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Change Data Capture (CDC) is a common technique to track data changed in a database system. Then downstream systems, instead of fully resyncing, can operate on the incremental changes. … Read More
In this second post in the series “Practices for Data Warehousing with Ascend”, we’ll explore the concept of automating the management of a data warehouse through the projection of source data. … Read More
Welcome to the first in a series of posts regarding patterns and practices we’ve learned while working with customers using Ascend within the core of their data platform/stack to help them build and manage data warehouses. … Read More
This How-to video will provide you with an overview of how you can seamlessly ingest change data capture (CDC) data into the Ascend Platform for easy ETLT. … Read More
This How-to video will provide you with an overview of how you can seamlessly ingest change data capture (CDC) data into the Ascend Platform for easy ETLT. … Read More
This How-to video will provide you with an overview of how you can now quickly and easily ingest Kafka event data into the Ascend Unified Data Engineering Platform. … Read More
This How-to video will provide you with an overview of the new Flex Code Data Connectors, including how to get started with your own connectors. … Read More
This how-to will walk through how to set up an ODBC connection between Ascend and Power BI in cases when your dataset is too large to expose through the web connector. … Read More
This How-to will provide you with an overview of how to ingest data into Redshift by building a production pipeline that automatically keeps data up to date, retries failures, and notifies upon any irrecoverable issues. … Read More
This How-to will provide you with an overview of how to ingest data into Snowflake by building a production pipeline that automatically keeps data up to date, retries failures, and notifies upon any irrecoverable issues. … Read More
This tutorial will give you an overview of the “T” in ETL, namely, how to start transforming your data before you load it into the final destination. We will use SQL in this example, but Ascend also supports Python/PySpark and Scala/Java transformations as well. … Read More
Now that we’ve extracted some data from S3, cleaned it up using a SQL transform, we can start on the “L” of ETL and write our data back out to our data lake. Follow this guide to learn how. … Read More
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