This blog covers some of the latest features and enhancements in SAP Analytics Cloud and SAP Digital Boardroom release 2020.12. Please note that the Analytics Cloud Help documentation is updated at the same time as the upgrade to this release, so the links here may not yet reflect what is described below until after the upgrade is complete.
Upgrade your SAP Analytics Cloud agent to the latest agent version 1.0.277 to take advantage of all the data acquisition types!
If you haven’t upgraded yet, here are the data acquisition minimum requirements:
- Version 1.0.75 for SAP ERP / SQL databases
- Version 1.0.235 for SAP HANA view
- Version 1.0.91 for SAP Universe (UNX)
- Version 1.0.233 for SAP Business Warehouse (BW)
- Version 1.0.75 for all other data source types
For more information, see System Requirements and Technical Prerequisites.
Highlights of this release:
- Data Visualization: String Functions in Calculated Dimensions
- Data Integration: New Data Preparation Experience
- Data Integration: Default Data Mappings Inherited from SQL Source
- Data Integration: Tunnel Connection Type
- Mobile: Search to Insight on iOS for iPhone and iPad
- Analytics Designer: Create an Analytic Application Using Datasets of SAP Data Warehouse Cloud
- Analytics Designer: Create an Analytic Application Starting in SAP Data Warehouse Cloud
- Analytics Designer: Page Book Widget
- Analytics Designer: Variable Parameters to Open an Application URL
- Add-in for Microsoft Office: Microsoft Excel Integration
Great news! We have enhanced the following new string functions in calculated dimensions.
- CONCAT: You can now use the CONCAT function to combine two strings into one string dimension. An example would be if you wanted to combine the dimensions, first name and last name, into a single dimension.
- REPLACE: You can now use REPLACE function to replace characters specified by location in a given text string with another text string. For example, if you want to replace a certain country with a prescribed value, you can use the REPLACE function to achieve this.
- LOWERCASE and UPPERCASE: You can now use LOWERCASE and UPPERCASE functions to convert a text string to all LOWER and UPPER cases.
These enhancements will provide you with more flexibility and ease when editing and creating stories.
We understand that the data preparation process can be quite time-consuming and complex. This is why we are excited to introduce a new, smarter data preparation experience that was designed to add ease and flexibility when working with your data in SAP Analytics Cloud.
- Wrangling Public Datasets
You can now quickly analyze and visualize public datasets in stories. Features include:
- Cleanse public datasets
- Directly consume public datasets in stories: Analyzing data has never been easier! Simply upload the data in your Dataset and directly analyze it in a story. Datasets are entities that are ready to be analyzed from the get-go: The dataset creation step includes an automatic inference of which columns are dimensions and which are measures. Users can always adjust those by editing the Dataset.
Reminder: the upload thresholds for Datasets are 1B cells, 1000 columns, 5000 characters in a cell.
For the security measures on datasets:
- Object security of Datasets will be maintained in stories.
- If a user has view rights on the dataset, they can see the data, but not change it.
- Users with edit rights will be able to open a Dataset and use all of the wrangling capabilities.
- If a public dataset is used in a story, any user with at least view rights on the dataset will be able to see it in view mode directly in the story. This new feature provides users with the confidence when working with their data.
- Embedded Datasets in Stories
We are introducing a complete self-service analytical experience that will bring you closer to data manipulation and the augmented analytic capabilities of your stories. When loading data in a story, users will now create an embedded dataset. The biggest benefit is the near-instant transition between the story layout and the wrangling area, making any adjustment to the data a simple click away. For those fans who are a fan of Excel, you will also be able to drag and drop their data into the homepage to get start analyzing it right away. In case you are still looking for an environment you are still familiar with, there is an option to start wrangling with the basic data preparation experience.
- Model and Column Overview
Next, we have simplified the modeling experience by introducing a new right-hand side panel that will provide a summarize representation of your model including your dimensions, measures, and descriptions. Here are the actions that will be directly available from panel:
- Change from dimension to measure and vice-versa via the drag and drop or menu
- Rename and delete objects
- Shortcuts to geo-enrich dimensions
- Create hierarchies
- Check errors
There is also the ability to view all columns of the dataset, even those not part of the model, by switching to the column view. Note that if columns are not part of the model, they will simply not appear when selecting dimensions or measures to create charts, or any story widget.
- Data Types and Statistical Types
In SAP Analytics Cloud, there will be new data types in each column. If a value doesn’t match the data type, the value will be flagged and will not be visible in the story. However, these errors will not block the move to story view nor will delete rows. Here is a list of the different column types:
- Date and time
In addition, columns will also contain a statistical type, which can be edited.
- Working with a Sample
With this new experience, you are still working on a 2000 row sample when wrangling. You also have the option to validate all the data outside the sample. Warnings will be raised to the user:
- If the data in a column does not fit corresponding datatype
- If an ID has multiple descriptions
All errors are only warnings, meaning that users can always proceed to work with that dataset. In this case, cells with issues will be cleared but rows will not be deleted.
- Transformations, Unpivot
All existing transformations are available also on Datasets. These transformations include concatenate, split, extract, replace, change, and unpivot. In addition to these transformations, Filter is a new function that will be available as a transformation. It will allow users to specify which values to filter out, even if they are not part of the sample.
Note, that unpivot can only be run on a single column header, and if you want to be able to unpivot a dataset with multiple headers, you will have to move to the basic data preparation experience to have access to this functionality.
