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

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.

80 results

  1. How Big Data and AI Help Us Tackle the World’s Biggest Problems in 2017 and Beyond

    Published: 10/February/2017

    Reading time: 4 mins

    Some of the world’s most troubling issues — climate change, the energy crisis, healthcare, and overall safety — are being addressed with emerging technology such as artificial intelligence and big data. Analysts are gleaning more and more insights everyday to help make the world a better and safer place.

  2. How to Configure an SAP Stability Study for Better R&D and Product Improvement

    Published: 09/December/2016

    Reading time: 25 mins

    Discover how SAP system functionality can assist businesses in research and development (R&D) and product improvements. In certain sectors such as pharmaceuticals and the food industry, it is a legal requirement to document and maintain the data related to various tests carried over in the R&D phase for product approvals. Learn step-by-step configuration to realize...…

  3. 8 Simple Steps for Creating a Successful Dashboard (Part 2): Steps 1 – 4

    Published: 14/November/2016

    Reading time: 14 mins

    In this second part of a three-part series of articles, learn about the first four steps of this new approach to building better dashboards. Key Concept One key for creating a successful dashboard is to have a complete grasp of the actual business problem that the dashboard should solve. This process also includes interacting with...…

  4. Data Analytics for the Modern Business

    Published: 21/October/2016

    Reading time: 2 mins

    A logistics company that reroutes its trucks in real time to avoid a traffic jam. A manufacturer that preemptively services an asset before it breaks down. A retail organization that selects the location of its new store based on foot traffic on a city street. These are just some examples of modern businesses that make…

  5. Modern Analytics for the Live Business

    Published: 10/October/2016

    Reading time: 5 mins

    The amount of structured and unstructured data flowing into today’s businesses is overwhelming — and can make or break an organization in the digital age. If it remains siloed and disorganized, it‘s difficult to generate the timely, enterprise-wide insights required to run a live business. Discover how SAP BusinessObjects provides customers with a modern, end-to-end…

  6. Analytics Is the Key to Efficient Application Delivery

    Published: 10/October/2016

    Reading time: 2 mins

    New business intelligence (BI) technologies enable companies to harness and drive insights from vast amounts of customer data. But external data isn’t the only resource companies can draw on. Internal data, such as system performance data, is also a vital source of insights that companies can use to increase efficiency and agility. Learn how you…

  7. 8 Simple Steps for Creating a Successful Dashboard (Part 1): An Overview

    Published: 21/July/2016

    Reading time: 12 mins

    Increasingly, business users are requesting that dashboard designers provide compelling data visualizations that outline the overall situation of a company, while at the same time demanding that this be done more quickly. This leaves less time to gather the requirements, come up with the correct data, and develop a great design. Learn how to streamline...…

  8. 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…

  9. Farouk Systems Achieves Tangle-Free Spreadsheet-Based Reporting

    Published: 06/January/2016

    Reading time: 6 mins

    Farouk Systems, a global high-end hair care manufacturing company based in the United States, replaced its homegrown, legacy systems with a full SAP ERP environment and simultaneously capitalized on the opportunity to upgrade its financial and operational reporting processes. Learn how Global Software’s Spreadsheet Server tool was deployed and discover the many ways Farouk Systems…

  10. Leverage Transportation Analytics to Solve the Logistics Puzzle

    Published: 04/January/2016

    Reading time: 2 mins

    Transportation organizations face pressure to develop lean operations to stand out among a crowded field of competitors, and are continually looking at more efficient ways to keep up with evolving customer demands while providing clear insights into all transportation processes. Keep up with how many organizations are modernizing transportation processes, including leveraging analytics for significant…