Big data is offering answers to everything from the best ways to treat patients in a hospital to ensuring every airline flight arrives on time. Some organizations have built their success on big data. Netflix, for example, has found wide viewership for its award-winning original series in part because its data shows exactly what its viewers want to watch. Amazon too has an uncanny ability to predict what its customers want to buy, even to the point of shipping products before they’re purchased.
The era of big data is now, and while making sense of it is one of the biggest challenges facing organizations, big data offers companies large and small a window into their business, customers, and future. Organizations that think they don’t have anything to learn from big data are letting the competition jump ahead, propelled by insights that offer a competitive advantage.
Pursuing big data initiatives can help your organization make better strategic decisions and answer the most important questions about your industry. But before jumping into big data, or even if you have already, realize that with big data collection comes potential challenges. As you pursue a big data initiative, try to avoid these three major obstacles:
1. Unknown capabilities. Often, organizations lack knowledge of their capabilities, whether it’s the volume, variety, and velocity of data available to them or the technology they possess to make sense of that data. If the lines of communication between IT and the C-suite or other stakeholders aren’t open, or there’s a lack of awareness around how to extract value from the information available, a big data initiative can become an overblown project for storage. In time, that data tends to become overgrown, and you’re left holding information you don’t use.
2. Vague ideas of what you’re looking for. One of the most common mistakes organizations make is a simple one: not asking the right questions. Big data won’t offer the right answer if you don’t ask the right question, regardless of how much data is available. Some of the questions you have about your business might be answered with traditional business intelligence, but big data presents a glut of raw information, structured, unstructured, or semistructured, and combing through terabytes of such data often proves problematic. Being able to extract the most value from your data might mean hiring a data scientist or someone else who knows how to ask the right questions and interpret the results.
3. Failing to match technology to your organization’s needs. Big data analytics is within the reach of companies of all sizes. New solutions appear every day to make big data more friendly to organizations, and each offers different capabilities and is best suited to different organizations. A small or medium-sized business might opt for the open-source Apache Cassandra to handle their data, while large enterprises with an ERP system might choose an SAP or Oracle system that has more capabilities but carries a larger cost. Even small mom-and-pop stores can take advantage of big data through a solution like Amazon Web Services, which offers a more cost effective option to get off the ground. Based on your needs, budget, and in-house capabilities, know the solutions available and the costs associated with them.
There are many potential roadblocks to effective use of big data, from communication to the ability to interpret the data collected to finding the right technology. But the process doesn’t depend on the size of your business. Any organization that can read the signals in their data will better understand their customers, and thus have an advantage in the marketplace.
SHI partners with HP, EMC, IBM, Oracle, Cloudera, Teradata, and many other vendors in the big data ecosystem. We can pair you with the solution best suited to help you capitalize on your data by gathering real-time information and utilizing predictive and cognitive capabilities so you can outperform your competition. Reach out to your SHI Account Executive or contact me at BigData@SHI.com to learn more about leveraging big data and business analytics in your organization.