With the rapid rate in which data is being produced and aggregated across the enterprise, will our analytical capabilities scale fast enough to provide valuable insights in time?

Big data refers to a field that treats ways to analyze, extricate information from, or manipulate data sets that are extremely large and complex to be dealt with by traditional data-processing application software. A variety of digital tools—from the IoT to AI—are available to enable you to collect huge amounts of data and better understand how your users are responding to the products and services.

Big data has taken center stage in recent years, with companies in a huge range of industries beginning to understand the opportunities it can bring. Companies use big data in their systems to improve operations, provide better customer service, create personalized marketing campaigns and take other actions that, ultimately, can increase revenue and profits.

Big data provides valuable insights into customers that companies can use to refine their marketing, advertising and promotions in order to increase customer engagement and conversion rates. Both historical and real-time data can be analyzed to assess the evolving preferences of consumers or corporate buyers, enabling businesses to become more responsive to customer wants and needs.

Whereas, Big data analytics will increasingly focus on data freshness with the ultimate goal of real-time analysis, enabling better-informed decisions and increased competitiveness.

Big data has the power to reduce business costs. Specifically, companies are now using this information to find trends and accurately predict future events within their respective industries. Knowing when something might happen improves forecasts and planning.

However, the industry feels that there are equal levels of challenges associated with big data. An overwhelming majority of organizations believe they need to improve the qua.