Smart Insights and Smart Discovery are two machine learning features in SAP Analytics Cloud. With the power of machine learning, they help users take advantage of advanced contribution, classification and regression techniques. These features help anyone discover hidden patterns and complex relationships in their information, even without any data science background or experience. These are powerful machine learning capabilities that help businesses make quick decisions with SAP Analytics Cloud.
What are Smart Insights?
Smart Insights takes a data point, variance in the data and examines what lies behind that data. It helps to quickly find what is behind a given object. It can add context to your point of view, helping you understand what's going on.
Smart Insights discovers the key drivers behind a chosen price or pivot point. Top contributors are the dimension members that make the largest contribution to the analyzed data point.
Why smart insight?
The benefit of Smart Insights is that it helps business users save time when looking for quick answers at a specific price. Therefore, without using Smart Insights, a business user would have to manually cycle through the data to identify the members of each dimension that contribute the most to the data point.
How do Smart Insights work?
Once a specific data point is selected, machine learning calculations are performed on information that is of the same nature as the selected data point. If the selected data point e.g. is Total Revenue, are the largest contributors based on Total Revenue. Parses the property in your selected data and looks for members in the properties that affect the selected value.
(Video) SAP Analytics Cloud-funktion: Smart Insights
To run Smart Insights, select a data point on a graph to display the quick action menu and select the light bulb symbol.
Select a data point from a graph -> Quick Action Menu ->
In this scenario, Smart Insights is used to explain the largest contributor to total sales revenue for a given organization.
- In the generated history, go to the button "More actions" -> "Add smart info"
- Now, when we run Smart Insights, we quickly see that the central region is the biggest contributor to our sales.
- Even using the bulb symbolin the top right corner of the page you can search for Insight. For example, you can search for the top 2 regions that contributed the most to total sales.
- It will show the top 2 contributors to total sales as shown below:
(Mais) SAP Analytics Cloud Planning - Smart Discovery - Smart Insights - Search to Insight
What is Smart Discovery?
Smart Discovery is a very powerful feature in SAP Analytics Cloud that uses machine learning to analyze and explore your data and uncover valuable insights. SAP Analytics Cloud's intelligent data discovery feature helps save time by running automated machine learning algorithms on the backend to discover correlations between items in your dataset and target metrics, for example KPIs such as revenue, days filled, sales, etc. With a few clicks, you can't not only get all the best influencers for your target, but you can also see the impact of other variables, see data anomalies and run what-if scenarios, analyze patterns in data and use historical data to predict future results.
Why Smart Discovery?
Smart Discovery in SAP Analytics Cloud helps business users interact with information, in the form of intuitive graphics and natural language processing (NLP), to make better, faster decisions and share valuable new insights with your organization.
How does smart discovery work?
The user selects a measure or dimension.
If a measure is selected, a regression model is created, and if a dimension is selected, a ranking model is created. If a property is selected, Smart Discovery will focus on members of the taxonomy group (target) selected by the user.
When the user selects Run, Smart Discovery begins creating and testing various test models using automated machine learning technologies. Smart Discovery will choose the best model based on accuracy, robustness and simplicity. This template will be used to create the 4 story pages – Overview Page, Key Influencer Page, Unexpected Values Page and Simulation Page.
- Summary Page – This page provides views to summarize the results of the target attribute or metric.
- Top Influencer Page – Key influencers are measures and dimensions that influence results or outcomes. They are identified from the information in your selected model using classification and regression techniques. Classification techniques are used to identify dimensions that separate outcomes into different groups of outcomes. Regression techniques identify relationships between data points to predict future outcomes.
The Key Influencer page shows variables that are related to each other and have the greatest influence on the target. This page lists (sorted from highest to lowest) down to almost the dimensions and measures that significantly affect the discovery goal.
(Video) SAP Analytics Cloud: Updates to Smart Insights
- Outliers Page - The Unexpected Values page displays the outlier information. This page is only displayed if there are unexpected values. The table shows records where the actual value differs greatly from what the predictive model would expect (expected values). The scatterplot shows these outliers to compare expected values with actual values. The bar chart compares expected values and actual values for the selected record.
- Mock Page - When the Smart Discovery goal is a measurement, a mock page is created. It allows us to test hypothetical scenarios. The site uses top influencers in an interactive hypothetical simulation. On the right of the page is a list of top influencers and their corresponding values. The user can change a value and simulate its effect. Select the value and use the slider that appears or the radio buttons on the page to enter a new value. Each time a value changes, a number flashes to show the percentage change from the previous set of values. The graph shows the contributions of each of the top influencers based on the selected values.
After you finish analyzing the Smart Discovery results, you can:
- Save the smart discovery as part of the new or existing story.
- Share this story with other users in your organization.
Example: Analysis CtraktorData to cover the budget
In this example, we use a scenario where an organization hires contract workers on an ongoing basis. We would analyze the factors that have a positive and negative impact on accomplishing the contractor's mission within their given budget. Using Smart Discovery, the organization can discover influencing factors and then take appropriate action to ensure that contractors complete their work within budget.
- Create a "New Story" and enter your data
- Create a "New Smart Discovery"
In this example, the "Percentage_of_Budget_Spent" column in the data shows how much of a specific contractor's budget was spent on their project. We will learn what data factors affect the %Budget_Spent field. The Smart Discovery interface allows us to easily exclude all measures and dimensions not required by the analysis.
- Select "Percentage_of_budget_spent" as the target
- Click the Run button.
When Smart Discovery runs, predictive technologies lag behind and use completely different algorithmic models to help us find the best fit for our data.
Top influencer bar chart page showing top influencers for "Percent_of_Budget_Consumed".By clicking on them, we can get more information about the effect of specific influences. This shows that the regulatory authorities have a greater influence on whether contractors exceed their 'budget'. Average,ErikeYuruIts contractors are collectively over budget so the agency can take the necessary action.
(Video) Sap Analytics Cloud Smart Insights | Make smarter cloud decisions with SAP Analytics Cloud
We can then analyze the unexpected values in our dataset to find the differences between the predicted (expected) values and the actual (actual) values of Consumed_Budget. The Unexpected Values page provides the following information:
The simulation function can be used to see how much we can expect in Percent_of_Budget_Consumed. Based on the selected criteria, we can see Influencer's contribution to potential_budget_percent_spending. Below we can see in the selected Supervision together with all the other fields that there is an expectation of a budget consumption of 93.89%.
Finally, after we acquire and collect all this new information through our smart data discovery analytics, we can share this information with our peers. We can simply select any of the graphics we need and pin them to any page to share.
- Click on any chart you want to share
- Click Copy to Page
- Select the page you want to pin the graphic for sharing
Thus, the Smart Insights and Smart Discovery features of SAP Analytics Cloud enable users, even those without data science experience, to gain insights and analyze the hidden and complex relationships and patterns in the information that help them make better decisions.
Images referenced at: https://blogs.sap.com/2017/07/07/sap-analytics-cloud-smart-discovery/
(Video) SAP analytics cloud insights inteligentes | Brug o Smart Insights - SAP Analytics Cloud
1. SMART Discovery med SAP Analytics Cloud
2. Karakteristisk for SAP Analytics Cloud: Smart Discovery
3. How to add smart insights to stories and analytics apps: SAP Analytics Cloud
4. How to run Smart Discovery on your stories: SAP Analytics Cloud
5. SAP Analytics Cloud - Intelligent Discovery
6. SAC Quick Demo Smart Insights Smart Discovery
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