Any established blogger or publicist that deals with data-related topics has some opinion on data-centricity versus data driven organizations. The most creative comparisons have been presented to describe the usefulness of a data-centric approach in a data driven organization. While they are creative, they do have good points and hopefully convince the reader of the difference and the two terms.
A huge lake filled with fish
Data is like a huge lake filled with fish (the proverbial “data lake”). Different fishermen will have different fishing rods or even fishing boats to try to catch fish in the most effective way. But if you take away the fishermen, you will still be left with a lake full of fish. When you translate this to data; organizations have many data, that is a fact. No matter how many tools and applications you will implement to manage the data, the data will always be the heart of the organization, left untouched once the applications change or be deleted.
The problem with the application-centric approach
It must be clear what the difference is between data and tools and applications. Let us move on to the data-centric versus data driven part. Huge organizations come with huge data, that is inevitable. But how they deal with these data is where the big difference, the largest budgets and the most time is spent on.
Organizations implement applications that will store, manage or report on data to provide them with insights in their most important KPIs, ignoring the remainder of the data in the organization. The data models included will not be universal and are based on rigid processes suiting the needs of that application. Decisions are based on the outcome of these applications ignoring the information that other data might have uncovered. Since this important data is isolated in these applications there is no telling whether the data is complete, accurate or even reliable. Better yet, or even worse, these data are only accessible to the users of these applications. This creates different silos in organizations, both in applications as in departments. While organization using this approach might think they are 100% data-driven, most of the time they make decisions based on only part of the data.
Adopt the data-centric approach
Instead of using an application-based approach in these data driven organization, they are better off using a data-centric approach: put the data at the heart of the organization, place it in a centralized position where everybody has access to it in a universal, consistent way. One database, one structured way of accessing it, for everybody to use. This huge database must be structured in a consistent, consumable, and integrated data model. A model that describes the hierarchy of data, the parent-child relationship between data and most importantly, includes all the data of the organization that can be maintained in a well-organized way.
Complete and reliable data to base decisions on
When you structure your data in a data-centric approach you create a “single source of truth”, one transparent database for everybody to access, eliminating any departmental or application silos. It allows for people and departments to better communicate with each other and empowers better collaboration. You work with a unified governance of accurate, complete and reliable data and data processes that will never be up for discussions. These data are company-wide pure and integrated, always up for any export into any needed format. These data can be imported and exported from different tools and applications always referring to the pure data at heart.
If any organization wants to be truly data driven, the most important condition is that they first adopt a data-centric approach.
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