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Operational Data Science

Team with diversity can work together for an enterprise to deliver Data Science workflow. 1. Person(s) with strong business acumen with Visualization skills. 2. Data Integration Engineer(s) with ETL skills on structured and unstructured data 3. Statistician with R skills 4. Smart programmer with Predictive modeling skills.

Interestingly, there is no right and specific order of delivery from these people. Having said that the person who has strong business background can work at both the ends of a shore i.e. in data discovery as well as in communicating the final result (either in terms of prediction or pattern or summarization). However, programmers can pretty much independently work in all areas of data preparation, data analysis and scripting to build datasets for modeling. In a same way, statistician can very much communicate the business result and reflection. Now after all these efforts what left is just a game of effective collaboration. Moreover, along with the right collaboration channel there should be a Data scientist(s) who can watch over and architect the whole work flow and should always be ready to design+code+test the prototype of the end product. So, this whole Operation Data Science need a collaborative team and an architect(s) with diverse skills. Read complete study on: http://datumengineering.wordpress.com/

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Featured Case Study

Financial giant goes green

The corporate IT group of a very large, worldwide financial organization with 100,000 employees, has initiated an ongoing “greening” process. This is focused largely on reducing energy use both to decrease the corporation's carbon footprint while creating a net savings in operational costs over the lifetime of new, more energy-efficient equipment, including new storage systems. This effort is not viewed by the IT administration as a one-time project but rather as a perpetual process of evaluating new technology in part on its energy efficiency and introducing it into the corporate data centers to replace aging systems as appropriate.

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Featured How-To Note

Planning a Green Storage Initiative

Fluctuating energy prices have heightened electricity and energy consumption as a major issue within the technology community. IT is a significant consumer of energy and IT energy costs have been rising disproportionately because of continued investment in denser IT equipment. Estimates from the EPA and others indicate that IT will account for 3% of energy consumption by 2012. While technology changes have decreased footprint, power loading (amount of power required for a square foot of data center space) and heat load (the amount of heat that has to be removed from a square foot of data center space) have both escalated dramatically. The result is higher energy costs to provide power and extract heat from the data center, and lower utilization of data center floor space because of power and cooling limitations. The technology trends are toward higher heat and power loading, which will exacerbate the problem. read more...