How do you know where your company falls? Some of the best advice about how to address the big data question can probably be summed up by admonitions that we frequently give to our children:
* Set the table. The first step in any data project (big or otherwise) is to clearly establish what you're trying to accomplish. Additionally, it can be helpful to establish a visual picture or framework that organizes the business around an end game and breaks down the problem into consumable, achievable initiatives. With all the excitement around the big data concept, it's easy to get pulled into an initiative with objectives that are likely to change as you go along. Defining upfront what you need helps determine if big data is the answer and puts parameters around what you undertake if it is.
* Eat what we already have in the pantry. Many companies have valuable data ready and waiting to be exploited with the help of business intelligence and analytical tools. Before assuming that an expensive initiative around big data is required, determine what data you have and whether you can accomplish your goals with existing tools. Incremental capabilities can also be incorporated in a non-disruptive way, giving you a big bang for your buck by providing better, more consistent visibility to data and making it more consumable.
Analytic applications that surround existing information and transactional systems can effectively manage your data while also delivering a host of other benefits, like giving non-technical users simple dashboards that help them target specific problems and opportunities; delivering information directly and automatically to users so they head off problems and make better decisions; and making collaboration a standard part of your work processes.
* Finish what's on your plate before asking for more. All of the new data available today can be tempting. From Amazon to Facebook, we now have a dizzying array of choices that seem poised to unlock new and previously untapped opportunities. However, the data you already have can be equally as valuable, if not more so, because of its relevance and quality. At some point, there are diminishing returns on adding more insight into the mix, as too many data sources can create "analysis paralysis," particularly for the average worker.
Improving your ability to deliver a highly focused view of the business with targeted workflows is likely to serve you better than focusing time and energy on what can easily turn into a great deal of outside noise. The best approach is to make sure you fully understand and exploit what's core to your business and already exists before taking on new, potentially complex and expensive data initiatives.
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