Jul 7, 2021
•1 minute read
SAP Analytics
SAP Analytics focuses on how organizations use enterprise data to generate insight, support better decisions, and automate parts of day-to-day decision-making across SAP environments. The topic spans business intelligence, machine learning, artificial intelligence, SAP HANA, the Predictive Analytics Library, SAP Data Intelligence, SAP Analytics Cloud, and SAP AI offerings embedded across business processes.
Analytics connects business users, data scientists, ML engineers, finance leaders, supply chain teams, and IT organizations around a shared goal: turning SAP data into operational insight, predictive capability, and business process intelligence.
What is SAP Analytics?
SAP Analytics is the use of SAP data, analytics platforms, and embedded intelligence to understand business performance, identify patterns, predict outcomes, and guide decisions inside enterprise processes. It includes descriptive analytics through BI, advanced machine learning models that learn from changing data, and AI capabilities that support problem-solving and decision-making.
SAP Analytics focuses on how organizations use enterprise data to generate insight, support better decisions, and automate parts of day-to-day decision-making across SAP environments. The topic spans business intelligence, machine learning, artificial intelligence, SAP HANA, the Predictive Analytics Library, SAP Data Intelligence, SAP Analytics Cloud, and SAP AI offerings embedded across business processes.
Analytics connects business users, data scientists, ML engineers, finance leaders, supply chain teams, and IT organizations around a shared goal: turning SAP data into operational insight, predictive capability, and business process intelligence.
What is SAP Analytics?
SAP Analytics is the use of SAP data, analytics platforms, and embedded intelligence to understand business performance, identify patterns, predict outcomes, and guide decisions inside enterprise processes. It includes descriptive analytics through BI, advanced machine learning models that learn from changing data, and AI capabilities that support problem-solving and decision-making.
The end-to-end process of BI involves analyzing the data generated by businesses, transforming the data into insights, and leveraging those insights to make optimal decisions. BI tools primarily leverage “descriptive analytics,” because these tools traditionally focus on analyzing current and historical performance based on data generated by the enterprise.
In practice, SAP Analytics helps organizations use tools such as SAP Analytics Cloud, SAP HANA, SAP Data Intelligence, and SAP AI capabilities to support reporting, planning, predictive analytics, automation, and business process improvement.
What are some SAP Analytics use cases?
Business intelligence and reporting
Teams use BI tools to analyze current and historical enterprise performance, transform business data into insights, and support decisions based on descriptive analytics.
Predictive analytics
Organizations use machine learning algorithms and SAP HANA’s Predictive Analytics Library to build models that learn from input data and support predictive use cases.
Self-service analytics
SAP Analytics Cloud supports business users with intuitive, AI-guided analytics capabilities, helping functional managers work with analytics without needing to be data scientists or technical managers.
Enterprise planning
SAP Analytics Cloud combines planning, predictive analytics, reporting, and BI, allowing organizations to use it as a collaborative enterprise planning tool.
Business process intelligence
SAP AI offerings are positioned to infuse intelligence into lead to cash, design to operate, source to pay, and recruit to retire processes.
Data science and ML development
SAP applications support data scientists and ML engineers building advanced ML models and solutions, while also helping end users perform advanced analytics with minimal technical proficiency.
What does SAPinsider research say about SAP Analytics?
SAPinsider research shows that analytics maturity increasingly depends on cloud-based platforms, self-service access, and cross-functional data models. SAP Analytics Cloud reflects this shift by combining planning, predictive analytics, reporting, BI, and AI-guided analytics for business users.
The SAP Business Data Cloud benchmark shows that data foundations remain a major constraint. Only 3% of organizations have a unified governed data layer, while 38% remain siloed, limiting progress toward real-time analytics and AI-driven decision-making. Still, investment momentum is building. SAPinsider found analytics modernization was a top SAP BDC driver at 28%, followed by AI and agent-based use cases at 26%.
SAPinsider’s AI maturity research reinforces the importance of trusted analytics foundations. While 91% of respondents report some AI use, 79% cite access to high-quality, trusted data as a requirement for successful AI strategies.
Ask the Expert | SAP Solutions for Planning & AnalysisThis interactive session will help you navigate the various Planning & Analysis scenarios supported by different SAP planning solutions. Attend this session to ask the experts about the latest in features, functions, strategy, guidance, and future direction to gain the latest understanding and update on where you are and where you can be in your Planning landscape.
Maximize Your Investment in SAP and Azure Synapse to Create a Cost-Effective Data Analytics StrategyBusinesses across the globe are struggling as they attempt to wrangle multiple data sources into a cohesive data analytics strategy. Bringing together SAP and non-SAP data is complex and requires significant technical resources. In this session, learn from experts about how you can leverage IBM to help you bring this data together in a data fabric that maximizes your investment in SAP combined with Azure Synapse creating a cost-effective data analytics strategy and […]
Jun 29, 2021
•1 minute read
Elevating Insights: Moving Data and Analytics to the CloudData management, data warehousing and analytics are all moving to the cloud — and opening up new opportunities. In this interactive session, we’ll address the business imperatives for adapting your data architectures to the platforms of the future, with tips on how to overcome common barriers to successful transitions. We will cover a variety of […]
Jun 15, 2021
•1 minute read
How analytics changes with SAP S/4HANA and impact to modern data platformAs you transform your business with SAP S/4HANA, the way analytics are handled is going to change. SAP S/4HANA opens insights like never before. A new approach to a modern data platform adds significant value and provides the opportunity to unlock the potential of a SAP S/4HANA transformation.
