Merge pull request #189357 from whhender/catalog-updates-7

Updating date, author, format, and Acrolinx

Author: LJSpiller

articles/data-catalog/data-catalog-common-scenarios.md

@@ -1,11 +1,11 @@
 ---
 title: Azure Data Catalog common scenarios
 description: An overview of common scenarios for Azure Data Catalog, including the registration and discovery of high-value data sources, enabling self-service business intelligence, and capturing existing knowledge about data sources and processes.
-author: JasonWHowell
-ms.author: jasonh
+author: ChandraKavya
+ms.author: kchandra
 ms.service: data-catalog
 ms.topic: conceptual
-ms.date: 08/01/2019
+ms.date: 02/22/2022
 ---
 # Azure Data Catalog common scenarios
 
@@ -14,6 +14,7 @@ ms.date: 08/01/2019
 This article presents common scenarios where Azure Data Catalog can help your organization get more value from its existing data sources.
 
 ## Scenario 1: Registration of central data sources
+
 Organizations often have many high-value data sources. These data sources include line-of-business, online transaction processing (OLTP) systems, data warehouses, and business intelligence/analytics databases. The number of systems, and the overlap between them, typically grows over time as business needs evolve and the business itself evolves through, for example, mergers and acquisitions.
 
 It can be difficult for organization members to know where to locate the data within these data sources. Questions like the following are all too common:
@@ -23,26 +24,28 @@ It can be difficult for organization members to know where to locate the data wi
 * Who should I ask, or what is the process I should use to get access to the data warehouse?
 * I don’t know if these numbers are right. Who can I ask for insight on how this data is supposed to be used before I share this dashboard with my team?
 
-To these and other questions, Azure Data Catalog can provide answers. The central, high-value, IT-managed data sources that are used across organizations are often the logical starting point for populating the catalog. Although any user can register a data source, having the catalog kick-started with the data sources that are most likely to provide value to the largest number of users helps drive adoption and use of the system. 
+To these and other questions, Azure Data Catalog can provide answers. The central, high-value, IT-managed data sources that are used across organizations are often the logical starting point for populating the catalog. Although any user can register a data source, having the catalog kick-started with the data sources that are most likely to provide value to the largest number of users helps drive adoption and use of the system.
 
-If you are getting started with Azure Data Catalog, identifying and registering key data sources that are used by many different teams of data consumers can be your first step to success.
+If you're getting started with Azure Data Catalog, identifying and registering key data sources that are used by many different teams of data consumers can be your first step to success.
 
-This scenario also presents an opportunity to annotate the high-value data sources to make them easier to understand and access. One key aspect of this effort is to include information on how users can request access to the data source. With Azure Data Catalog, you can provide the email address of the user or team that's responsible for controlling data-source access, links to existing tools or documentation, or free text that describes the access-request process. This information helps members who discover registered data sources but who do not yet have permissions to access the data to easily request access by using the processes that are defined and controlled by the data-source owners.
+This scenario also presents an opportunity to annotate the high-value data sources to make them easier to understand and access. One key aspect of this effort is to include information on how users can request access to the data source. With Azure Data Catalog, you can provide the email address of the user or team that's responsible for controlling data-source access, links to existing tools or documentation, or free text that describes the access-request process. This information helps members who discover registered data sources but who don't yet have permissions to access the data to easily request access by using the processes that are defined and controlled by the data-source owners.
 
 ## Scenario 2: Self-service business intelligence
-Although traditional corporate business-intelligence solutions continue to be an invaluable part of many organizations’ data landscapes, the changing pace of business has made self-service BI more and more important. By using self-service BI, information workers and analysts can create their own reports, workbooks, and dashboards without relying on a central IT team or being restricted by that IT team’s schedule and availability.
+
+Although traditional corporate business-intelligence solutions continue to be an invaluable part of many organizations’ data landscapes, the changing pace of business has made self-service BI more important. By using self-service BI, information workers and analysts can create their own reports, workbooks, and dashboards without relying on a central IT team or being restricted by that IT team’s schedule and availability.
 
