- SAP Managed Tags
Enjoy reading this and all upcoming blogs 😊
Here is a short Sneak Preview about some of the feature which will be described in this blog. Of course the blog provides more than in the video. 😉
And now let's kickoff the blog.
Welcome to my new blog series on SAP Analytics Cloud (SAC) and its powerful live data access capabilities with SAP BW/4HANA, SAP S/4HANA, and SAP Datasphere! This series is dedicated to exploring the seamless integration your SAP live data sources, enabling real-time insights and fast, data-driven decision-making. The focus will be fully on SAC's features with the Optimized Design Experience.
Covered topics (will be enhanced)
As organizations strive for agility, having access to the freshest data directly within their analytics platform is crucial. With SAC's live connectivity, users can explore and analyze data from core SAP systems like SAP BW/4HANA, SAP S/4HANA, and SAP Datasphere without duplicating or moving data. This approach not only enhances data security and governance but also ensures that your insights are always aligned with the latest data in your SAP systems.
We’ll kick off this series by diving into some parts about the SAP BW live access within SAC (main focus in my demo is SAP BW/4HANA). Here, we’ll explore how SAC leverages the robust data structures and hierarchies in SAP BW while enabling a high-performance, optimized design experience that transforms how you interact with and visualize your data. As we move through the series, we'll look at each SAP data source individually, showcasing the unique features and benefits that SAC brings to each environment.
Whether you're a data analyst, a business intelligence professional, or a decision-maker, this series will help you unlock the full potential of your SAP ecosystem with live data capabilities in SAC. Join us as we explore
For those who are new to SAP Analytics Cloud, just a short description. SAP Analytics Cloud is a complete solution for analytics and planning that is designed to unlock the full potential of all your investments in mission-critical business applications and most valuable data sources.
Infuse trusted AI: Embrace the power of generative AI to automate reporting, discover hidden insights, and create and develop business plans with Joule copilot.
Deliver mission-critical analytics: Elevate BI capabilities and deliver industry-specific analytics with pre-built business content.
Transform enterprise planning: Enable collaborative planning by unifying financial, supply chain, and operational planning with a single solution.
Now let's turn back to the main topic - the live access to SAP BW/4HANA. SAP BW/4HANA is a powerful data warehousing solution that organizes and structures large amounts of business data. Through SAC’s Optimized Design Experience, you can interact with SAP BW live data in a high-performance environment that maintains all the familiar benefits of SAP BW—hierarchies, variables, and complex data models—without data replication. This real-time access provides business analysts and decision-makers with a continuous view of their operations and up-to-date insights.
Throughout this article, we’ll explore the essentials of configuring and working with live connections to SAP BW in SAC, focusing on how live data access streamlines workflows, enhances collaboration, and enables more agile decision-making. We’ll cover best practices, and key features that make SAC an ideal platform for analyzing SAP BW data.
Let’s dive into how SAC’s live connection to SAP BW empowers organizations to harness the full potential of their data, all within a single, unified analytics experience. I am going to share my personal SAC highlights with the community. We will start with a few basics and then I will dig directly into one of the greatest features of SAC - the "Live Access" itself to SAP BW/4HANA and SAP BW on HANA: no data replication, no data duplication, no data extraction – just live access. What are the reasons for selecting the live access? Let's have a look.
For those who wants to understand, whats the main difference is between the live connection and the data acquisition, the following overview is helpful for the start:
Anyhow, choosing live access with SAP Analytics Cloud (SAC) on top of SAP BW/4HANA offers significant advantages, bringing agility and efficiency to your analytics experience:
Plug-and-Play Integration: SAC seamlessly connects with SAP BW/4HANA in a plug-and-play setup. The configuration to set up this live access is well described in the SAP Help. This effortless integration means you can quickly leverage SAC’s powerful visualization and analytics features without complex setup, enabling your teams to get started with live data analysis right away.
a) Check the pre-requisites for the live connection in the SAP Analytics Cloud help:
https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/11b4e5ff76eb4747bc255...
b) Learn more about the live connection itself and the setup in the SAC Help:
https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bdf055159cbb4f36b26c9...
c) Check the Live Data Connection Overview Diagram to understand more about the connection:
https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/5b4dad4d97664c41ae63b...
d) If you are looking for a technical description how the live connectivity works, just check the SAP Analytics Cloud Connection Guide:
https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/2d7115b0e0aa4f78bfd9c06fdc1fe4f6/9b941b974b594a5897c7c...
e) SAP Notes you need to know (there are of course more and I will add them to this blog soon): If you want to know which new features are available for your SAP BW system, please check SAP Note 2715030 (https://me.sap.com/notes/2715030).In addition please have a look into SAP Note 2541557 (https://me.sap.com/notes/2541557). It contains all information's about the SAP Note Analyzer and the XML file with the notes, which "needs" to be imported into the SAP BW backend to get the best experience.
Reuse Your SAP BW Queries 1:1: By going live, SAC allows you to fully reuse your existing SAP BW queries, saving you from needing to rebuild reports or KPIs. This reuse ensures consistency across reports and speeds up deployment, making it simple to access and visualize the insights you already have and now in BW. Imagine you created all the content over the years. Now you only want to reuse all this and more just via plug and play and that is what you get with the live connection.
Preserve Your Investments: Live connectivity with SAC lets you preserve the valuable structures, hierarchies, authorizations, and reusable components like key figures and characteristic structures already established in your SAP BW system. SAC inherits these elements directly, leveraging years of investment in data modeling and governance to ensure accurate, trusted analytics.
Enhanced Security and Governance: Since SAC respects SAP BW’s authorization settings, you maintain the same robust security and governance controls over your data. This alignment keeps sensitive information secure, ensuring that the right people access the right insights at all times.
