6.5 Discussing Augmented Analytics Flashcards
SAC ML features (6)
- Predictive forecast
- Predictive scenarios
- smart grouping
- smart discovery
- smart insight
- search to insight
What predictive features are supported on acquired data?
- time series forecasting
- search to insight
- Smart grouping
- smart insight
- smart predict
- smart discovery
On acquired data, Smart predict is support only for (2):
-datasets
-planning models
NOT analytics models
What predictive features are supported on live data?
- time series forecasting
- search to insight
- Smart grouping
- smart insight
- smart predict
What predictive features are supported on acquired data but not live data?
Smart Discover
search to insight * doesn’t support which live connections
- SAP HANA Cloud
- SAP Data Warehouse Cloud
smart insights ** for live data are only supported for
S4HANA on prem
smart predict ** for live data are only supported for source
S4HANA on prem
What is Predictive Forecast
uses historical data to predict values
What algorithms does Predictive Forecast provide to choose from (4)
- automatic
- linear regression
- triple exponential smoothing
- add additional inputs
Features of Time Series Forecasting (4)
- project expected values in future time periods
- validate quality w/ confidence internal, hindcast and quality indicators
- include additions factors (eg weather) to simulate values
- creates trend charts and line charts
What is Smart Grouping
- creates segments of data (clusters) across several measures
- recommends # of groups based on your data
What is Smart Discovery
- run on data sets to analyze data and generate a story
What tabs are included in Smart Discovery Stories
- overview
- key influencers
- unexpected values
- simulations
how does Smart Discovery - Core KPIs helps understand business drivers behind your KPIs (4)
- classification and regression techniques
- explore hidden structures and relationships
- intuitive charts
- natural language
Smart Discovery - simulation features (3)
- see impact on KPI or value based on historical data
- experiment to see how particular dimensions/kpis will impact the outcomes
- add smart text explinations for visuals
Because SAC runs on HANA, HANA’s core predictive features are available. What does this include? (2)
- Automated Predictive Library (APL)
- Predictive Analysis Library (PAL)
What do you need to chose to form the context for Smart Discover (2)
- Target (measure/dim you want to know more about)
- Entity (dims you want to explore in relation to the target, and level of aggregation of data for analysis). You can an include specific members of dims
What is on the Smart Discovery Overview page? (3)
- visuals to summarize target dim in relation to entity, has 2 parts:
- one half gives summary of data
- second half has visuals
What is on the Smart Discovery Key Influencers page? (5)
- ranks up to 10 dims/measures that impact the target
- each has chart to show relationship w/ target
- summary of the takeaway from these visualiztions
- each chart has insight quality checkbox (eg confidence)
- measures and dims are aggregated at level of Entity
What is on the Smart Discovery Unexpected Values page? (5)
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