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Data Warehouses

The Data Chief Live: Beyond the Buzz in Data Mesh, Lakehouse, Data Warehouse

Oct 7, 2021 By ThoughtSpot In ThoughtSpot
Join The Data Chief Live on October 7 to go beyond the buzz on all things data mesh, lakehouse, and data warehouse. Gain clarity on what is hype, what is real, and how others are delivering business value faster with modern data platforms and processes. You'll hear live from Darren Pedroza, VP Enterprise Data and Analytics, First Command Financial Services, Inc., Zhamak Dehghani, Director of Emerging Technologies at Thoughtworks & author of The Data Mesh, Chris D'Agostino, Global Field CTO Databricks & me.
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integrate

5 Tips for Pushing Data From Your Warehouse to Zendesk

Oct 4, 2021 By Abe Dearmer In Integrate
For decades, ETL (extract, transform, load) has been a mainstay of organizations’ data integration workflows, moving information from various sources to a centralized data warehouse. More recently, however, businesses have been shaking things up with reverse ETL, which flips the sources and targets by sending data from your warehouse to third-party systems like Zendesk.
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integrate

Apache Hive vs. Apache HBase

Sep 24, 2021 By Mark Smallcombe In Integrate
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.
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integrate

Pushing Data to Zendesk From Your Warehouse

Sep 17, 2021 By Abe Dearmer In Integrate
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.
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integrate

Which Tables in a Data Warehouse Use Change Data Capture

Sep 15, 2021 By Mark Smallcombe In Integrate
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.
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integrate

5 Tips for Pushing Data from Your Warehouse to NetSuite

Sep 14, 2021 By Abe Dearmer In Integrate
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.
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integrate

5 Tips for Pushing Data from Your Warehouse to Intercom

Sep 7, 2021 By Mark Smallcombe In Integrate
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.
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keboola

Data Warehouse vs Database: What is the difference and which one should you choose?

Sep 7, 2021 By Keboola In Keboola
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?
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