Exam DP203 front-end services Azure Synapse Analytics Studio

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Revision as of 14:26, 18 November 2024 by NeilM (talk | contribs) (→‎2. Data)

First front-end_service is 1. Azure Synapse Analytics Studio.

To open this, go into the Azure Synapse Analytics Workspace resource, and click a button to open the Azure Synapse Analytics Studio web app.

Pipelines.

Functions:

  • Descriptive analytics
  • Diagnostic analytics
  • Predictive analytics
  • Prescriptive analytics

A Workspace typically has a default data lake, which is implemented as a linked service to an Azure Data Lake Storage Gen2 container.

Note there are two meanings of the word "Workspace". The first one is that of the overall Azure Synapse Analytics Resource. The other is the name of the "Workspace" tab.

There are the following sections on the left-hand side:

  1. Home
  2. Data
  3. Develop
  4. Integrate
  5. Monitor
  6. Manage

Looking at these in more detail:

1. Home

The "Ingest" button is a go-to to manually import data from a .csv file. It opens the Copy Data tool

2. Data

Here there are two tabs:

  1. Workspace
  2. Linked

And items under these have Categories such as "Azure Data Lake Storage Gen2", under which the specific data sources are to be found ("data explorer" can be used to see files in Gen2.

These in more detail:

Workspace

Contains databases defined in the Workspace (i.e. wholly within Azure Synapse Analytics Studio) "Data Explorer" items allow you to explore data. This uses KQL - Kusto Query Language to do this.

Linked

Data sources that are linked to the workspace, including Azure Data Lake storage.

Access by Azure Synapse Analytics Studio to files in Azure Data Lake Storage Gen2 is normally done in the "Linked" tab, under section "Azure Data Lake Storage Gen2" by adding a path to the files in Azure Data Lake Storage Gen2.

This involves providing credentials so that Azure Synapse Analytics Studio is able to connect to Azure Data Lake Storage Gen2.

3. Develop

Saved SQL query objects, Spark Notebooks, and "Data Explorer" KQL scripts. Click the + button to choose the new item from these to create here.

4. Integrate

This is where Pipelines are developed. See: Data Pipelines

5. Monitor

6. Manage

Manage the two types of SQL Pool:

  1. Serverless SQL Pool. Built-in pool. Reads from data lake files.
  2. Dedicated SQL Pool. sqlxxxxxxx. Reads relational data from data Warehouses.

Azure Synapse Analytics can also be used for Real time analytics. Stream Analytics?

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