While many in the business world tout the revolutionary transformation brought about by Big Data, others remain skeptical that this analytical process will ever live up to its reputation. The promise of greater efficiency and business growth through the insights provided by Big Data—including market trends/fluctuations and consumer likes/dislikes as well as future predictions—have yielded positive results for some organizations, while other businesses have struggled to net a return on their investment.
Despite the remedying of early obstacles to its widespread success, Big Data has tallied a sizeable number of myths surrounding its core concepts and implementation steps.
“The thing about the best and longest lasting myths, legends and lore is that there is always a nugget of truth that keeps the mistruth going. It is commonly the case with complex technologies that are often overhyped and ultimately become slower than expected to be adopted. Big data is one of those technologies,” says Andrew Froehlich, President & Lead Network Architect, West Gate Networks.
These four myths continue to haunt Big Data.
- Big Data is for big businesses
“This is a huge myth and needs some busting left and right. Big Data is not an expensive entity that only the vast businesses can afford. The quality of data wins over its quantity, and therefore, small and medium enterprises can equally leverage the immense benefits of Big Data in their organizations,” insists James Warner.
Smaller companies will often benefit most from real-time data analytics that doesn’t require expensive data storage systems. Determining the precise type of data most useful to an organization, regardless of their size, is the key to netting the most benefit from data analytics.
- Collecting mammoth amounts of info WILL produce answers
Success from analyzing Big Data is not based on the volume of information collected, but rather from the level of insight gleaned from said data. Another key to effectively using the gathered data is to focus collection efforts around a defined goal, to have a specific business aim in mind when collecting and analyzing the data.
“Exploiting big data doesn’t have to mean working with massive amounts of information. While some organizations are struggling with petabytes of data, you can still derive insight from data sources that collect 100 terabytes of information—or even less,” notes Mark Samuels.
- Big Data will tell you what will happen next
“Big Data-driven prediction is about extrapolating what is most likely to happen in the future, based on what you know has happened in the past. If you are analyzing real-time data, it can take into account what is happening right now, as well. But any predictions it gives you will be based on a probability, and there is always a margin for error,” reminds Bernard Marr.
Big Data is not a foolproof crystal ball. However, the quantity of relevant data will impact the accuracy of data-driven forecasts: the more data, the more relevant the data, the more predictable the outcome.
- Big Data analytics are far too expensive
Discussions about Big Data among those still learning the ropes too often focus on the notion that the initial cost is too high.
“This likely came about because big data first became popular with the largest enterprise organizations. Story after story about big data being leveraged in companies such as Facebook, Microsoft and Wal-Mart led many to believe that this was a technology only attainable by the largest of organizations,” shares Andrew Froehlich.
Early on, this may have been the reality, but now cloud-based big data and analytics solutions accommodate companies for relatively low start-up costs and allow future as-needed additions.
Your best bet? Start small, discover how Big Data can benefit your company, and put the myths to rest with your data. Because RomAnalytics focuses on top talent for market insights and analytics, our deep pool of candidates can provide your company with individuals ready, willing, and able to accomplish that goal. Contact our team today!
