What is SAP - and what is SAP Analytics?
- Advanced Analytics
- 6 min reading time
Marie Daipo
This wiki article is about SAP and the role the company plays in the world of business software. It focuses on the development from the first ERP solutions covering various business processes such as finance, logistics and human resources to modern technologies in the field of SAP Analytics. It explains how the company grew from its beginnings in the 1970s to become a global market leader and which systems are at the heart of the digital transformation today.
Innovative analysis platforms such as the SAP Analytics Cloud and the SAP Business Data Cloud, which support companies in consolidating and evaluating large volumes of data and converting them into strategic decisions, are highlighted in particular. The article shows how data management and business intelligence have developed in the SAP environment and the importance of these technologies for future-oriented companies.
Table of contents
1. introduction - what does SAP mean?
1.1 Origin and history of SAP
In April 1972, five former IBM employees in Weinheim decided to found a GbR Systemanalyse Programmentwicklung. Dietmar Hopp, Hasso Plattner, Claus Wellenreuther, Klaus Tschira and Hans-Werner Hector had the vision of changing or improving the business world with business software.¹ The abbreviation SAP emerged from the original name, which is now used as the company name. The company, based in Walldorf, Germany, is now a registered trademark with more than 400,000 customers. As the market leader for all listed companies (DAX, SMI etc.), SAP is an integral part of the application landscape.
1.2 What does SAP do as a company?
SAP offers more than 100 software solutions designed to cover various business functions and support business processes. These components are designed to help companies of all sizes and in all industries to increase economic efficiency, enable adaptability, promote sustainable growth and facilitate well-founded decisions. SAP has developed numerous pieces of software, including SAP ERP (SAP Enterprise Resource Planning) and SAP S/4HANA.
If you would like to know more about ERP solutions or finance, logistics and human resources , you can find out more here.
2. overview of SAP ERP modules
By managing data centrally, the SAP software provides a uniform view of company information. The ERP system covers all core business areas, which are divided into various SAP modules. The most important modules include logistics, production, materials management, sales, finance and human resources:
- Materials management (MM): Avoids bottlenecks through timely material procurement → Benefits: Efficient production planning
- Production Planning & Control (PP): Optimizes production processes and demand planning → Benefits: Punctual delivery of customer orders
- Logistics (SCM): Controls the flow of goods and services → Benefits: Cost reduction and more efficient supply chains
- Sales and Distribution (SD): Covers order management, shipping, invoicing → Benefits: Faster sales processes
- Finance (FI/CO): Ensures transparent accounting and controlling → Benefits: Sound financial decisions
- Human Resources Management (HCM): Automates employee processes → Benefits: Higher productivity and efficient personnel planning
Problem-solution perspective: SAP ERP solves typical business problems such as data islands, inefficient processes and a lack of transparency, thereby increasing productivity and customer satisfaction. With the introduction of SAP S/4HANA, the SAP modules were restructured into "business units" (LoB) that are more closely aligned with real business processes.7
SAP ERP can be used to control central business processes such as finance, logistics or human resources, while SAP S/4HANA is a modern further development that integrates additional functions such as embedded analytics to enable evaluations directly within the operational systems.
3 What is SAP Analytics?
3.1 Definition and objectives of SAP Analytics
SAP Analytics is a generic term for the analysis and reporting solutions within the SAP ecosystem. The applications are used to evaluate business data and make it usable for operational decisions. The aim is to convert raw data into usable information in order to support companies in developing and adapting their business strategies.
SAP Analytics solutions can be adapted to different business requirements. SAP Analytics offers analysis functions that are put together without manual programming, which means that companies can improve their business logic without the help of developers. Companies can easily extend the analytics functions or have the option of developing their own analytics applications.
3.2 Differentiation from operational SAP components
SAP Analytics is part of the mySAP Business Suite solutions, but can also be used as a stand-alone application. It offers analyses to support general and industry-specific business processes. It also enables the formulation of strategies and the provision of analysis results via company portals.
The functions include the integration of data from SAP NetWeaver Business Intelligence, the processing of real-time data feeds and master data management that can provide consistent information from multiple SAP installations as well as from heterogeneous system landscapes.
3.3 Data analysis vs. data processing
The terms data processing and data analysis refer to different activities in the field of data management.
Data processing involves the collection, conversion and organization of raw data in a structured format. The aim is to make the data usable for storage, retrieval and analysis. It relates to technical and mechanical aspects of data management and is intended to ensure the quality and consistency of the data. This includes tasks such as data cleansing, data integration, data enrichment and data transformation. 8
Data analysis, on the other hand, is concerned with the examination and interpretation of processed data. It is used to identify patterns, trends and correlations in order to enable data-based decisions. Methods include statistical analysis, machine learning, data mining, predictive modeling and business intelligence reports.9
4. tools & components of SAP Analytics
4.1 Cloud-based tools & components
SAP Analytics Cloud (SAC)
The SAP Analytics Cloud (SAC) is a cloud-based platform that supports companies with reporting, planning and forecasting. It combines various analysis functions in a single product. By using artificial intelligence and machine learning, forecasts can be improved and data-based decisions can be made more easily.
