4 Key Ingredients For An Effective Big Data Implementation

4 Key Ingredients For An Effective Big Data Implementation

4 Key Ingredients For An Effective Big Data Implementation

Do you know about the Big Data dilemma? It’s currently a problem for many businesses.

It is divided in two forms which are all ringing alarm bells for both CIOs and CDOs because the competition starts to get more serious about dominating market share. In the first form, the dilemma is that when it comes to Big Data, many businesses do not know where to begin, how to manage the multi-phased Big Data programmes. The second form is that a business has a Big Data programme but it is not aligned with strategic business initiatives and so it is not delivering expected outcomes.

Assess internal Big Data capability
It is believed that its own excellent Big Data technology is not enough to create a winning Big Data strategy, but it is the phase that most businesses stop at when it comes to assessment. The problem is that businesses do not stop to consider whether the technology is fixed with the Big Data associated business goals and whether there is underlying technical infrastructure to support it, as well as skilled stakeholders who believe in it.

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Naturally, this assessment gap is most clear in businesses which have made an effort to put a Big Data programme in place. These companies can benefit from assessing what the original business goals are before moving to assess the governance perspectives of Big Data. After that, they can start the process of selecting the Big Data solutions that meet their objectives and goals.

Create a data-driven culture
Big Data governance is a very key ingredient to Big Data programme success. However, create and maintain a data-driven culture is equally important. There is useless in bringing Big Data experts into a company that does not have data-driven culture, mindset, and infrastructure where it is accessible when needed.
When it refers to developing the mindset and sharing data with stakeholders, organizations have to work together to make sure that they understand what they expect Big Data to do for them.



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