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Exploring The Evolution And Adoption of Customer Data Platforms and Reverse ETL

Data Engineering Podcast

A natural outgrowth of that capability is the more recent growth of reverse ETL systems that use those analytics to feed back into the operational systems used to engage with the customer. Connect your warehouse to Hightouch, paste a SQL query, and use their visual mapper to specify how data should appear in your SaaS systems.

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Open Source Reverse ETL For Everyone With Grouparoo

Data Engineering Podcast

By acting as a virtual hub for data assets ranging from tables and dashboards to SQL snippets & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Snowflake, Slack, Looker and more.

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Apache Spark vs MapReduce: A Detailed Comparison

Knowledge Hut

The Pig has SQL-like syntax and it is easier for SQL developers to get on board easily. It also has rich Spark SQL APIs for SQL-savvy developers and it covers most of the SQL functions and is adding more functions with each new release. Spark is fast and so can be used in Near Real Time data analysis.

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Reverse ETL to Fuel Future Actions with Data

Ascend.io

However, data warehouses are only accessible to technical users who know how to write SQL. And, even if you are an SQL expert, there is still a gap between the warehouse and frontline business tools companies use every day. In many ways, ETL and ELT are a one-way door: they aren’t designed to read or write data out of your warehouse.

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ETL Testing Process

Grouparoo

ETL testing can be challenging since most ETL systems process large volumes of heterogeneous data. However, establishing clear requirements from the start can make it easier for ETL testers to perform the required tests. Stages of the ETL Testing Process The ETL testing process can be broken down into 8 different stages.

Process 52
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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

Kafka is great for ETL and provides memory buffers that provide process reliability and resilience. SQL Today, more and more cloud-based systems add SQL-like interfaces that allow you to use SQL. ETL is central to getting your data where you need it.

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61 Data Observability Use Cases From Real Data Teams

Monte Carlo

Upstream Code Impacting Data Systems It’s not just SQL queries that can create data quality problems. They are also typically deploying dozens of dbt models each of which is transforming data and the underlying SQL codes in ways that can create quality issues if not closely monitored.

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