In our previous two articles, we introduced:

• SAP S4HANA Embedded Real-Time Analytics - 1/4 Semantic Model Enhancing and creating calculated measures based on CDS Views in the S4 system.
• SAP S4HANA Embedded Real-Time Analytics - 2/4 Story Dashboard Creating story dashboards for real-time analysis of S4 system data based on CDS semantic models.

This article will explore how to manage indicators in the S4 system using CDS View and other models to build a comprehensive business indicator system.

Xpert Analytics Cloud, leveraging semantic models, offers powerful indicator management functions, designed to help users efficiently manage and monitor indicators within data models. By establishing a unified semantic modeling of enterprise data based on a core OLAP engine, Xpert Analytics Cloud eliminates the need for cumbersome data conversion and ETL. Through unified indicator definition functions, it enables unified management and certification of enterprise operational data. Ultimately, indicators are used for analyzing and evaluating company business and financial data through the indicator applications and story dashboards provided by Xpert Analytics Cloud.

Key Performance Indicator System (Indicator System) is a set of indicators used to measure and monitor business performance. These indicators help enterprises evaluate the achievement of their strategic goals and the efficiency of their business processes, thereby guiding management decisions.

In the first article, we introduced how to enhance CDS models using the semantic modeling capabilities of Xpert Analytics Cloud.. This article will explore how to use these enhanced CDS models to create visual story dashboards for better data analysis and business insights.

Story dashboards are a crucial component of Xpert Analytics Cloud's embedded analytics. They help users gain a comprehensive understanding of their business from multiple dimensions and levels through rich visualization features and interactive operations. This article will introduce the key features of creating story dashboards, including calculation measures, filter bar widgets, input controls, key metrics widgets, chart widgets, and grid table widgets. Combining these features can create a story dashboard as shown below:

This series of SAP S/4HANA embedded analytics feature introductions will be explained in three parts:

1. Semantic Models: Explore how to enhance CDS models using Xpert Analytics Cloud's semantic modeling capabilities, including defining calendar semantics and creating calculation measures using MDX statements, laying the foundation for subsequent story dashboards and KPI management.
2. Story Dashboard: Introduce how to create visual dashboards using enhanced CDS models to create rich and diverse stories and calculation measures.
3. KPI Management: Discuss how to define a series of KPIs for CDS models to form a systematic KPI management function, making it easy for enterprise managers to subscribe to and analyze KPIs and monitor business data in real time.

Embedded Analytics Introduction​

Xpert Analytics Cloud is a powerful data analytics tool that can directly connect to the SAP S/4HANA system and utilize Transient Analytical Queries generated from CDS (Core Data Services) views for embedded real-time data analysis. By leveraging the in-memory computing capabilities of the SAP HANA database, it provides real-time data analysis and reporting functions, allowing users to gain insights directly during business operations.

This series introduces SAP S/4HANA embedded analytics functionality in three parts:

1. Semantic Model: Explore how to enhance CDS models using the semantic model functionality of Xpert Analytics Cloud, including defining calendar semantics and creating calculated measures using MDX statements, laying the groundwork for subsequent stories and metrics management.
2. Story Dashboard: Learn how to create visual dashboards using enhanced CDS models to create a variety of stories and calculated measures.
3. Metrics Management: Discuss how to define a series of metrics based on CDS models to form a systematic metrics management function, allowing managers within the enterprise to subscribe to and analyze metrics and monitor business data in real time.

This article will introduce how to enhance CDS models using the semantic model functionality of Xpert Analytics Cloud, including calendar semantic definitions, calculated measures, and more.

We are excited to announce that the latest version of the Xpert Analysis Platform, version 2.4, is now available! As a cloud-based agile AI data analysis platform, it integrates multidimensional modeling, indicators management, and BI visualization to provide users with a one-stop data analysis solution. This update introduces the revolutionary "Copilot Multi-Agent Command" feature, further enhancing the platform's intelligence and user experience.

AI Digital Business Experts​

In Xpert Analysis Platform 2.4, we have introduced a revolutionary feature—the AI Digital Business Experts Platform. This feature aims to digitize professional knowledge and experience from various industries, allowing users to quickly access and apply these valuable resources to build their own enterprise data analysis systems. Whether you are a startup or a large enterprise, this feature enables you to quickly build a data analysis framework tailored to your business needs, improving decision-making efficiency and accuracy.

