Everyone wants a piece of Big Data action whether you are part of Product Company, Solution provider, IT, or Business user. Like every new technology, Big Data is confusing, complex and intimidating. Though the idea is intriguing, the confusion begins when the techies start taking sides and tout the underlying tools rather than solution. But the fact is picking the right architecture (tools, platforms) does matter. It involves consideration of several aspects starting from understanding the technologies appropriate for the organization to understanding the total cost of ownership.
When you look at the organizations embarking on Big Data initiative, most organizations fall into the following 3 types.
De-centralized
Have experimented with several tools, multiple deployments done in multiple platforms by multiple business units/subsidiaries. Own several tool licenses, built several Data applications or experimenting currently. Many data management applications in production.
Loosely Centralized /Mostly De-centralized
Has Enterprise focus but BU’s and departmental Data applications are in use. Also several tools purchased over the years across various BU’s and departments. Many data management applications in production.
No major Data Applications
Yet to invest in major data applications. Mostly rely on reports and spreadsheets.
In all of the above scenarios, IT leaders can make a big difference in shaping the vision for embarking on a Big Data journey. Mostly Big Data projects have been experimental for many and the pressure to deliver tangible results is very high. Typically optimal tools strategy and standards takes a back seat. However at some point it becomes a priority. The opportunity to focus on the vision and strategy is easier to sell when leadership change occurs within the organization. If you are the new manager to tackle Big Data, it is your chance to use your first 90 days to formulate the strategy than get sucked into business as usual. Utilizing these moments to formulate a strategy for platform / tools standardization is not only prudent but also presents greater opportunity for approval. These strategic focus is critical for continued success and to avoid investments with low returns.
The options within Big Data is vast. Vendors with legacy products to startup companies offer several solutions. Traversing the maze of products without the help of right partners can lead to false starts and big project delays.