SAP Business Data Cloud
The SAP Business Data Cloud (BDC) is also a cloud solution. It brings together data from different sources - both from SAP systems and other applications - in one central location. This creates a common basis on which advanced analyses and AI-supported evaluations can be carried out in order to gain new insights. 11
4.2 On-premise tools & components
SAP BusinessObjects
SAP BusinessObjects Business Intelligence (SAP BO BI) is a suite for data reporting, visualization and sharing. As the local BI layer for SAP's Business Technology Platform (BTP), it transforms data into usable information that is available anytime, anywhere.12
SAP BW/4HANA
SAP BW/4HANA is an in-memory data management system that serves as a central data warehouse. It collects data from SAP and non-SAP systems, models it in simplified structures, integrates different sources and provides optimized analyses for the SAP HANA database.
5 Areas of application and advantages of SAP Analytics Cloud
Compared to other SAP analytics tools, the SAP Analytics Cloud (SAC) is currently the central application that most companies and employees in the SAP analytics environment come into contact with. The platform can be linked to other SAP solutions and enables the creation of visualizations via drag-and-drop, so that even users without in-depth IT knowledge can create reports and analyses.
5.1 Reporting & dashboards
- Real-time insights: Direct connection to SAP data enables up-to-date and precise evaluations.
- Integration of data sources: SAP and non-SAP data can be combined → Uniform view of all relevant information.
- Interactive reports: Users can filter data, zoom in or examine it in detail in order to recognize correlations more quickly.
- Consistent KPIs: Key performance indicators are presented in a standardized way throughout the system and are therefore reliably comparable.
- Modern visualizations: Diagrams, maps or storyboards ensure that results are presented in an understandable and clear way.
- Planning & forecasting: Planning and forecasting functions can be integrated directly into reports, combining analysis and control.
5.2 Self-service analytics
- Independent creation: Business users can develop their own reports and dashboards without IT support.
- Ad-hoc analyses & personalization: Individual queries and storage of personal views are possible at any time.
- Integrated data preparation: Data can be linked, calculated and transformed within the platform - without additional tools.
- Scenario analyses: "What-if" analyses make it possible to simulate the effects of various assumptions.
- AI-supported support: Automatic forecasts and intelligent analyses provide additional insights.
- Collaboration: Results can be shared directly and edited together, making collaboration easier.
5.3 Predictive analytics
- Automated forecasts: Forecasts are based on historical data and also take seasonal effects into account.
- Smart Predict: Machine learning-based predictions without programming → easy to use for business users.
- Smart Insights: Provides explanations of which factors influence changes in key figures.
- Compass: Supports the recognition of patterns and the testing of scenarios.
- Integration in planning: Forecasts are embedded in the planning environment so that realistic budgets and forecasts can be created.
- Natural language & augmented analytics: analyses can be queried by voice input or with extended intelligent functions.
System / Data source | Integration type | Benefit / Advantage |
Live Connection | Real-time access to operational ERP data without data copying | |
Live & Import Connection | Use of proven data models and queries | |
Live Connection | Central data platform for consistent analyses | |
Live & Import | Access to HR, purchasing and travel expense data | |
OData, BW extracts | Connection to classic SAP systems | |
Import Connection | Integration of cloud applications | |
Live & Import | Access to relational and cloud databases | |
Import Connection | Simple data integration of file sources | |
Live & Import | Flexible connection to web services and modern interfaces |
6 Conclusion: Why SAP Analytics is indispensable
SAP Analytics plays a central role in the SAP ecosystem, as the analysis functions are based on a standardized and controlled database. This increases efficiency and agility and enables the use of AI-based applications.
In the past, companies first had to prepare and merge data from different SAP systems before they could be used for analyses. With the SAP Business Data Cloud, data can now be directly integrated and harmonized. This saves companies time and resources that they can use for value-adding tasks, such as the use of AI solutions.
The SAP Business Data Cloud is currently the central element in the SAP Analytics environment. It enables individual reports to be analyzed and converted into AI-supported insights. By providing a uniform, semantically harmonized database, it supports faster and more informed decisions throughout the company. In the long term, the Business Data Cloud is expected to have a significant impact on business processes across the entire SAP ecosystem.
Advanced analytics is a key driver of digital transformation and supports future-oriented companies in successfully implementing data-based strategies.
List of sources
[1] History of SAP | About SAP SE
[2] SAP S/4HANA Cloud Public Edition | Procurement
[3] SAP S/4HANA Cloud Public Edition | Manufacturing
[4] SAP S/4HANA Cloud Public Edition | Supply Chain
[5] SAP S/4HANA Cloud Public Edition | Sales
[6] SAP S/4HANA Cloud Public Edition | Finance
[7] Moving from SAP ECC to SAP S/4HANA: Key SAP ERP Modules and Their Replacements
[8] What is data processing? | IBM
[9] Data science vs. data analysis: differences and correlations
[10] SAP Analytics Cloud®: Your entry into data analysis
[11] Introducing SAP Business Data Cloud
[12] SAP BusinessObjects | Business Intelligence (BI) Platform & Suite
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