SAP Analytics Cloud (SAC) is a cloud-based software-as-a-service that provides all the business intelligence, augmented analytics, predictive analytics, and enterprise planning capabilities in a single system.

Business intelligence, enterprise planning, and augmented analytics.

SAP Analytics Cloud can become a consolidation solution only by acquiring the consolidation extension for SAP Analytics Cloud. The extension enables consolidation for different methods (Holding, Full, Proportionate and Equity) and for as many consolidation scopes as required. Click here to know more.

SAP Analytics Cloud (SAC) offers a range of advantages, including seamless collaboration with controlled data for generating interactive visualizations and dashboards securely. Its intuitive self-service analytics empower users to uncover valuable insights and distribute actionable findings throughout the organization effectively.

SAP Analytics Cloud is a true SaaS service previously delivered in SAP data centers (SDC) on SAP’s own Neo platform. SAP Analytics Cloud provides customers with global deployment options by partnering with SAP Cloud Platform and public cloud providers to support data center options that meet customer business needs. Below are public cloud partners:

• AWS – primary public cloud for SAP Analytics Cloud.
• Azure – primary alternative option to AWS.
• Alibaba – primary public cloud for China market and cyber security compliance.
• AWS Government cloud – FedRamp certified data center to support the compliance needs of the U.S. government.

Models are comprised of dimensions and measures and represent a specific subset of data and are the primary data sources for SAP Analytics Cloud stories and analytic applications.

There are mainly two types of models: Live and Load. Live models to not store data, meanwhile load models do store data and can be further divided into two categories: Analytic model (read-only) and Planning model (read/write)

An analytic model is used strictly for read-only data reporting and analysis. Analytic models do not have a version type dimension.

Planning models are pre-configured with required dimensions for time and version. They offer support for multi-currency and security. Users with planning permissions can create their own versions of data, write data to the model by typing new values, copying and pasting data, and using data actions.

A dataset is a simple collection of data usually presented in a tabular format. You can use a dataset as the basis for a story. SAP Analytics Cloud has two types of datasets: Embedded (cannot be shared outside the story or refreshed) and Public (standalone datasets and can be shared among different stories)

Providing a fast and easy starting point with prebuilt stories, analytics applications, models and business content packages enables a head start for analytics and planning, the rapid result-based setup majorly accelerates projects reliable data scenarios with industries best practices from SAP business process experts through quickly accessing the included detailed documentation of KPIs, models, data sets, and data flows using the included sample data or live connections. Tailored home pages using the Analytics Catalog allows users to have a unified access to all their analytics content, from prebuilt, SAP BusinessObjects, Business Intelligence Suite, and third-party solutions.

Augmented Analytics is a smart feature in SAP Analytics Cloud, ensuring to help users make the best decisions faster with automated insights powered by machine learning. The smart features of SAP Analytics Cloud consist of Search to Insight, Smart Insights, Smart discovery, Time Series Forecasting, and Smart Grouping.

SAP machine learning algorithms are used by SAC’s Smart Predict to explore datasets relationships and construct a predictive scenario formula predicting future events, and trends from the current data, predicting outcomes and generating forecasts at the push of a button. With three types of Predictive Scenarios supported in Smart Predict: Classification, Regression, and Times Series; the automation and augmenting of your Business Intelligence experience intricately provides more data to insight.

SAP Predictive Analytics; a statistical analysis, data mining and predictive analytics software solution that enables users to build predictive models to discover hidden insights and relationships in data organizations to extract valuable insights from their data and make predictions about future events or outcomes. Some of the key features of SAP Predictive Analytics include:

1. Automated Predictive Modeling, data preparation and deployment
2. Automatic data prep on command
3. Model Assessment and Deployment
4. Advanced visualization capabilities for the quick disclose of insights in Analytics and Reporting
5. Ability to integrate with R enabling a large number of algorithms and custom R scripts
6. Deploy SAP Predictive Analytics alone or with SAP HANA

SAC provides business users (non-data scientists) with automated, easy-to-use predictive analysis capabilities: Augmented Analytics.

Augmented Analytics comprises a set of SAP Analytics Cloud features that enhance the analytics process using machine learning. The Augmented Analytics features include Smart Insights, Search to Insight, Smart Discovery, Smart Grouping and Smart Predict

A predictive scenario is a preconfigured workspace that you can use to create predictive models and reports to address a business question requiring the prediction of future events or trends. You choose the one that is relevant to the type of predictive insights for which you are looking.

