The growing popularity of big data use cases has bought many new technologies and frameworks each of them comes with scalability, high throughput, and low latency in mind. Some companies have very large data warehouses storing hundreds of petabytes of data, and the data is used for various applications such as machine learning, batch analytics, and more. The data is used by technical engineering teams to get insights into businesses, which helps improve the product or services and yields new opportunities to generate more revenue for companies.
The performance of data warehouses plays an important role, as fast results will always help in quicker decision making. Data warehouses should have the ability to run queries in parallel and give results in less time to help businesses increase their productivity and profitability. It is also important to monitor the cost of the warehouse, which will also have an impact on the profitability of the organization. Hadoop came to...
