Big Data Project Planning and Deployment: 10 Suggested Best Practices

By Chris Preimesberger  |  Posted 2012-11-21 Print this article Print
Recognize the Opportunity

Recognize the Opportunity

Big data is everywhere, so find your opportunity to put it to work. If your organization does not produce "big data," there are still valuable external data sets that, if you could access and analyze them, would provide better operational insight and deliver a new competitive advantage. For example, professionals within the financial service sector can pay a small amount of money to access a huge amount of intra-day trading information (equity exchanges, commodity exchanges, etc.) in order to find key data that can help them make more strategic business decisions. Or a wide array of census and population information is now made available by many government organizations. The world of data has become much more open. How can you participate?


Big data, the collection and analysis of various types of data in large volumes to create business insights and advantage, is a fast-growing IT trend that is on the lips of many corporate executives and IT managers these days. It is certainly true that excellent tools are available to build these projects now. These tools include big data-ready storage, intelligent networking, increased processing power and high-end analytics. Some of these tools are even available as services from cloud providers. However, like any other emerging trend, the reality is that we are in the early stages of developing any real best practices for putting big data to work. Fortunately, there are a growing number of IT people who are now harnessing big data to the business advantage of their companies and we can learn from them. For example, according to a recent survey from Jaspersoft's 310,000-person user community, 62 percent of respondents have either deployed or are planning to deploy applications that use big data stores in the next 12 months. In the following slide show, eWEEK contacted Jaspersoft CEO Brian Gentile to explain best practices for planning and executing a big data project for any size enterprise. Jaspersoft specializes in self-service business intelligence that scales for cloud, mobile and big data environments. San Francisco-based Jaspersoft competes in markets with Microsoft (with SQL Server), Truviso, MiAgents and Millbrook.


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