Big Data Analytics Use Cases in Businesses


Big Data Analytics Use Cases in Businesses


June 7, 2020
Name: 阮氏蘭香
Student ID : D0458704
Reference: https://www.tpptechnology.com/big-data-analytics-use-cases-in-businesses



Big data analytics provides a competitive edge for business organizations across various industries. It enables businesses to transform and improves operations by minimizing risks, reduce overheads and overall improve performance.

Big Data Analytics Use Cases in Businesses

Big Data Analytics can be applied across various business industries such as Financial Services, E-commerce and Retail, Healthcare, Market Research, and others. Big Data Analytics allows business to make use of real-time data and make better informed business decision. Below are some of the business areas that Big Data Analytics can help transform and improve upon:
Sales and Marketing: customer segmentation, customer relationship management, and offering more personalized customer care program and marketing campaigns; launching of new products and services;
  • Purchasing: Inventory management and inventory levels forecast;
  • Administration: optimizing internal resource and reducing costs;
  •  Financial services: fraud detection; mitigating risks;
  • Machinery operation: identifying and removing performance bottlenecks proactively;
  •  Others: predicting equipment failures;
  • Maintenance and support: Identifying the causes of failures and problems in real time.

Top 5 Big Data analytics use cases in businesses:

  • Fraud detection

One popular use case of big data analytics is Banks and financial institutions leverage this technology to monitor millions of credit cards transactions, to protect credit cards holder from fraudulent transactions on a daily basis.

  • Credit assessment

Along with fraud detection, banks together with financial institutions and insurance companies can also leverage the massive amount of data by applying data science models to assess the credit worthiness of borrowers.

  • E-commerce

In e-commerce, by analyzing customers’ past purchase history data and shopping behavior, companies can discover various hidden patterns and offered a more personalized marketing program as well as recommending the products and services items that customers are more likely to purchase, thus boosting sales and effectiveness.

  • Retail

With big data analytics, inventory management can move beyond the traditional methods of analyzing historical data on sales and stocks out. By applying data science and analytics with algorithms exploring relationship between different data elements, retailers can produce insights into customers behavior, product demand level, in-store and online sales performance, and more.

  • Transportation and logistics

Data Science and Big Data analytics can help transportation providers and logistics companies to optimize routing and freight movement by recommending the optimal route and time for delivery, reducing time taken, saving on petrol, and subsequently increasing productivity.
Moreover, data science and Big Data analytics can also help businesses to proactively enhance vehicles performance and maintenance through real-time view of fleet operating conditions and metrics. This helps eliminate bottlenecks and improve efficiency.

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