Apache Hive and Apache HBase are incredible tools for Big Data. While there is some overlap in their functions, both Apache Hive and Apache HBase have unique qualities that make them better suited to specific tasks. Some key differences include: Ultimately, comparing Apache Hive to Apache HBase is like comparing apples to oranges or Google to Facebook. While the two entities are similar, they don't provide users with the same functionality.

Data warehouses have made it easier for customers to store massive amounts of data. That information is useless, however, unless it is actionable. Making data actionable means employees can use the data for decision-making and improving the user experience. In this article, we’ll discuss reverse ETL, pushing data to Zendesk from your warehouse, and the value of this process.

In today’s 24/7 digital world, real-time data is a necessity to stay relevant for today’s businesses. Companies who wish to remain competitive must be able to quickly respond to customer demand and adjust to market changes. Supplying business leaders with real-time information for informed decision-making can be a challenge with information spread among disparate systems.

NetSuite is an enterprise resource planning (ERP) business management platform part of the Oracle enterprise software ecosystem. Although it's primarily intended for small and medium-sized businesses, organizations of all sizes and industries have successfully used NetSuite to balance their checkbooks, manage inventory, bill and invoice customers, and more.

Intercom bills itself as a “conversational relationship platform,” helping businesses connect with their audiences primarily through live chat, as well as email and chatbots. The Intercom platform offers functionality including engagement and onboarding for new customers, support for existing customers, and marketing for potential customers on the fence.

The world of big data is getting bigger every day. As the volume of data increases exponentially, businesses of all sizes try to capture raw data, process it, and extract insights for competitive decision-making. The end-to-end operation of extracting value from data is called the ETL process. It stands for: A crucial component of the ETL process is the data storage aspect. The two main contentious architectures for storage solutions are databases and data warehouses. But how do they differ?

Organizations are losing out on data-driven decision-making opportunities when data stays in the data warehouse. While business intelligence solutions can surface insights from these data sets, it often reaches team members too late to be used for daily business operations. Reverse ETL empowers organizations to increase the value of their data warehouses through operationalization. Learn how this can transform the way companies use data and insights.