Big data has a massive potential to revolutionize businesses by offering business intelligence. However, big data is often incomplete, incorrect, unsegmented, or poorly categorized. This prevents companies from taking advantage of data from different sources to deliver good customer service and implement strategies. Amid the competitive clutter in the business world, having the right insight can propel your company to the top and give it a competitive advantage. Taking advantage of big data to improve decision-making is easier said than done. While big data analytics is a good thing, it sometimes becomes costly. This calls for approaches to eliminate costs associated with gathering, accessing, sorting and analyzing data. Finding the right ways to collect and process information enables streamlining production, sales and customer service. To ensure big data analytics does what is intended, the cost needs to be minimized as much as possible; here are ways to cut down the costs of your big data efforts.

Big data is one of the leading technologies that has become a buzzword for the past few years. However, most people in organizations do not entirely know what big data is and how their organizations are set to benefit from it. As such, we have gathered the most frequently asked questions on big data that might help them know what it is and provided answers to these questions.

Big data is no longer mere talk. It is accelerating rapidly, leading to massive innovation in organizations never witnessed before. This is particularly the case in the emerging tech world and the evolution of applications such as AI and machine learning (ML). Although one cannot deny that data is a new goldmine for organizations, keeping up with the pace of change is difficult for them, and some projects sometimes become obsolete even before they launch. As such, we now find ourselves in a catch-22 kind of situation where while data has become a necessity for businesses and decision-making processes for organizations, gathering, processing and making sense of it is a massive challenge that requires the right strategies in place. Despite the years that we have invested in big data, it is true when we say that big data still has its problems. Here are some of the problems that big data still face.