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“Unlock the Power of Cosmos DB: Capture Changed Data from your Analytical Store (Preview)”

Blog Post Outline:

Introduction
H2: What is Capture Changed Data From your Cosmos DB analytical store (Preview)?
H3: Overview
H3: Benefits
H3: Challenges

H2: Steps to Capture Changed Data from your Cosmos DB analytical store (Preview)
H3: Step 1: Set up a linked service
H3: Step 2: Create a dataset
H3: Step 3: Create a pipeline
H3: Step 4: Invoke the pipeline

H2: Popular Questions
H3: Q1: How do I set up a linked service?
H3: Q2: What is the purpose of creating a dataset?
H3: Q3: How do I create a pipeline?
H3: Q4: What is the purpose of invoking the pipeline?
H3: Q5: What are the benefits of Capture Changed Data?

Conclusion

Introduction
Capture Changed Data from your Cosmos DB Analytical Store (Preview) is a feature that allows developers to efficiently capture incremental changes within their Cosmos DB Analytical Store databases. It is currently in preview stage. This blog post will provide a step-by-step guide to setting up and using this feature. It will also answer some of the most popular questions related to this feature.

H2: What is Capture Changed Data From your Cosmos DB analytical store (Preview)?
Capture Changed Data from your Cosmos DB Analytical Store (Preview) is a feature that allows developers to efficiently capture incremental changes within their Cosmos DB Analytical Store databases. It captures any new or modified data from an Analytical Store collection and stores it in an Azure Data Lake Store (ADLS) for further analysis. It allows developers to be able to track changes within the Analytical Store databases, as well as to ensure data integrity.

H3: Overview
Capture Changed Data from your Cosmos DB Analytical Store (Preview) is a feature that allows developers to capture incremental changes in their Cosmos DB Analytical Store databases. It captures any new or modified data from an Analytical Store collection and stores it in an Azure Data Lake Store (ADLS) for further analysis. It works with both the current and next version of the Analytical Store.

H3: Benefits
The main benefit of Capture Changed Data from your Cosmos DB Analytical Store (Preview) is that it allows developers to efficiently capture incremental changes in their Analytical Store databases. This means that they can track changes within the Analytical Store databases, as well as ensuring data integrity. Additionally, it allows developers to save time and resources by not having to manually check for any changes in their Analytical Store databases.

H3: Challenges
The main challenge with Capture Changed Data from your Cosmos DB Analytical Store (Preview) is that it is currently in preview stage and therefore may be unstable and buggy. Additionally, it requires the current or next version of the Analytical Store, which may not be available to all developers.

H2: Steps to Capture Changed Data from your Cosmos DB Analytical store (Preview)
H3: Step 1: Set up a linked service
The first step to using Capture Changed Data from your Cosmos DB Analytical Store (Preview) is to set up a linked service. This involves creating an Azure Data Factory instance, connecting it to your Analytical Store, and setting up an Azure Data Lake Store.

H3: Step 2: Create a dataset
The next step is to create a dataset. This involves defining the source and destination of your data, as well as any additional settings that you may need.

H3: Step 3: Create a pipeline
The third step is to create a pipeline. This involves creating a pipeline that will capture any changes in your Analytical Store databases and store them in an Azure Data Lake Store.

H3: Step 4: Invoke the pipeline
The fourth and final step is to invoke the pipeline. This involves running the pipeline to capture any changes in your Analytical Store databases and store them in an Azure Data Lake Store.

H2: Popular Questions
H3: Q1: How do I set up a linked service?
Setting up a linked service involves creating an Azure Data Factory instance, connecting it to your Analytical Store, and setting up an Azure Data Lake Store.

H3: Q2: What is the purpose of creating a dataset?
The purpose of creating a dataset is to define the source and destination of your data, as well as any additional settings that you may need.

H3: Q3: How do I create a pipeline?
Creating a pipeline involves creating a pipeline that will capture any changes in your Analytical Store databases and store them in an Azure Data Lake Store.

H3: Q4: What is the purpose of invoking the pipeline?
The purpose of invoking the pipeline is to run the pipeline and capture any changes in your Analytical Store databases and store them in an Azure Data Lake Store.

H3: Q5: What are the benefits of Capture Changed Data?
The main benefit of Capture Changed Data from your Cosmos DB Analytical Store (Preview) is that it allows developers to efficiently capture incremental changes in their Analytical Store databases. This means that they can track changes within the Analytical Store databases, as well as ensuring data integrity. Additionally, it allows developers to save time and resources by not having to manually check for any changes in their Analytical Store databases.

Conclusion
Capture Changed Data from your Cosmos DB Analytical Store (Preview) is a powerful feature that allows developers to capture incremental changes in their Analytical Store databases. This blog post provided a step-by-step guide to setting up and using this feature, as well as answering some of the most popular questions related to it.

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