Since there's no limit to how you can use big data, almost every industry can leverage it to get insights into how it can perform better, generate more revenue, or beat the competition. Here are some industries where big data is of absolute importance.
Banking and Securities The banking industry uses big data for various purposes, including fraud detection, customer segmentation, and risk management. Banks also use big data to develop new products and services, such as customer-focused financial products. In fact, the big data analytics market in banking is expected to be as massive as $62.10 billion by 2025.
Healthcare The healthcare industry uses big data for population health management, disease diagnosis and treatment, and clinical decision support. Pharmaceutical companies also use big data to develop new drugs and therapies. For instance, companies might collect data about weather patterns and how they correlate with pollen counts to help with asthma forecasting and medication recommendations.
Telecommunications The telecommunications industry uses big data for network management, service assurance, and customer experience optimization. Big data is also valuable for targeted marketing and improving customer loyalty. For instance, companies can use big data to develop new products and services, such as personalized mobile plans. They do this by collecting data about customer preferences and then creating a plan accordingly.
Education Big data is also being used in the education industry to improve teaching and learning. For example, it is being used to develop personalized learning plans for students, identify at-risk students, and evaluate teacher performance.
Government The government collects a large amount of data on its citizens. This data is used for various purposes, such as taxation, census taking, and law enforcement.
Retail The retail industry uses big data to understand customer behavior and preferences. It helps retailers develop targeted marketing campaigns and improve their merchandizing strategies.
For instance, retailers might use data to identify which products are most likely to be purchased together. They can then place those products near each other in the store to make it easier for customers to find them.