Big data and advanced analytics are a relatively new class of business solutions that bring together a variety of tools to process humongous amounts of structured or unstructured data by employing statistics and probability to project what may take place in the future. This category of solutions has significantly transformed how business is done by enabling enterprises to make some very useful predictions, hence allowing them to take advantage of opportunities or to avoid huge losses to the business.
The following are some big data use cases for modern businesses:
Analyzing customer behavior for retail
Advanced, data-driven insights are vital for dealing with the challenges of personalization of marketing campaigns in order to increase revenue, improve customer conversion rate, foresee and avoid customer churn, and reduce customer acquisition costs. However, with customers having many interaction points with the business, like social media, e-commerce websites, in-store channels, mobile devices, and more, the companies have a more complex task of aggregating the data from various sources and then analyzing it. An enterprise can get a deeper understanding from the effective use of such data, like who are its high-value customers, what drives those customers to buy so much, when and how those customers can be reached, and so on. Such data can help to enhance customer loyalty and to significantly cut customer acquisition costs. Since a business may lack well skilled and experienced data engineers and scientists, it may consider engaging experts like those in Active Wizards.
Predicting equipment failure in manufacturing
Manufacturing establishments can use big data to predict equipment failure. Equipment engineers and service persons can detect early problems by analyzing both structured data, like the equipment year, model and make, and unstructured data—such as error indications, engine temperature readings, log entries, sensor data, and other things. These sets of data can enable manufacturers to maximize equipment uptime and parts as well as arrange for maintenance in a more cost-effective manner. In addition to predicting equipment failure, this data is vital to foretell the remaining useful life of the systems and components to be sure they deliver within the specifications. Failure of a machine to perform within the permissible limits is a failure, even if no part is broken, as it can cause issues. For example, if a machine in drug manufacturing allows more than the correct amount of an active ingredient, the result can be disastrous.
Human resource analytics
Organizations’ HR departments can have in place big data and advanced analytics solutions that take in resumes and data from networking/job search sites, like LinkedIn, to search for candidates. These solutions use techniques that pick key attributes from candidates.
Operational efficiency
Big data can have a significant impact on profitability by streamlining operations. By utilizing big data, a business can plan its operating hours to capture the highest traffic, to analyze and evaluate production processes, to anticipate and respond accordingly to future demands, and to proactively act on customer feedback. Also, big data can enable the planning of shifts to ensure there is enough staff during peak times, and even to give staff breaks or days off during the less busy times.