- Custom Transformations
Next, SAP Analytics Cloud will contain a variety of data manipulation functions enabling data analysts to write custom transformations. A particular focus was set on providing the best development experience when writing a new expression. Imagine being able to write the custom transformation without leaving the keyboard. That was the challenge and in order to address it, here are some of the features that were brought into the editor:
- Typeahead of column, function, keyword names
- Function stub automatically displayed
- Easy navigation across function arguments
- Copy/Paste of expressions
- Clear troubleshooting experience
Custom transformations are based on a new, powerful language, developed in-house:
- Functions are divided in the following categories: Numeric, String, Date and Time, Spatial, Others
- A total of 50 functions are available, further superseding existing capabilities. Notable additions: timeDiff(), Distance(), element() etc..
- Outputs are now named: [NewTown]=“Roma” creates a new column with “Roma” as constant value
If needed, transformations can be edited from the transform log for further adjustments, thus matching the realities of everyday developments.
- Semantic Enrichments
For the drilling experience in charts across dimensions, users can create level-based hierarchies. This means:
- Levels are defined by dimensions
- Hierarchies are declared objects in models
- Dimensions can only be used in one hierarchy
- Columns can be ordered together in the grid
To map data points, users can geo-enrich existing dimensions through a variety of entry points, such as the toolbar and dimension menu. A big improvement is that an associated hierarchy can be created in the model, which users can use to build charts. Locations that have errors will not be displayed but will also not prevent the enrichment nor delete rows in the dataset.
- Reimport Data for Dataset
This new feature introduces the ability for users to update data inside a dataset. For any local dataset, whether a public dataset or embedded dataset in a story, users can now re-acquire the data from the original source to fully replace the contents of the dataset. The columns of the dataset will automatically be matched to the newly acquired ones. In cases where there are structural differences with the newly acquired data, the process will be cancelled. Lastly, regarding files, users will need to specify the location of the new file in order for all other sources queries to be automatically re-executed.
- Invoking Basic Data Preparation Option
Lastly, users can now re-initialize the wrangling session in the classic workflow without having to re-acquire data. When doing this, a warning sign will inform the user that all work will be lost. Basic data preparation can only be opened when the column count of the Dataset is less than 100 columns and has less than 100m cells total for non-file sources.
Benefits of using the Basic Data Preparation includes be able to:
- Append data to an existing embedded dataset
- Map a new upload into an existing dataset
- Acquire data coming from Dow Jones
- Use multi-headers when doing unpivot
- Use Smart Insight on variance chart
- Build a parent-child hierarchy
- Support of cross-calculations on tables and charts (just like remote models, universal models)
When acquiring SQL data, default data mappings are now inherited from the source. The data type definition is directly passed through from the SQL source, and not inferred. This feature saves you from having to recreate the metadata in the wrangling view, saving you time and reducing any possible errors.
Would you like to be able to share your business findings and insights with your external stakeholders, without giving them VPN rights? SAP Analytics Cloud administrators will now be able to create connections using the Tunnel connection type. This connection type will allow users outside your corporate network to connect live to your data, without giving them VPN rights. The Tunnel connection can be created to an on-premise remote source through the SAP Cloud Connector. These sources include HANA, BW, and S4HANA.
Are you ready to find the answers you need no matter where or when you are working? You will now be able to extract insights with just a few taps using the new Search to Insight capability on the SAP Analytics Cloud Mobile iOS app available on iPhone and iPad. This new feature is supported for acquired and live models based on Prompts available for acquired/live SAP HANA, SAP S/4HANA, SAP BW.
Please Note: Currently, Search to Insight on Mobile does not support changing variable values and uses the default set model parameter values to run the query. If no variables are set with default values, then all results are returned. Setting chart level variables is also not supported.
Within SAP Analytics Cloud, application designers can now create analytic applications by using datasets from SAP Data Warehouse Cloud. By using the “Select Model” dialog, the application designer can choose a configured connection, space, and dataset for the model-based widgets. This new enhancement will increase the scope of the data you can utilize when designing your analytic applications.
Application designers will now also be able to create an analytic application directly in SAP Data Warehouse Cloud. There are two methods application designers can follow to create an analytic application in Data Warehouse Cloud:
- Select Data Warehouse space and then select Analytic Application
- Select Analytics Cloud space and then select Analytic application
Using either of these options, the application designer will then navigate to SAP Analytics Cloud, where you can choose a configured connection, space, and dataset for the model-based widgets. This new enhancement will increase the scope of the data you can utilize when creating your analytic applications.
In your mobile device, you can now use the Page Book widget to group the application contents by different pages. You can use the swipe gesture to navigate from one page to another. The Page Book widget was designed to make it much easier to navigate through your analytic applications on your mobile device.
Let’s speed things up a bit! Let’s take a look at an enhancement that will accelerate your analytic application’s start up performance. Users can now set the variable value through the application URL parameters. For analytic applications, setting variables via the application URL parameter can avoid the double round trip of comparing setting variables in onInit event.
Add-in for Microsoft Office
We are excited to announce that you can now integrate Microsoft Excel with SAP Analytics Cloud. With this new integration, we are combining the best of the Microsoft Excel interface with the planning and analytic benefits of SAP Analytics Cloud. This makes it even easier to analyze your plans, simulate future outcomes, and take effective business actions. Here are some of the exciting features you can utilize with this new integration:
- Report on SAP Analytics Cloud models and write back data into different versions: You can publish different versions of your data and revert them in case you would like to discard your changes.
- Pivoting and filter features: You can use pivoting and filter features within the highly interactive table to easily create your ad hoc reports.
- Add any calculations and use formulas to easily create added value.
- Create Hierarchies and return Subtotals in your database
If you want to use this integration, please ensure you meet the following prerequisites:
- Have an SAP Analytics Cloud tenant
- SAP Analytics Cloud deployment on Cloud Foundry
- Have a Data-acquired in SAP Analytics Cloud models
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