A ‘Data First’ Approach

NewVantage’s ‘Data First’ approach targets getting more value, faster and at comparable or lower cost to implement.

Data First ensures maximum value in the shortest possible delivery time by targeting data content — how to get at it, break it down, analyze it, mine it, scrape it, and link it with existing relational data to create new insights, new analytic views, new business opportunities. It also assesses potential cost reductions by considering the use of big data technologies resulting in less dependence on higher cost software and platforms over time.

It’s all about the data. The “known” or traditional approaches to sourcing, loading, processing and enriching data are shifting under the sands of Big Data. NewVantage understand the “new” approach using Big Data technologies which value speed to market and flexible loading paradigms – images, video, semi-structured XML files, text and other formats can all be loaded into an Hadoop filesystem, for example, “as is”.

It’s not about throwing out the old. NewVantage understands that it’s equally important to use and capitalize on the known or existing data warehouses and be able to integrate with the “new” approach to get the best of breed from both platforms.

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Four Key Principles enable the Data First approach:

  1. Data Storage is cheaper and easier to manage on commodity hardware and open source software.
  2. Data modeling in big data environments should focus on subject area breadth — collect all the relevant data in one place for many uses vs. a select set.
  3. Goal is making data discovery easier – more accessible, faster, and usable. Data should be versioned, curated and tagged so that users can readily see the state of the data before using it. In this way, users can mine this data for potential analysis and new insights with total control while contributing to the overall ecosystem.
  4. Business driven analytics move at the speed of the data vs. the speed of ETL code releases and/or large batch jobs that run too long only to present day old data at best. On demand and real time analytics are within reach.

 

 

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