Explaining AI, Machine Learning, and Augmented Analytics

Objective

After completing this lesson, you will be able to explain how AI technology and machine learning are used in augmented analytics.

Artificial Intelligence, Machine Learning, and Augmented Analytics

SAP Analytics Cloud uses artificial intelligence (AI) and automated machine learning technology for predictive analysis to help discover deep insights, simplify access to critical information, and empower informed decision making.

Watch this short video to find out more.

Machine and Rule-based Learning

Machine learning gives computers the ability to learn without being explicitly programmed and is a key component of SAP Analytics Cloud augmented analytics.

Artificial intelligence is a combination of algorithms, code, or techniques that enable machines to mimic, develop, and demonstrate human cognition or behavior. AI can be supported by if or then type rules, or by using machine learning techniques, or by a combination of both.

Augmented analytics is an approach in data analytics that employs the use of machine learning and natural language processing (NLP) to automate analysis processes that are normally performed by a specialist or data scientist.

Watch this short video to learn more about the difference between machine learning and rule-based learning.

SAP Analytics Cloud Smart Features

SAP Analytics Cloud augmented analytics can help investigate a variety of business scenarios. SAP Analytics Cloud uses AI technology for predictive analysis to help discover deep insights, simplify access to critical information, and allow informed decision making.

A slide picturing the different ways that AI and machine learning can support solving a range of business problems.

Sales and marketing	Operations	Fraud and Risk	Finance and HR
Churn reduction	Predictive maintenance	Fraud and abuse detection	Cash flow and forecasting
Customer acquisition	Load forecasting	Claim analysis	Budgeting simulation
Lead scoring	Inventory/demand optimization	Collection and delinquency	Profitability and margin analysis
Product recommendation	Product recommendation	Credit scoring	Financial risk modeling
Campaign optimization	Manufacturing process optimization	Operational risk modeling	Employee retention modeling
Customer segmentation	Quality management	Crime threat	Succession planning
Next best offer/action	Yield management	Revenue and loss analysis

Smart Features in SAP Analytics Cloud

SAP Analytics Cloud provides you with many artificial intelligence and machine learning utilities to assist you in your data analysis and planning activities.

SAP Analytics Cloud Just Ask Feature: Request information in natural language simply by typing a question about your data.

Smart Insights: Smart Insights take the form of a textual insight combined with a visualization to provide you with as much information as possible about your selected data point or variance.

Smart Predict: Use a trained data set to build a predictive model that can be applied to a target data set. Run a forecasting algorithm to automatically project out time frames based on historical data.

Note

Smart Discovery features are only available in classic design stories. They are not included in this learning journey. For more information, visit the SAP Help Portal.

Create an Automatic Forecast Using SAP Analytics Cloud Smart Features

Business Scenario: You have created a chart in your story. You want to add a forecast to the chart and decide to use SAP Analytics Cloud smart features.

Task Flow: In this practice exercise, you will:

Add an automatic forecast to your story.
Use advanced options to add a linear regression forecast to your story.
Use advanced options to add an exponential smoothing forecast to your story.
Review the forecast quality.

ExerciseStart Exercise

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