SAP Learning Journey

Introducing Data Modeling in the Data Builder

Objectives
After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Describe the purpose of the Data Builder and how to work with it

The Data Builder

Initial Steps of Modeling in SAP Datasphere

SAP Datasphere offers multiple modeling capabilities that address different user groups – from business analysts with deep business understanding to tech-savvy developers and power users. In a typical end-to-end scenario, two closely related components of SAP Datasphere apply:

  • The SAP Datasphere Data Layer contains the basic modeling of the underlying data sources and tables. The related set of tools is available in the SAP Datasphere Data Builder. Here, developers and modelers use tables, views, and intelligent lookups to combine, clean, and prepare data. You can expose views directly to SAP Analytics Cloud and other analytics clients.
  • The SAP Datasphere Business Layer enables users to create their own business models on top based on business terms. The SAP Datasphere Business Builder provides the related set of tools. The Business Builder can consume Data Builder objects for further modeling and consumption. As a more semantic approach, business users create their models using the Business Builder editors. They combine, refine, and enrich the SAP Datasphere Data Builder artifacts with further semantic information before exposing lightweight, tightly-focused objects. SAP Analytics Cloud and other analytic clients consume these objects.

Data Builder Artifact Types

SAP Datasphere provides an editor to model Data Builder artifacts in an intuitive graphical interface. You can drag and drop sources from the Source Browser and join them as appropriate. You can add other operators to remove or create columns and filter or aggregate data. You can also specify measures and other aspects of your output structure in the output node.

You can preview the data contained in your tables and views. When working in the graphical view editor, you can also preview the data output by each of the nodes in the diagram.

SAP Datasphere provides various methods for importing tables or database views into your space:

  • Data Builder start page: Use the import wizard to import remote tables from any connection.
  • E/R Model: Import tables into the space and add them to the E/R model diagram.
  • Graphical or SQL view: Import tables into the space and use them directly as sources in the view.

Enable the "Expose for Consumption" switch (reporting layer) to make a view available for consumption in SAP Analytics Cloud, other analytic clients, and in ETL and other tools. You can only access views that have the Expose for Consumption switch enabled outside the space. SAP Analytics Cloud can access dimensions and other entities to which your Analytical Dataset points through associations, even if they have not been exposed. Other analytics clients can consume views of any type that have the Expose for Consumption switch enabled.

Data Visualization from SAP Datasphere in SAP Analytics Cloud

In SAP Datasphere, together with SAP Analytics Cloud, you can combine your data sources and extract insights from them based on stories. A story is where your data comes to live with powerful data visualizations. Charts, graphs, tables, and other visual elements are arranged to tell the story of your business or organization. Stories are the analyzed results of combining different data sources and models. Here, you begin visualizing the valuable insights you got from your data and prepare those insights for sharing with your stakeholders.

SAP Analytics Cloud offers One integrated experience for planning, BI and predictive in one service, with live data connectivity for end-to-end analytics for your Intelligent Enterprise.

SAP HANA Cloud, SAP Analytics Cloud and SAP Datasphere are an essential part of the SAP strategy. The combination of both is a powerful tool designed for complex analytics scenarios based on hybrid system architectures.

There are several ways to visualize data from SAP Datasphere in SAP Analytics Cloud. If you already have an SAP Analytics Cloud system and want to use SAP Datasphere as a data source using a live connection.

For example, you are the CFO of a multinational chain of furniture stores. A particular product sold poorly last year. You need to learn if your recent store design changes impacted the sales of the product. You can get insights by analyzing your data in the SAP Datasphere and modeling this data to show you the connections you are looking for. Then, you can visualize all of it with the SAP Analytics Cloud and a SAC Story.

A Story involves the ability to analyze the data generated by the connections you made during your modeling phase. You then visualize it and tell a story based on the data. With SAP Datasphere, you can ensure you have the fresh data you need. You can also ensure your data is ready to be interpreted without spending valuable time organizing it.

In SAP Datasphere, building a story is usually the last step in data analysis. Here, you visually discover and communicate important data insights. Creating a story is as easy as choosing the charts and selecting the appropriate dimensions and measures. However, you can deploy different strategies and best practices to build engaging stories that memorably communicate exactly what you want.

Define Your Goals

The best way to approach story building is to outline exactly what are looking for from the data. This provides a clear jumping-off point from which you can find other insights. Your primary objective could be to learn what customers are buying the most through looking for any possible buying trends. It could also be to discover which salesperson has the highest sales. It could be both. To do these, you focus on answering each question with charts, then, after you answer the big questions, unfold additional hidden insights.

Use Design Principles

When creating your story, design principles are important. Examples of design principles include using white space (so that stories are easy to read) or using complimentary colors (so that you highlight important charts in your story).

It is important to keep charts from becoming busy by minimizing color, eliminating confusing design, removing redundant information, and putting data in the correct order. The goal is to draw people into your story and keep them engaged by presenting information that is easy to interpret. You can present complex information. However, you do it in a simplified way.

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