 In self-service BI scenarios, users commonly combine data from multiple sources, many of which might not have previously been used for BI and analysis. Although some of these data sources might already be known, it can be challenging to discover what to do to locate and evaluate potential data sources for a given task.
 
 Traditionally, this discovery process is a manual one: analysts use their peer network connections to identify others who work with the data being sought. After a data source is found and used, the process repeats itself again for each subsequent self-service BI effort, with multiple users performing a redundant manual process of discovery.
 
-With Azure Data Catalog, your organization can break this cycle of effort. After discovering a data source through traditional means, an analyst can register it to make it more easily discoverable by other users in the future. Although the analyst can add more value by annotating the registered data assets, this annotation does not need to take place at the same time as registration. Users can contribute over time, as their schedules permit, gradually adding value to the data sources registered in the catalog.
+With Azure Data Catalog, your organization can break this cycle of effort. After discovering a data source through traditional means, an analyst can register it to make it more easily discoverable by other users in the future. Although the analyst can add more value by annotating the registered data assets, this annotation doesn't need to take place at the same time as registration. Users can contribute over time, as their schedules permit, gradually adding value to the data sources registered in the catalog.
 
-This organic growth of the catalog content is a natural complement to the up-front registration of central data sources. Pre-populating the catalog with data that many users will need can be a motivator for initial use and discovery. Enabling users to register and annotate additional sources can be a way to keep them and other organization members engaged.
+This organic growth of the catalog content is a natural complement to the up-front registration of central data sources. Pre-populating the catalog with data that many users will need can be a motivator for initial use and discovery. Enabling users to register and annotate more sources can be a way to keep them and other organization members engaged.
 
 It’s worth noting that although this scenario focuses specifically on self-service BI, the same patterns and challenges apply to large-scale corporate BI projects as well. By using Data Catalog, your organization can improve any effort that involves a manual process of data-source discovery.
 
 ## Scenario 3: Capturing tribal knowledge
+
 How do you know what data you need to do your job, and where to find that data?
 
 If you’ve been in your job for a while, you probably just know. You’ve gone through a gradual learning process, and over time have learned about the data sources that are key to your day-to-day work.

articles/data-catalog/data-catalog-how-to-connect.md

@@ -1,33 +1,37 @@
 ---
 title: How to connect to data sources in Azure Data Catalog
 description: How-to article highlighting how to connect to data sources discovered with Azure Data Catalog.
-author: JasonWHowell
-ms.author: jasonh
+author: ChandraKavya
+ms.author: kchandra
 ms.service: data-catalog
 ms.topic: how-to
-ms.date: 08/01/2019
+ms.date: 02/22/2022
 ---
 # How to connect to data sources
 
 [!INCLUDE [Azure Purview redirect](../../includes/data-catalog-use-purview.md)]
 
 ## Introduction
+
 **Microsoft Azure Data Catalog** is a fully managed cloud service that serves as a system of registration and system of discovery for enterprise data sources. In other words, **Azure Data Catalog** is all about helping people discover, understand, and use data sources, and helping organizations to get more value from their existing data. A key aspect of this scenario is using the data – once a user discovers a data source and understands its purpose, the next step is to connect to the data source to put its data to use.
 
 ## Data source locations
+
 During data source registration, **Azure Data Catalog** receives metadata about the data source. This metadata includes the details of the data source’s location. The details of the location will vary from data source to data source, but it will always contain the information needed to connect. For example, the location for a SQL Server table includes the server name, database name, schema name, and table name, while the location for a SQL Server Reporting Services report includes the server name and the path to the report. Other data source types will have locations that reflect the structure and capabilities of the source system.
 
 ## Integrated client tools
+
 The simplest way to connect to a data source is to use the “Open in…” menu in the **Azure Data Catalog** portal. This menu displays a list of options for connecting to the selected data asset.
-When using the default tile view, this menu is available on the each tile.
+In the default tile view, this menu is available on each tile.
 