Attend this comprehensive session to:
-Learn how to perform operation analytics in SAP S/4HANA
-Receive practical tips on how to use advanced analytical capabilities with SAP S/4HANA and other systems
-Understand how to create a modern data platform
May 27, 2021
•1 minute read
Leveraging Machine Learning for Demand ForecastingUntil recently, conventional time series forecasting methods have been predominantly used for forecasting in demand planning. A majority of demand forecasting tools in the market leverage these methods in their solutions. With advances in technology and computing power, the sophistication of these time series algorithms has increased thereby increasing forecast accuracy.
However, with the advent of machine learning (ML) tools and increased interest in exploring them to improve forecasting approaches and methods, many vendors are increasingly incorporating ML-based forecasting methods in their tools. A key aspect to remember is that most of the frequently used ML algorithms have been around for decades now. Technology and computing power today allow us to leverage them easily in a variety of ways and applications. This article shares some Machine Learning approches that are being used by SAPinsiders.
May 23, 2021
•4 minute read
A quick comparison of SAP S/4HANA Cloud, SAP Analytics Cloud, and SAP Data IntelligenceThe goal of the presentation is to explore the latest updates related to SAP cloud technologies (SAP Analytics Cloud, SAP Data Intelligence, and SAP S/4HANA Cloud), and as a useful guide to companies to choose when each of these technologies is applicable to them depending on their key processes they want to involve in the cloud. It is oriented to towards decision makers and business managers interested to use SAP Cloud technologies, but I am not sure which one is appropriate for their process and their organization. The result of this presentation is to guide business users and technical managers to know exactly what capabilities can be found in each of these technologies, and how they align with other business processes.
Key takeaways:
-How to choose the right technology for you Key functionality differences
-Explore the limitations of each of them Why SAP Cloud technologies are important to consider including them in your ecosystem
-A quick review of a practical application of SAP Cloud technologies
May 12, 2021
•1 minute read
Drive Predictive planning through machine learning with SAP Analytics CloudSAP Analytics Cloud provides machine learning capabilities that can help organizations integrate advanced and predictive analytics within their planning processes. Given the rapid pace of change and disruption within global organizations, these features can provide useful insight to the business. In this session you will:
- Gain a detailed introduction to the concept of predictive planning and how it is improving the way enterprise organizations run their business
- Walk through the machine learning and predictive planning capabilities available in SAP Analytics Cloud
- Understand the skills and technology prerequisites needed to unlock the potential of SAP Analytics Cloud’s predictive planning capabilities
May 12, 2021
•1 minute read
The Role of Analytics in Business Process Intelligence: A RISE with SAP PerspectiveIncreasingly, businesses are shifting their focus to accommodate the new digital reality. Technology is a key enabler in this aim, but businesses also need to consider what needs to change within their enterprises, including their processes and organizational design. Business transformation has become the front-and-center strategic priority that helps organizations adapt to the digital world and ultimately deliver value to customers.
The business process intelligence (BPI) component of RISE with SAP enables businesses to become intelligent enterprises by providing best-in-class processes, process management, and process intelligence capabilities. When linked with analytics capabilities, BPI serves as a foundational component for driving business transformation because it extensively leverages all three key ingredients involved in the journey: people, process, and technology.
In this article, Kumar Singh, Research Director, Data & Analytics, Supply Chain Management, SAPinsider, explains how analytics-powered BPI establishes process foundations that drive and undergird the success of a business transformation journey.
Read this article and learn:
• The role of analytics in supporting four critical BPI sub-components: Monitor and Analyze, Design, Simulate and Improve, Model and Manage, and Benchmarking.
• The value of an effective and robust data collection and data management infrastructure to eliminate data latency, quality, and integrity.
• About the importance of good data to drive process improvements, process re-design, and process optimization in business transformation initiatives.
• How strategic and thoughtful KPIs help improve processes continuously while serving as a benchmark against the best in your class.
• Why investing in people – an analytics talent pool dedicated to BPI and BPM – is essential to enhance analytics capabilities and drive business transformation success.
May 10, 2021
•6 minute read
Enterprise Artificial Intelligence – Embedded AIIf your company has not begun building an artificial intelligence (AI) strategy, it may risk falling behind competitors. That could mean lagging in areas of innovation that AI can enable, including improved or new products, reduced risks, and a better bottom line. There is good news for SAP customers: SAP has already begun embedding AI into its offerings, intending to make them ready to use. Additionally, SAP provides development platforms with AI capabilities that will enable customers and partners to enhance SAP systems with AI innovations. How can SAP customers incorporate SAP’s AI work into their own strategy?
In an exclusive piece for SAPinsider, Dr. Feiyu Xu, Senior Vice President, Global Head of Artificial Intelligence at SAP teams up with Maximilian Herrmann, Project Consultant and Storyteller at SAP, to detail SAP’s plan for AI both within and complementary to its products, as well as what the vendor and its customers have already achieved in the AI space.
Read this column and discover:
- The growing market and demand for AI across many industries and the common roadblocks to adoption that companies are facing;
- How SAP embeds AI into processes and applications, and how it develops ready-to-use AI functionalities with its internal “AI Factory” approach;
- The AI-powered products and services that SAP currently offers and how customers can use them; and
- An embedded AI use case for increasing efficiency around supplier invoice processing already in use by more than 100 small business and medium enterprise (SME) SAP customers.
May 4, 2021
•9 minute read
The journey from Strategy to an Analytics Algorithm : A Marketing Analytics exampleEvery Analytics algorithm that you use in your teams should tie to your Corporate strategy goals. However, very few resources currently clearly highlight how. Closing this link, in my mind, is one of the ingredients to the secret sauce to developing analytical products that will work, in a sustainable way (not a blip that goes […]
Feb 6, 2021
•1 minute read
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