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Data & Intelligence

Approaches to Embrace Big Data

Not every organization starts its big data journey from the same place. Some have robust business intelligence functions and capabilities, while others are doing great things with Excel. However, in order to drive efficiencies, support expected future growth and to continue its evolution to a data-driven company, most organizations are reviewing their current suite of software solutions, platforms and documenting processes and areas of improvement along with devising and executing a strategy to deploy modern business intelligence capabilities. Here are three different ways organizations can leverage a big data platform to evolve and become a more data-driven company empowering their business users to make fact-based decisions.

  1. Baby Steps from EDW to Big Data

Organizations that already have an enterprise data warehouse (EDW) built to provide insights into their structured data are expanding this platform to incorporate unstructured data, which is stored using open source software. It’s entirely feasible to use open source software to set up a big data platform. There are also vendors like Oracle and IBM who offer both hardware and software to set up a big data platform.

  1. EDW on Big Data

Companies that did not have an EDW in the past and are looking to build a modern business intelligence platform are considering a big data platform to reduce software costs and lower their total cost of ownership (TCO) to build an EDW platform.

Data Intelligence - The Future of Big Data
The Future of Big Data

With some guidance, you can craft a data platform that is right for your organization’s needs and gets the most return from your data capital.

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In a traditional data warehouse, all the required data needs to be structured before being stored in a relational database; this is also called “schema-on-write.” This approach significantly increases storage costs and also adds cost to the design of data models to store the information. ETL tools required to move and store such data add to the licensing cost. Since a big data platform stores data in a data lake and creates schema-on-read by using ML algorithms instead of a manual effort, it significantly reduces the cost to store and structure data, thereby reducing the TCO to build an EDW.

  1. Big Data Cloud Platforms

Cloud-based big data projects offer the opportunity to start a big data initiative, without the upfront capital investment and with the benefit of support from a cloud partner. Google, Amazon, Oracle, and Microsoft offer various cloud services for organizations to validate their proof-of-value ideas by leveraging big data cloud infrastructure.

Regardless of the approach taken, one thing is abundantly clear: big data is not going anywhere, and AI and ML will only increase the need for a big data solution. Every enterprise, and particularly the C-suite, needs to understand big data and how it can add value to the organization in order to drive change and lead projects from the top down.  Each of the approaches outlined above can be incorporated into your organization’s big data roadmap, the development of which should be every organization’s first step.


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Shiv Bharti

Shiv is the Practice Director of Perficient’s National Oracle Business Intelligence Practice. Shiv has solid experience Building and Deploying Oracle Business Intelligence Products. He has successfully led implementation of over 75+ Oracle Business Intelligence and Custom Data Warehouse Projects. Shiv has worked in multiple industries and with clients that include fortune 500 companies . He has Expertise leading large global teams, as well as in-depth knowledge across multiple verticals and technologies. Prior to 2008, Shiv was a member of the Oracle and Siebel Core Engineering Teams and responsible for the Design and Development of numerous Business Intelligence Applications.

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