• Classification – Used to anticipate the behavior of customer, propensity to buy, and risk of failures. Classification analysis identifies the category to which a new observation belongs on the basis of a training set of data that contains observations whose category membership is known as shown in the figure below
• Regression – to predict numeric values and identify their influencers. It is a statistical indicator which measures the average of the square difference between values predicted by the predictive model and actual values of the target for all cases of the validation dataset.
• Time Series Forecasting – useful for estimating future values of a measure where you have a time dimension available to help you identify a trend. Used to generate Time Series Forecasts with individual forecasts generated for each value of a dimension

Smart Assist features:

• Search to Insight
• Smart Insights
• Forecasting
• R Visualization
• Smart Grouping
• Smart Discovery

Search to Insight is a natural language query interface used to query data (create queries that provide more insight into the analysis)

While working with indexed models based on acquired and SAP HANA, SAP S/4HANA, SAP Universe, and SAP BW live data, you can query Search to Insight to get quick answers to questions and incorporate these insights into a story.

Smart Insights gathers data from all the high points in a Big Data model and turns it into intelligent information using advanced scoring models and predictive algorithms. For example, it picks up the high contributors of a selected value in a data or variance point and analyze the roots of the data to identify top members of a dimension, and add contexts to visualizations to help business users save a major amount of time when looking for quick clarifications to specific values.

The machine learning calculations scan through information that is of the same nature to the selected data point and looks for influencers in the members of the dimension of the selected data point and analyzes what influences the particular selected value.

Time Series Forecasting is used to forecast the future evolution of a measure based on its past values. For example, how many products should be produced to cope with demand.

SAC (SAP Analytics Cloud) Smart Predict and Predictive Planning offer such forecasting capabilities. The high-level principle is that several predictive models are generated behind the scenes based on the three techniques

The time series forecasting algorithm analyzes the time series and breaks it down into different components.

• Trend is the general orientation of the signal or its long-term evolution.
• Cycles correspond to periodic and/or seasonal events.
• Influencers indicates how the variable to forecast is influenced by other variables. This is an optional component which is present only if influencers are part of the predictive model.
• Fluctuation is what is left when the trend, the cycles (and optionally the influencers) have been extracted.
• Residual is what remains from the time series when all the above components have been subtracted from the original time series. This part of the data cannot be modelled and does not help determine predictive forecasts
  
  

Select the forecasting option in the chart or table menu, which enables the following:

• Adding a forecast to a time-series chart, line chart, or planning table.
• Automatic forecasting, triple exponential smoothing, and linear regression.
• Forecast quality display on the chart and additional input criteria that can be used to improve the accuracy of the forecast.

R is an open-source programming language that includes packages for advanced visualizations, Statistics, Machine Learning and much more.

SAP Analytics Cloud R Visualization feature allows users to integrate their own R environment into SAP Analytics Cloud.

R visualizations work with data from SAC models, filters that are configured for the whole history work with R visualizations as well, there is also the possibility of adding individual filters to these elements with standard SAC tools. This provides particular flexibility and the ease of use.

Another benefit of integrating R visualizations with SAP Analytics Cloud is that it’s flexible. You can change the chart type, characteristics, and depict your information in a variety of ways.

With this new integration in SAP Analytics Cloud, you can now:

• Insert R-visualizations into your story
• Interact with R-visualizations using SAP Analytics Cloud-controls (such as filters)
• Share these SAP Analytics Cloud stories, which include R-visualizations, with other users.

The functionality of R visualization in SAC enables you to create both standard graphs and visualizations of more complex data analysis. It is also possible to preview R visualizations and share a story containing R visualizations with other users.

You can create smart groupings (clusters) of data values across several measures. Use the recommended number of groups most appropriate for your data, automatically create segments on different types of data.

Smart grouping is available for both bubble and scatterplot charts for correlation analysis. You can use related APIs to trigger grouping of data points in charts in analytic applications based on similar properties.

SAP Analytics Cloud’s powerful Smart Discovery provides automated insights and recommendations for data exploration and analysis. It leverages machine learning algorithms to help users uncover hidden patterns, correlations, and outliers within their data. Smart discovery settings depend on the type of underlying model you are using, a classic account model or a new model type, with a main difference is the handling of measures which are the structures in the model that store the numeric values.

With Smart Discovery more than one business question can be asked, allowing the exploration of data from different angels by asking it to analyze the same target in relation to different entities, producing different results.

Some key aspects of Smart Discovery in SAP Analytics Cloud are: Automated Data Exploration to discover the key influencers driving your KPI’s, discover influencers insights, identify outliers, analyze patterns in data, use historical data to predict future outcomes, and simulate what-if scenarios.

ELIMMEMBER is a function in Advanced Formulas that resembled the US Elimination in SAP BPC, whereas accounts are knocked off in full against each other through an Elimination entity. Unlike InsightCubes’ Consolidation Extension for SAC, this logic doesn’t take into consideration any Consolidation method, Ownership percentage or scope.

To gain comprehensive IFRS/GAAP consolidation capabilities, know more about InsightCubes’ Consolidation Extension for SAC