Keys to Solving Big Data Issues

Earlier in our big data series we explored the rise of big data and some of the specific factors that define it.

We also examined a handful of reasons why big data is important and why companies and governments alike are using it to predict trends and customer behavior.

In this installment we’ll take a look at some of the keys we use to solve emerging big data issues. Of course this is just the tip of the iceberg. Dealing with big data can be a tricky proposition if you don’t know where to start, and the challenges it presents are constantly changing.

One challenge many of our clients face stems from having “bad” or incomplete data. In many cases they either don’t know what data they should be capturing or they track the wrong things.

Other companies struggle because they try to capture everything, but either don’t know how to process it or they don’t have the capability, time or resources. Remember, the more data you start with the more issues that begin to crop up. It’s important to identify what data can truly help you improve your business and better understand your customers.

We begin any new client relationship with an initial discovery process. The first step to solving a problem is to fully understand why it’s a problem. Big data is no different. During our discovery meeting we dive deeper into three main areas; resources, technology, and processes.

Resources: Does the organization have the time and staffing capabilities to deal with big data? Do they have the expertise? Many businesses don’t.

Technology: Does the organization have the computing power or server storage dedicated to capturing and computing massive amounts of data? Again, this is a major roadblock for the average small or mid-sized business.

Processes: We identify benchmarks of the client’s business process and examine how prospects or customers move through it. It’s also important to look closely at different departments or divisions within an organization. How does the marketing department share data with the sales force? Are there data redundancies? Do different sectors know what type of data sets others are tracking?

If an organization isn’t considering how data sets fit together it’s nearly impossible to effectively leverage valuable information across other areas of the business. Large corporations spread across the country or the world can see major delays if data isn’t moving properly through different channels. Even small bottlenecks in the business process can cause major disruptions.

When we start working with a new client many of them try to turn over ALL of their data. This discovery process helps them understand that it’s not about passing all of the data over, but the data that is most relevant to their success.

Finding the relevant info involves data mining, and we’ll have more on that, in the next part of the series. Stay tuned…