Technology Blogs by SAP
Learn how to extend and personalize SAP applications. Follow the SAP technology blog for insights into SAP BTP, ABAP, SAP Analytics Cloud, SAP HANA, and more.
Showing results for 
Search instead for 
Did you mean: 
0 Kudos
The wTracAugmented analytics is defined by Gartner as the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation and insight explanation to augment how people explore and analyze data in analytics and BI platforms.

In SAP Analytics Cloud, you can leverage augmented analytics with our portfolio of Smart features. Smart features are dedicated to helping Business Users uncover insights faster and understand trends within their data to help drive decision making. In this blog we will walk through Jane’s analytics journey and see how she leveraged various Smart features to help conduct her analysis!

Jane has recently joined AlpineCo, a global ski and snowboard manufacturing company, as a Business Analyst. With the busy holiday season approaching the in-house Data Analytics team is swamped and have reached out to Jane for help. She has been tasked with analyzing historical sales data and presenting an overview of her findings.

This would normally not be an issue for an experienced Business Analyst such as Jane, however she only had until the end of the day. With this time constraint in place, Jane turned to the Smart features available on SAP Analytics Cloud. The use of augmented analytics helps her to accelerate her workflow and reveal insights.

Get started today with your free trial for SAP Analytics Cloud. Sign up now. 


Augmented Analytics: Getting Started

Jane was handed an excel file with sales data from the past 2 years and wants to bring it into SAP Analytics Cloud.  To do so, she simply drags and drops the file in by using the “I’m Feeling Lucky” functionality.

No data preparation is necessary as the system automatically recognizes the measures and dimensions in her dataset.

Looking over the data exploration view, Jane already has an idea of how to approach her analysis.

Search to Insight: Get answers about your data

With limited knowledge of the underlying data, Jane starts her analysis by launching Search to Insight. Jane is able to ask questions in natural language and receive answers instantly with the most appropriate visualization. Jane is particularly interested in knowing the Order Value by Product.

The resulting bar chart clearly shows that skis are outselling snowboards.

By drilling down further she notices that the SK 500 is the most popular model.

Smart Insights: Uncover top contributors and detect changes over time

Jane learned that the SK 500 is selling well, but why exactly is it so high? This is where Smart Insights can help to find out what contributes to Order Value.

Jane adds a Smart Insights footer to her chart and it’s telling her that the variation is driven by the Sales Agent Tracy Jiang.

Taking it step a step further by clicking “view more,” Smart Insights also detected a significant data change. There was a large increase in Order Value from Q2 to Q3.

This trend is likely due to retailers stocking up on equipment for the winter season.

Smart Discovery: Automatic dashboard generation

In addition to Order Value, AlpineCo uses Units Sold as a key metric to measure success.

To jumpstart her exploration into Units Sold and help identify patterns in the data, Jane uses Smart Discovery. The main question she wants answered is: What are the influencing factors for Units Sold?

In just a few clicks Jane was able to generate 4 pages of analysis: overview, key influencers, unexpected values and simulation.

With the variety of visualizations and insights and provided, Jane has a better understanding of the factors that affect AlpineCo’s performance.

R-Visualizations: Build custom visualizations

Knowing that AlpineCo has over 2000 global customers ranging from retail to wholesale to direct, Jane wants to determine who the top customers are. She decides to use the R-Visualization feature in SAP Analytics Cloud to create a word cloud.

The top 20 customers are visualized in the word cloud above. The customers are ranked using varying font sizes and colors. A larger font equates to a higher Order Value.

Jane can look at the chart and see that one of the top customers is Ethos Wheel.

Finishing Touches

Before her meeting, Jane decides to adjust the dashboard using the styling tools.

Jane changes the fonts and colors to not only align with AlpineCo’s branding but to also better highlight key findings.

With this improved layout and design Jane is now ready to showcase her analysis and tell a compelling story!

Augmented Analytics: Putting it all together

Jane found herself in a difficult situation having to complete a lot of work in a short period of time. By leveraging a variety of Smart Features, Jane was able to quickly answer specific questions while also surfacing patterns and complex relationships hidden in the data.

Jane discovered the following:

  • The SK 500 skis are the bestselling product

  • Tracy Jiang significantly drove the high Order Value for the SK 500

  • There was a large spike in Order Value from Q2 2019 to Q3 2019

  • Ethos Wheel is the top customer by Order Value

Want to learn more about how a cloud-based analytics platform helps you perform processes on company-wide data and identify new opportunities? Read our Ultimate Guide to Enterprise Analytics. To learn more about how a cloud-based planning solution can help you uncover trends, patterns, and correlations in your enterprise-wide planning data, check out our Ultimate Guide to Enterprise Planning.