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Driving Machine Learning with SAC

13 Apr 2021

SAP Analytics Cloud uses machine learning to enhance the business intelligence landscape, with just a few clicks users can uncover deeper insights, increase forecast accuracy, and improve decision making. Importantly these features can be used by anyone, taking self-service BI to the next level.

If 2020 has proven anything, it is that organisations need to be more efficient, further leverage data, and more accurately plan ahead. For companies looking to invest in the future the solution may lie in adopting the machine learning concepts in SAP Analytics Cloud (SAC). A recent Forrester study revealed that of the organizations who have adopted augmented analytics:

  • 70% of companies experienced revenue growth of 10% or more over a period of 3 years.
  • 51% reported greater confidence in decision-making.
  • 50% reported an increase in analytics efficiency.
  • 48% reported an improvement in analytics effectiveness.

SAP Analytics Cloud and Machine Learning

Machine Learning sounds like a daunting and complicated concept especially for end users with minimal technical experience, SAC delivers a selection of simple but powerful machine learning features categorised within the tool as “augmented analytics” which provide the opportunity for any business to empower their employees and increase the effectiveness of their Business Intelligence (BI) solution. This next step in the evolution of business analytics will ensure that organisations have access to key information at the right time to best influence a positive future.

Augmented Analytics:When we talk about augmented analytics what do we actually mean? Essentially it is the integration of Artificial Intelligence (AI) into the BI landscape, allowing applications of AI such as machine learning and natural language processing to assist with the preparation and presentation of data. Augmented Analytics is considered to be the new generation of BI and is an area that is seeing expediential growth.

SAP Analytics Cloud: SAC forms the core of SAP’s BI strategy and the key feature is simplicity, a central tool in which an organisation can deploy entire analytics strategy from day to day operational reporting via stories through to strategic management dashboarding in the Digital Boardroom, as well as end to end planning and forecasting with AI functionality integrated throughout the tool.

SAC provides user-driven machine learning tools, which means that users can easily locate the tools and do not need to be explicitly taught how to use them. The predictive functions are integrated seamlessly, I personally found these tools to be user friendly and simple to navigate. Augmented Analytics in SAC consists of 4 key functions:

Smart Predict:

Source: Capgemini

Smart Predict is a feature that helps you generate predictions about future events, values, and trends by leveraging historical data, it then identifies the best relationships or patterns of behaviour to generate values for the future. Three predictive scenarios are available to choose from depending on the type of business question, examples of this can be seen in the visual below. In this era every business collects an obscene amount of data; it’s the process of transforming this into actionable insight which provides the real value. Greater accuracy in forecasting and better-educated decision making is exactly what you can expect from smart predict.

Source: Capgemini
Source: Capgemini

Smart Discovery:

Source: Capgemini
Source: Capgemini

Smart Discovery helps to uncover new or unknown relationships between values within a dataset to help understand the main business drivers behind core KPIs and calculations. For example, uncovering the key drivers behind revenue, net margin and employee productivity. A vital part of this tool is the Simulation tab, which allows users to experiment with data and understand the impact this could have on a chosen KPI. For example, you can estimate the figures involved in a new sales opportunity or evaluate the potential damage of risks. Importantly, you can transfer these visualisations to new or existing stories with only a couple of clicks to be shared accordingly within the business.

Search to Insight:

Search to Insight is an interface based on natural language to query the data. This feature allows a user to simply ask questions in plain english to get quick, visualized answers which can then be integrated into a story. A simple but effective tool that puts more power in the hands of the everyday business user taking self-service BI to the next level. This can be accessed on any story with a single click via the small light bulb symbol which is located on the context menu in the top right corner.

Source: Capgemini
Source: Capgemini

Smart Insights:

Source: Capgemini
Source: Capgemini

Smart Insights allow users to quickly develop a deeper understanding of complex data, this is achieved by using machine learning technologies which analyse visualisations in a story. Additional insights are provided by selecting specific data points which will display dimensions and elements with the greatest influence on the selected value. This feature can be activated on any visualisation and helps to answers questions about what contributes to creating that specific value. For example, understanding which product is providing the highest net profit and why.

R-Script Visualisations:

R-script is an open-source programming language which is used for statistical computing and data analysis, it is commonly used to develop machine learning models, although this is a more complex feature targeting data scientists it is another function which can be used to enhance stories and integrate powerful AI features. SAC now offers users the ability to integrate their own R environment, enabling the creation of interactive visualisations and advanced analysis. Once connected user are able to:

  • Insert R visualizations into stories
  • Interact with visualizations, using filters/sorts and other controls
  • Edit R scripts and preview visualizations
  • Share stories containing R visualizations with other users


There is no doubt about it SAC offers a range of easy to use, intuitive and powerful machine learning functions which are capable of enriching the user’s experience by generating new insights, uncovering unforeseen trends and improving the decision-making process. SAC and its machine learning capabilities are the future of SAP’s analytics platform, with plans being created for a simple migration from SAP legacy toolsets to SAC. Investing in augmented analytics right now is investing in a better future.