With it the enterprise will be able to identify key business challenges to be overcome, the business process requirements that define how big data will be used, as well as the architecture, data, tools and hardware needed to make the blueprint a reality.
It also provides the basis for developing a roadmap to guide the organization through practical approaches to the development and implementation of its big data strategy.
3. Start With Existing Data
To achieve short-term results as the big data implementation starts and gathers steam, enterprises need to be realistic about what they can achieve initially. For those that have implemented a successful strategy already that is providing business value, the easiest place to gather insights is from information that is already in the enterprise.
Doing this enables an enterprise not only to use easily available data but also the skills and software that are already in place. This provides immediate benefits as they make the business case for extending the big data analytics to include more complex sources of information and types of information.
Most successful strategies have started analyzing existing repositories of information while scaling data warehouses to handler larger volumes of information for future insights.
4. Business Priorities, Skills Investments
As the market matures, businesses are being forced to choose between a growing number of analytics tools while, at the same time, having to deal with a critical shortage of analytics skills in both the US and Europe.
Big data success hinges on finding a way around this, which has seen IBM set up special analytics colleges in the US and Canada.
But for the moment, businesses will have to work in a market as it exists now and that means investing in tools and skills. As part of this process the research suggests that new career models will emerge for individuals with the requisite balance of analytical, functional and IT skills.
For those that already have the skills in-house, enterprise must focus on professional development and clear career progressions; investment in these people at the moment should be a top priority for executives.
5. Measurable Outcomes
To develop a viable big data strategy and to ensure that there will be ongoing interest and investment from decision makers, enterprises need to ensure that the case for ongoing investment is based on quantifiable business outcomes. In other words, business leaders need to be able to see the advantages.
Businesses can do this by ensuring that there is active involvement and sponsorship from one or more business leaders when the original strategy is being developed and when the first implementations take place. Also of crucial importance here is ongoing cooperation between the business and IT departments. This should ensure that the business value of all the investments in big data analytics is properly understood.
This paper and the research around it have a lot of insights for businesses that are considering their first big data deployments. Like all other IT elements in a business it requiems thorough planning before execution. This paper makes a good starting point.