In this blog, I will demonstrate SAP Data Intelligence, showing several aspects of SAP Data Intelligence 3.0 with a series of 7 videos, including the launchpad, connection management, metadata management, pipeline modeling, and ML scenario manager.
SAP Data Intelligence Launchpad
In our first video, we show you SAP Data Intelligence Launchpad. SAP Data Intelligence Launchpad is a browser-based application that provides a single point of access to a range of user-facing applications. The applications displayed in the Launchpad vary for different users and depend on the user logon credentials, which are dependent on user roles or personas, such as data engineer, data scientist, business analyst, IT user, data steward, and so on. The Launchpad enables you to organize, personalize, and launch the SAP Data Intelligence applications including grouping applications, ordering applications, removing applications, creating quick links, etc.
SAP Data Intelligence Connection Management
Before you can do anything with SAP Data Intelligence, SAP Data Intelligence administrators or other business users with necessary privileges use the SAP Data Intelligence Connection Management application to create and maintain connections. A connection represents an access point to a remote system or a remote data source. The connection management video shows connection management functionalities, including a list of connections available in your SAP Data Intelligence instance and the type of connections that SAP Data Intelligence supports. You can create a new connection, delete an existing connection, or check the status of the connection.
After your administrator(s) created connections and provided you access to the SAP Data Intelligence instance and to the connections, you can perform a series of operations and, based on your persona, the order will be different.
SAP Data Intelligence Metadata Explorer
As a data steward or a business analyst, you can use Metadata Explorer to perform metadata management functionalities available in SAP Data Intelligence. The use cases supported by Metadata Explorer include three use cases.
The first use case is data discovery and governance. It is not easy to find the dataset that you need for your uses. Even after you find a potential dataset, you may not trust the data itself for several reasons. In many cases, you will need to evaluate the data quality based on the source of the data, you may need feedback from other users, or the vocabulary to describe the attributes of the data may not conform your understanding. With a metadata catalog, along with a set of services including a business glossary, search, fact sheet, lineage, rating, and tagging, we support data discovery and governance in SAP Data Intelligence.
The second use case is data quality monitoring. The easy to use business rules and scorecards allow users to monitor data quality continuously.
The final use case is self-service data preparation, where business users and business analysts can leverage the data pipelining capability in an easy-to-use spreadsheet UI to enhance and enrich datasets.
In the third video of this series, we navigate all of the functionalities to perform the above three use cases in Metadata Explorer.
Data Preparation within SAP Data Intelligence Metadata Explorer
We demonstrate data discovery and data preparation in this video, where a easy-to-use search bar helps you find the dataset, filters search results based on additional knowledge, acquires data from a structured source, and enhances the dataset. Then we further enrich the data with another dataset from a Hadoop data lake and perform an inner join without doing any coding.
In our 5th video we demonstrate the modeling in SAP Data Intelligence using out of the box operators, out of the box pipelines, how to use graph snippets or when to use templates to jump start your pipeline development,