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Big Data #2: Planning for the Big Data Analytics

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Implementing big data and business analytics are two intertwined areas in current business and IT infrastructure. For many enterprises, big data analytics are in implementation or development stages, offering almost infinite opportunities to be exploited. But to fully exploit the opportunities, big data analytics has to be carefully thought of. Throughout the article, I will talk about the biggest issues that the enterprises need to address before implementing big data analytics.

First of all, the business and the IT need to be tightly aligned in all concepts of big data. The business should lay down clearly its expectations from the IT and the IT should lay down how it can meet the expectations. The expectations should also include possible scenarios, such as shift in consumer buying behavior, new product / competitor product launch etc. and ask IT about how the analytics can be used to respond to such changes. Without speaking everything out and addressing possible scenarios, big data analytics would be doomed from the start.

Then, the business and IT has to talk about their know-hows on the big data analytics. From the IT perspective, big data comes with big changes. There should be high performance clusters to crunch the data and specialized storage solutions to both store and serve the data. The storage solution has to have high-speed disks (SSDs or big caches) to store the frequently accessed data and lower-speed disks to store the less frequently accessed data and perhaps even lower-speed solutions to keep historic data for “just in case” scenarios. There are many solutions for these types of scenarios from the storage vendors. It would be wise to ask for specialized consultancy from the vendors to prioritize and to access big data. IT managers should include their storage staff in the strategic meetings and keep their training up to date.

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From the business perspective, big data analytics need training. Many businesses fall into the trap that if they can receive the reports they manually prepare from the big data system, big data analytics is implemented. The the case with the many migrations “we have been preparing these reports every month, can you make sure that we can receive them from the system with a few clicks?” is one of the worst things that you can do with big data. Big data analytics is not about automating reports, rather it is a tool to answer complex business questions. The consultants will also come with their preformatted report templates and tell you how it is easy to use big data analytics. Often those reports are not aligned with business requirements. To overcome these problems, it is necessary to send the end users to training to have an understanding of big data queries and how to answer business questions.

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From the datacenter perspective, the load on the servers and their roles will also change. High performance servers will be deployed, background data processing will be prioritized and the storage I/Os will increase. Considering the current values on the data center and the required results, there will be a different workload on the data center, which I will discuss extensively in the next article in the series.

The discussion about big data will come to a point of receiving outside know-how, which comes with big data vendors and/or consultants. In an area that is so new and so unknown, it will be wise to do so. Unfortunately many of the consultants (including my fellow colleagues) choose to work with predefined solutions in all the companies. I, on the other hand, believe that each company needs a different solution. To receive the tailor-made solution, the companies need to address clearly what they want to receive from the consultants.

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As you may have already realized, I have not yet talked about the budget planning. The gap between the business requirements and the current data center offering will be the biggest item in determining the budget. In terms of big data and the government requirements, the gap is more than a few more servers and some more storage space.


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