- ![Opening a SQL Server table in Excel from the data asset tile](./media/data-catalog-how-to-connect/data-catalog-how-to-connect1.png)
+ :::image type="content" source="./media/data-catalog-how-to-connect/data-catalog-how-to-connect1.png" alt-text="Opening a SQL Server table in Excel from the data asset tile by selecting the Open In tab.":::
 
-When using the list view, the menu is available in the search bar at the top of the portal window.
+In the list view, the menu is available in the search bar at the top of the portal window.
 
- ![Opening a SQL Server Reporting Services report in Report Manager](./media/data-catalog-how-to-connect/data-catalog-how-to-connect2.png)
+:::image type="content" source="./media/data-catalog-how-to-connect/data-catalog-how-to-connect2.png" alt-text="Opening a SQL Server table in Excel from the data asset tile in the list view by selecting the Open In tab.":::
 
 ## Supported Client Applications
+
 When using the “Open in…” menu for data sources in the Azure Data Catalog portal, the correct client application must be installed on the client computer.
 
 | Open in application | File extension / protocol | Supported application versions |
@@ -40,21 +44,25 @@ When using the “Open in…” menu for data sources in the Azure Data Catalog
 | Report Manager |http:// |See [browser requirements for SQL Server Reporting Services](/sql/reporting-services/browser-support-for-reporting-services-and-power-view) |
 
 ## Your data, your tools
-The options available in the menu will depend on the type of data asset currently selected. Of course, not all possible tools will be included in the “Open in…” menu, but it is still easy to connect to the data source using any client tool. When a data asset is selected in the **Azure Data Catalog** portal, the complete location is displayed in the properties pane.
 
- ![Connection information for a SQL Server table](./media/data-catalog-how-to-connect/data-catalog-how-to-connect3.png)
+The options available in the menu will depend on the type of data asset currently selected. Not all possible tools will be included in the “Open in…” menu, but it's still easy to connect to the data source using any client tool. When a data asset is selected in the **Azure Data Catalog** portal, the complete location is displayed in the properties pane.
+
+:::image type="content" source="./media/data-catalog-how-to-connect/data-catalog-how-to-connect3.png" alt-text="Example data asset properties pane, showing the Connection Info section that contains location information.":::
 
 The connection information details will differ from data source type to data source type, but the information included in the portal will give you everything you need to connect to the data source in any client tool. Users can copy the connection details for the data sources that they have discovered using **Azure Data Catalog**, enabling them to work with the data in their tool of choice.
 
 ## Connecting and data source permissions
-Although **Azure Data Catalog** makes data sources discoverable, access to the data itself remains under the control of the data source owner or administrator. Discovering a data source in **Azure Data Catalog** does not give a user any permissions to access the data source itself.
 
-To make it easier for users who discover a data source but do not have permission to access its data, users can provide information in the Request Access property when annotating a data source. Information provided here – including links to the process or point of contact for gaining data source access – is presented alongside the data source location information in the portal.
+Although **Azure Data Catalog** makes data sources discoverable, access to the data remains under the control of the data source owner or administrator. Discovering a data source in **Azure Data Catalog** doesn't give a user any permissions to access the data source itself.
+
+To make it easier for users who discover a data source but don't have permission to access its data, users can provide information in the Request Access property when annotating a data source. Information provided here – including links to the process or point of contact for gaining data source access – is presented alongside the data source location information in the portal.
 
- ![Connection information with request access instructions provided](./media/data-catalog-how-to-connect/data-catalog-how-to-connect4.png)
+:::image type="content" source="./media/data-catalog-how-to-connect/data-catalog-how-to-connect4.png" alt-text="Example data asset properties pane, showing the Connection Info section with the Request Access textbox highlighted.":::
 
 ## Summary
+
 Registering a data source with **Azure Data Catalog** makes that data discoverable by copying structural and descriptive metadata from the data source into the Catalog service. Once a data source has been registered, and discovered, users can connect to the data source from the **Azure Data Catalog** portal “Open in…”” menu or using their data tools of choice.
 
 ## See also
-* [Get Started with Azure Data Catalog](data-catalog-get-started.md) tutorial for step-by-step details about how to connect to data sources.
+
+* [Get Started with Azure Data Catalog](data-catalog-get-started.md) tutorial for step-by-step details about how to connect to data sources.