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Delivering A Data Driven Enterprise: Turning Data Into Valuable Knowledge

Donald Rumsfeld’s “known knows” is a famously quoted phrase from a response he gave in 2002. Since then, the world has changed significantly, transforming the way we think, act, and engage in an increasingly digital world. These changes are contributing to the world of business and technology, and are now driving organisations to become  Data Driven Enterprises.

A Data Driven Enterprise can be defined as an Enterprise that is capable of validating what is known, confirming that which is unknown and discovering the truly new. 

The need for a Data Driven Enterprise stems from a more competitive landscape which has emerged due to the rapid changes in technology. These have impacted the overall product life cycle, significantly reducing the amount of time available between conceptualising a new initiative and launching it. Today, companies need to deliver their best efforts within a very short period of time and gain as much as possible, as their competition is often able to adapt their products and services to nullify advantages quicker than ever before.

In order to remain ahead of the game, organisations need to;

  • Understand and satisfy the needs of their customers.
  • Understand the operational costs of satisfying those needs to qualify revenue opportunities.
  • Analyse and optimise their supply and delivery channels.
  • Understand their competition.

A Data Driven Enterprise helps build the systems needed to gather and analyse the data needed to understand such insights. It captures the activities with internal and external stakeholders which are performed via the enterprise infrastructure. It helps gather the knowledge that is required to improve understanding and strategy with solutions which are needed to stay ahead.

There is a huge value to utilising Big Data, but likewise there are several questions that needs to be clarified;

  • How to build a Data Driven Enterprise?
  • What are the various components of the organisation, one should look at?
  • What are the technologies which is need to build expertise on?
  • What changes needs to be done to the current infrastructure?
  • How much it would cost?
  • What would be the ROI and time to recover the cost while working within budgetary constraints?

It is my attempt in this blog (and the upcoming) to answer a few of those questions. I may not be able to answer each one nor I can say if there is a definitive answer for it. But it is always  better to have a conversation that leads to answers, which I intend to initiate or continue depending upon each situation that is presented.

The Solution:

Based on the experience gathered while working on multiple Big Data Initiatives, the answer lies in a four-phased approach described below. Since we work in a field of discovering patterns, I will also explain the pattern that I think we could use to deliver the Data Driven Enterprise.

  • Discovering
  • Defining and Planning
  • Implementing
  • Expanding
  1. Discovering

In this phase, the requirement is simply to identify existing challenges within the organisation.

  1. Defining and Planning

During this phase information is gathered from across the Enterprise about various data sources that can be tapped into to build the knowledge pool (A Data Hub, Data Lake etc.). These may include current systems in use as well as future plans to deliver new offerings. In this phase, an Enterprise wide infrastructure plan is built that would fulfil the needs of a Data Driven Enterprise.

  1. Implementation

The next phase relies on building the exact infrastructure which is required for Big Data as well as focusing on building a small Cluster. This will be a platform for building POC’s for the use cases which are identified in Discovery phase. This starts small, to build the hypothesis, solution, and then proving value.

Next, an automated pipeline will ingest, cleanse, process, analyse and visualise the information. This involves data scientists building various models alongside engineers that will be using these models to build data solutions. Finally, the business users validate the solution in order to help more effective decisions within their business units.

  1. Operational

Finally, once built, a solution can be scaled by focusing on propagating the knowledge and insights that were gathered throughout the Enterprise. Every stakeholder in the organisation can be empowered to use the knowledge gained from the data and apply it to their day-to-day decision making more effectively.

If you would like to find out more about how Big Data could help you make the most out of your current infrastructure while enabling you to open your digital horizons, do give us a call at +44 (0)203 475 7980 or email us at

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