SAP Analytics


Analytics pertains to leveraging data generated and captured across the organization to generate insights that can help transform the way organizations run. Analytics can also  help build capabilities that can automate many aspects of day-to-day decision making that is currently performed manually. There are three main categories of analytics leveraged in organizations today:

Business Intelligence (BI)

Analytics pertains to leveraging data generated and captured across the organization to generate insights that can help transform the way organizations run. Analytics can also  help build capabilities that can automate many aspects of day-to-day decision making that is currently performed manually. There are three main categories of analytics leveraged in organizations today:

Business Intelligence (BI)

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.

Machine Learning

Machine learning (ML) is a subset of artificial intelligence (AI) algorithms. The differentiating aspect of these algorithms is that they can learn from the input data and modify the model based on changes in that data. It is this “learning” aspect that makes these algorithms powerful.

Artificial Intelligence

In simple terms, Artificial Intelligence (AI) refers to systems or solutions that can replicate human decision-making capabilities. These solutions often leverage a combination of software and hardware to mimic human capabilities like problem -solving and decision making

Key Considerations for SAPinsiders

SAP applications leverage AI and ML algorithms extensively to either embed innovative capabilities within their solutions, help end-users perform advanced analytics with minimal technical proficiency, or allow data scientists and ML engineers to build advanced ML models and solutions. SAP HANA has been designed to be easily leveraged as a scalable ML platform. A powerful tool built into SAP HANA is the Predictive Analytics Library (PAL).

SAP Data Intelligence has a rich ML content library. Like most best-of-breed analytics tools, SAP Analytics Cloud provides users the ability to leverage advanced Machine Learning (ML) algorithms.  While ML algorithms have many applications, predictive analytics remains a key one.

On the business processes side, SAP AI offerings promise to infuse transformative intelligence to all key business processes areas like lead to cash, design to operate, source to pay and recruit to retire. AI algorithms help include innovative features across all these processes.

498 results

  1. Driving HCM Success With Analytics

    Reading time: 3 mins

    SAP organizations are encouraged to adopt new analytics capabilities in SAP SuccessFactors, such as Report Stories and Workforce Analytics, to optimize HR functions and drive innovation, especially as older reporting tools are set for retirement by 2025.

  2. Journey to the Cloud: Complement your SAP BPC deployment with SAP Analytics Cloud

    As an SAP Business Planning and Consolidation (SAP BPC) customer you already made a key investment in planning software to support your business. Now, as cloud technology evolves and improves, you need to be considering whether extending your existing planning and visualization capabilities to take advantage of cloud technology is right for you. In this…

  3. Turbocharge SAP Analytics Through No-Code Data Integration

    Reading time: 4 mins

    SAP’s enterprise software is used by 80% of the world’s Fortune 500 companies and 98% of the world’s most valuable brands. Whether a company is using SAP’s ERP, supply chain, spend management or human resource solutions, your data is useless if you can’t analyze it.

  4. Case Study: End-to-End Planning with SAP Analytics Cloud

    Reading time: 1 mins

    While partnering with SimpleFi and deciding on a Hyperion Planning replacement, WWW was able to identify and address key pain points in the legacy tool and business process and envision how a new tool could tackle those hurdles in an effective manner. WWW wanted to provide a flexible, scalable planning platform that allows for planning,…

  5. Automation analytics recession

    Thriving in Recession With Analytics and Automation

    Reading time: 6 mins

    In this article we focus on how executives can leverage the competitive advantage levers of analytics and automation to manage their companies through this and future recessions. Membership Required You must be a member to access this content.View Membership LevelsAlready a member? Log in here

  6. A Guide to SuccessFactors HCM Reporting Options (Part 1)

    Reading time: 16 mins

    Learn more details about the available SuccessFactors reporting options and get some technical and practical examples for how these reporting options can be used to solve the challenges facing your business. Key Concept SuccessFactors Workforce Analytics provides concrete and actionable insights on workforce data to drive your business strategy today and help you plan for...…

  7. The Role of Analytics in Business Process Intelligence

    The Role of Analytics in Business Process Intelligence: A RISE with SAP Perspective

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    Increasingly, 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…

  8. How Recordati Streamlined SAP Data Management with CData Sync

    SAP Business Data Cloud Unifies Enterprise Data

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    SAP has announced SAP Business Data Cloud, a new solution that aims to unify SAP and third-party data across an organization. The company sees the offering as an evolution of data, analytics, and planning strategy that addresses the challenges SAP is seeing in the data market today. Some of those hurdles include data silos, the…

  9. Live from SAPinsider Studio: Clemens Praendl on SAP Cloud for Analytics

    Clemens Praendl, SAP Senior Vice President and General Manager, Analytics, joins SAPinsider Studio at Reporting & Analytics 2015 to discuss the business value cycle in the context of SAP Cloud for Analytics. This is an edited transcript of the discussion. Ken Murphy, SAPinsider: Hi this is Ken Murphy with SAPinsider and I am here at...…

  10. Live from SAPinsider Studio: Neil McGovern of SAP on Agile Analytics

    Neil McGovern, Senior Director, Product Marketing, SAP Data Warehousing, joins SAPinsider Studio at the 2016 BI-HANA-IoT event to discuss agile analytics and the modern data warehouse. Topics of this discussion include the logical, modern data warehouse, the importance and benefits of avoiding data replication in the data mart, and the role of SAP S/4HANA in...…