Everybody keeps extolling the virtues of Big Data analytics. This is fine. We love to hear stories of how Big Data analytics helps companies find the invisible needle in the haystack, double customer retention, triple cross-sell, and cut costs by 95%.
Business leaders are so enthusiastic about its potential to transform business that it’s being referred to in some circles as “the planet’s new natural resource.”
However, almost every article or white paper promotes a specific tool or solution, but misses out on the most important point – the key to success with big data is solving business problems. Let’s cover the basics first.
What Makes Big Data Different?
Big Data can mean a lot of things. Often, Big Data refers to a technology set or solution architecture. Sometimes the term is used to describe a business challenge. Other times, the term is used to refer to the data itself. And the definition keeps evolving.
Here are a few definitions that all apply:
- A collection of data assets that requires new forms of processing to enable enhanced decision making, to extract new insight or new discovery.
- Data sets whose characteristics include high volume, high velocity, and a variety of data structures.
- Data that cannot be processed using standard databases because it is too big, too fast moving or too complex for traditional data processing tools.
- An evolving concept that refers to the growth of data and how to curate, manage, and process the data within performance goals.
Where Do I Start to Make the Most out of My Big Data?
Big data is a problem and data challenge, not a technical problem. With this we mean that for most organizations the amount of data and processing power is not a challenge. Yes, Facebook, Google and some banks have real technical challenges with the amount of data generated and analysed, but most businesses don’t.
The real challenge is defining the problems you want to solve with data and ensuring that the data is available to help you solve it. The problem will drive the solution in terms of which tools and technical solutions are best for your organization.
How Do You Define the Problems to Be Solved with Big Data?
The starting point is generally a business challenge, product or idea. It can be optimizing pricing, predicting technical problems before they happen, personalizing customer communication for a product, keeping the business safe, managing risk, reducing cost of fuel, or virtually anything else. In an hour, a cross-functional team in any business can usually come up with hundreds of problems that can be solved with data.
The next step is prioritizing a couple of problems that can deliver a clear return of investment in the short to mid-term with relatively limited effort. Solving a couple of different types of problems to begin with ensures that the solution is flexible and scalable and doesn’t just support a single use case.
Which Is the Best Big Data Solution?
Ensure that the problems are clearly defined and tested with end-users or internal stakeholders before jumping into solutions. Once the problem is clear you can start focusing on the solutions, because usually there are many.
Notice that we haven’t even mentioned unstructured v.s structured data, data lakes, NoSQL, MPP databases, Hadoop, BI tools such as IBI, MicroStrategy, Microsoft BI or SAP HANA. The reason is that there is no generic optimal solution for big data problems or organizations. The business problems and needs should always drive the solution and selection of tools.
Which Big Data Solution Should I Choose?
Before implementing tools, writing a single line or code or data query, the solutions can be prototyped, tested and modeled. Once you’ve proven that it works, the specification and planning of the technical implementation can begin. This saves time and money and delivers better results.
Why DMI Big Data Insights?
We are a pioneer in helping organizations solve business problems, and even creating new products and services, with the help of data. Our focus is defining, understanding and solving the problems in whatever way makes the most sense for each organization, independently of technology. The methodology we use allows problems and solutions to be tested without investing in expensive technology.
And we’ve proven over and over again that it works. Our customer references and success stories speak for themselves when it comes to delivering customer success.
Let’s organize a workshop to discuss what problems data can solve for your business. Contact us to continue the conversation.
Magnus Jern (Chief Innovation Officer) & Thiag Loganathan (President Big Data Insights)