The platform not only provides users with ready-to-use digital business expert resources but also supports industry experts in digitizing and sharing their expertise with users in need. This sharing and collaboration mechanism promotes the dissemination and application of knowledge, contributing to the progress of various industries.

You can browse more information about AI Digital Business Experts on the AI Digital Business Experts page.

Xpert Analysis Cloud, an agile data analysis platform based on cloud computing, integrates multidimensional modeling, metric management, and BI presentation, aiming to provide users with an efficient and convenient data analysis experience. We are pleased to announce that the latest version 2.3 of Xpert Analysis Cloud has been officially released. This update not only optimizes platform performance but also brings several exciting new features, particularly a comprehensive upgrade to Copilot Command and Roles.

Major Breakthroughs in Copilot​

Copilot Command is an innovative way for users to execute AI functions. By entering commands along with corresponding prompts, the Copilot Agent will invoke large language models (LLMs) and run relevant functions to complete various data analysis tasks. The new version 2.3 of Xpert Analysis Cloud has made significant improvements in this feature:

We have released a new version 2.2.0 with the following major updates:

1. ER Diagram for Cube Designer​

We have added the ER diagram feature to the cube designer. You can now view the data relationship model of cubes through the ER diagram, including fact tables, dimensions, measures, and relationships. This allows you to intuitively understand the data structure of cubes, facilitating data modeling and analysis.

We have released version 2.1.0, with the following major updates:

1. Upgraded the state management framework, using @ngneat/elf, a reactive immutable state management solution.
   1. Upgraded the state management framework of the semantic model module, making semantic model operations more stable, and supporting State History and Undo/Redo functions. Refer to Shortcuts - Modeling Workspace
   2. Upgraded the state management framework of the story module, supporting State History and Undo/Redo functions. Refer to Shortcuts - Story Preferences
2. Changed olap data request method from Http requests to Websocket requests, improving the efficiency of data concurrent queries. Refer to WebSocket Request - Server Agent
3. The dimension designer data preview interface supports tree structure display. Refer to Tree Preview - Dimension Designer
4. Story designer interface updates:
   1. Support for fixing Toolbar to the sidebar: Refer to Toolbar - Story Workspace
   2. Optimized Zoom in / Zoom out mode, allowing individual page zoom and pan. Refer to Shortcuts - Story Preferences
   3. When opening a story in full-screen mode, it only goes full-screen within the webpage, no longer full-screening the browser.
5. The indicator registration page supports real-time data trend preview of indicators. Refer to Preview - Indicator Registration
6. Dimension/Measure selector component upgrade:
   1. Support for loading entity type status and error message display.
   2. Support for customizing member tag fields as hierarchical attributes or member intrinsic attributes. Refer to Member Label - Dimension Selector
7. In the indicator application, the drill-down chart displays the name of the current level as the title.

We are happy to announce Xpert Analytics Cloud 2.0.

We believe Xpert Analytics Cloud will help you analysis your big data with minimal effort, letting you focus on what really matters: indicators.

This is a new major version of Xpert Analytics Cloud, coming with new exciting features and new experiences.

Hello everyone!

We are excited to announce that the SaaS data analytics platform, Xpert Analytics Cloud, from the Xpert Analytics Cloud team, is now open source! This is a significant milestone, and we take pride in our ability to collaborate with the global developer community to drive innovation in the field of data analytics.

In this article, we will introduce some basic information about Xpert Analytics Cloud and how you can join our community to contribute to the development of the data analytics field.

In today's data-driven business environment, data analysis has become a key part of business decision-making. The Xpert Analytics Cloud provides you with an intelligent data query experience, through its powerful AI copilot function based on ChatGPT, you can more efficiently query, optimize and interpret data. This article will introduce in detail how to turn on and configure the AI copilot in the Xpert Analytics Cloud, and how to use the AI copilot in the Query Lab to improve the efficiency of data query.

Query Lab provides the function of flexibly operating the data source entity (physical table view or multi-dimensional data set) by using SQL query statement, which helps users in their daily data operation and maintenance work. The query lab is built in the semantic model workspace and operates and queries data through the data sources connected by the semantic model. If the user's data source is public network accessible, you can create a data source in the Xpert analytics cloud to connect query. If the user's data source is deployed in the private network, you can use the desktop agent to connect and query.

Next, this article will introduce how to turn on and configure AI copilot and use it to assist in querying the data sql in the laboratory, optimizing and explaining.