Pressed to pick a big-data platform, enterprises may wonder where to begin. Making matters worse, vendor-neutral information on the topic can be hard to find amid a sea of sometimes-conflicting marketing collateral from over-eager vendors.
To address this information gap, the Open Data Center Alliance (ODCA) late last year published The Big Data Consumer Guide, a document intended to establish "a common language and definitions that enterprises can use when working with Big Data vendors," the group said in a press announcement.
One differentiator of ODCA's documents is that they are developed by end users -- specifically by people working for large enterprises and representing a variety of industries (financial services, travel and leisure, manufacturing, entertainment, and so on). An independent IT consortium, ODCA's 12-member steering committee, includes BMW, Capgemini, China Unicom, Deutsche Bank, JPMorgan Chase, Lockheed Martin, Marriott International, National Australia Bank, NTT Data, T-Systems, Terremark, Disney Technology Solutions and Services, and UBS. Intel serves as technical advisor.
In an email exchange, ODCA Executive Director Marvin Wheeler told me:
We hope that the impact of this initial publication is the same as the other publications from the ODCA -- that end users are able to use the information to be better informed; can better frame the discussion of Big Data; and that they understand what characteristics are important and how to best to develop a strategy for the optimization of big data storage pools.
Also welcome is the 24-page guide's clear writing style, as in this section on "The Big Data Evolution":
Although Big Data has some new -- and fairly disruptive -- characteristics, it is simply the next step in a long evolution of enterprise reliance on data. In the early 1980s RDBMs were fledgling systems, and then grew into billion-dollar enterprises such as Oracle and SAP. With the growth of the Internet, it wasn't long before enterprises turned to online transaction processing (OLTP) databases, then to dimensional data warehouses (DWs) to meet their data storage and analytic needs.
Today we stand at the threshold of yet another transformation, where those who 'get it' will continue to thrive and grow, and those who
remain lodged in outdated technologies will fall by the wayside. What used to be considered a storage problem is now a strategic asset.
The guide received a positive review from one big-data scientist and consultant who'd seen it.
"OCDA's report is [a] comprehensive review of Big Data landscape, looking at the many dimensions of this space, whose technologies are disruptive," wrote Kirk Borne, a professor of astrophysics and computational science at George Mason University, in a direct message to me on Twitter.
OCDA's 300 members use the group's previous publications on security, transparency, and inter-cloud operability for request-for-proposal development and IT strategy decisions. Wheeler said he expects the same for the big-data guide.
Creation of the guide began last April inside the ODCA's Data Services Working Group. Along with terminology, the guide provides an overview of big-data topics and offers a simple table with 30-odd uses (Fraud Detection, Network Modeling, Marketing Campaign Analysis) and the industries for which these uses would be most appropriate.
Asked about follow-up plans for the guide, Wheeler wrote: "All documents from the ODCA are a living process, so there will be updates over time."
Have you taken a look at the ODCA big-data guide? Let me know what you think about it.
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