The 3 Pillars of Big Data and what one has to do!

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 As organizations are looking to become more data driven  many of the stakeholders that are embarking on this  journey are assessing the Big Data domain. Terminology  and expertise can vary as this field has a lot of moving  parts. It is almost as fun as researching and learning  nautical terminology.

 So how do you get to be a Big Data Admiral? What one  has to do in order to navigate successfully data oceans or  data lakes depending on the size of your company! Stats  vary on the expertise and what one should look for when creating such a program.

A significant number of organizations are still daunted of undertaking such task. Enter the 3 Pillars for your Big Data foundation:

data ocean monster

  •   Modernize Data Warehouse

Traditional Data Warehouses are not a good fit for Big Data. Just the unstructured data needs of the domain and storage can be very expensive to continue to support. Other areas to evaluate are ETL functionalities and disaster recovery.

  • Data Plenum and Data Juncture

In physics plenum means a space that is filled with matter (in our case data). In this part the essential planning is around a platform to be able to ingest the data across the company in an effective manner in order to get to the juncture stage. In the stage of data juncture, you should have all of the analytical functions finalized in order to start formulating decisions.

  • Insights

At the end of the day the purpose of Big Data is to help companies uncover hidden KPIs and Insights that lead to gains and profits for the organization. The main areas to consider are the development of dashboards/applications for the executives in your organization, reports via predictive analytics in order to help them get to the promise land.

In conclusion having early success in this type of journey is very important. The test part is to be open to collaborative ways of working and new ideas in order to achieve your company’s goals. Address the use cases that are important to your company. Assess if they are a Big Data problem first and then go to action. Most important be proactive and don’t wait for the business to be in a bad state in order to begin this journey.