and preparing the data , because in a logical data fabric , the available data is ready for you to leverage without the complexities of accessing it .
And here is the paradigm shift – a logical data fabric allows you to reclaim ownership of the data necessary for making informed business decisions that enhance both organisational performance and the business itself . p
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