Mitigating Big Data Cost

Author: 
Larry Xu

The era of Big is here and here to stay. The need for Big Data strategically is ever pressing, as the traditional EDW (Enterprise Data Warehouse) can no longer handle the explosion of Big Data. While presenting widespread opportunities to the enterprises, managing Big Data also comes with a BIG cost.

In spite of all the hype and buzz of Big Data, when the dust settles, organizations will face one of their BIGGEST challenges: money. According to some statistics, companies will spend an average of $7.4M on Big Data-related initiatives over the next twelve months , with enterprises investing $13.8M, and small & medium businesses (SMBs) investing $1.6M. 80% of enterprises and 63% of small and medium businesses (SMBs) have already deployed or are planning to deploy Big Data projects in the next 12 months. Naturally, understanding and mitigating the cost of Big Data is the top priority on decision makers’ agenda.

Before running a Big Data project, it is desirable for enterprises to consider some key elements, including:

  • Big Data roadmap.
  • Know you business requirement.
  • Leverage existing data infrastructure.
  • Identify and understand new innovative technology.
  • Consider a hybrid analytic data architecture.
  • With more and more companies budgeting for Big Data initiatives in the near future, understanding and mitigating Big Data cost has become a top priority on decision makers’ agenda. Cost-effective ways of implementing Big Data projects will certainly save companies millions of dollars, money that can be budgeted elsewhere for other projects.

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