Real-Time Decision-Making: With live data connectivity, SAC brings SAP BW data to life by eliminating delays from data extraction and transformation. This real-time access means your analytics are always up-to-date, allowing teams to make faster, data-driven decisions that reflect the latest operational realities.
Consistent Data Governance Across Platforms: SAC’s live connection ensures that all data governance and compliance settings in SAP BW/4HANA—such as roles, authorizations, and data masking—are seamlessly applied to analytics. This means you can trust that data security policies set in BW automatically extend to SAC, without the need for additional configuration.
High Performance and Scalability: SAC’s Optimized Design Experience is built to handle large volumes of data efficiently, even as data models in SAP BW evolve. This performance boost not only enables smoother, faster data exploration but also ensures that SAC scales effortlessly alongside growing data demands.
Unified Analytics with Familiar Structures: SAC recognizes SAP BW’s key elements, such as predefined hierarchies, structures, and reusable elements like key figures and characteristic structures. This alignment means analysts and business users can navigate and interpret data in SAC using familiar structures, reducing learning curves and fostering user adoption.
Future-Proofed Analytics Environment: By leveraging SAC’s live access with SAP BW, organizations create a flexible analytics environment that supports future innovations. As SAP continues to enhance SAC and SAP BW, your analytics capabilities grow in tandem, positioning your organization to leverage new features, improvements, and integrations without significant rework.
Enhanced Collaboration: SAC’s cloud-based environment allows team members across locations to access live SAP BW data from anywhere, enabling real-time collaboration on dashboards and reports. This collaborative capability means insights are shared, discussed, and acted on swiftly, breaking down silos and driving a more connected, insight-driven culture.
By going live with SAP Analytics Cloud on top of SAP BW/4HANA, organizations can unify data accessibility, preserve prior investments, and harness real-time insights that drive agility and competitiveness. SAC transforms SAP BW data into actionable insights within a high-performance, secure, and user-friendly analytics platform, setting a solid foundation for the future of data-driven decision-making.
Let's summarize it up: In SAP Analytics Cloud, you can create "LIVE" models based on your SAP BW Queries, build stories based on those live models, and perform online analysis without data replication.
The first wow effect, will come fast. If you see the live connection running for the first time and that within a short timeframe (from the setup to the first live dashboard), if anything is ready to start your journey with SAC live on your SAP data.
Of course there are many blogs available regarding the live connection from SAP Analytics Cloud to e.g. SAP BW on HANA or SAP BW/4HANA (even my older blog series with the classic design). I would like to show you how this live access works by providing a few examples build with SAP Analytics Cloud.
As mentioned in the SAP Analytics Cloud help or other SAP Blog Posts, the internet browser connects directly with the SAP BW system behind the corporate firewall and no data is moved into the cloud.
So as you know know, one of the main reasons customers select SAP Analytics Cloud on SAP BW is the fact, that they can consume 1:1 the SAP BW queries with all their elements (e.g. structures, hierarchies, variables, variants, global key figures) including the underlying authorizations & roles. There is no need to change the SAP BW queries for special reporting purposes as we can leave them as is. This helps IT & Business Departments to consume all existing SAP BW content without changes – no data extraction, no data silos, just plug & play.
From the SAP BW Query to the SAP Analytics Cloud Live Model
First of all you need to have a SAP BW query with all relevant key figures (measures) and characteristics (dimensions). After setting up the live connection from SAP Analytics Cloud to SAP BW, all SAP BW queries can be accessed “directly” and a “live model"can be created in SAP Analytics Cloud based on a specific SAP BW query. This model can be used to build stories with nice visualizations. To run the dashboard and to access the data you need of course the authorization for SAP BW (user and password plus underlying roles in BW). As already mentioned this works plug & play.
Connecting a SAP BW Query with SAP Analytics Cloud in live mode
The following video shows the mentioned stages when connecting live to a SAP BW Query with SAP Analytics Cloud. Within a few minutes you can see the data from your SAP BW query live in SAP Analytics Cloud with all the advantages mentioned.
Linked Analysis
SAP Analytics Cloud allows to enable the "Linked Analysis" between different widgets used in your story. Linked analysis is one way you and your team can dynamically interact with your data. This feature enables you to create relationships between charts within a story so that when you filter or in drill down one chart, it causes actions to occur in one or more other related charts. This works with live data sources as well. The following video shows how this works with a live model in SAP Analytics Cloud based on a SAP BW Query.
How SAC deals with SAP BW Query variables & variants
SAP BW queries can contain variables. Variables are parameters of a query which has been created during the query design process and are filled with values when you execute the query. They serve as placeholders for characteristic values, hierarchies, hierarchy nodes, texts and formula elements. They can be processed in various ways and SAP Analytics Cloud can deal with them. Plus we go a step further – as we support variants.
You can save a variant for a BW query (e.g. Analysis Office) after you have filled the variable popup with values according to your requirements. A query variant is a query for which variable values have already been selected. And SAP Analytics Cloud can deal with those variants. This means that when you next open and display your SAP Analytics Cloud story in the browser, you can call the variant for the query. The following video shows this process.
Dynamic Calculations on-the-fly in SAC
If you worked with SAP Analytics Cloud already, you know that end users can create their own calculations (e.g. calculated measures) in a story. But it is also possible to create dynamic calculations within a table based on a live model with data from SAP BW. The following video shows how easy this dynamic calculations can be created.
Data Analyzer for Ad-hoc Analysis (open the SAP BW Query directly and start the action)
The Data Analyzer in SAP Analytics Cloud (SAC) is a powerful tool designed for ad-hoc analysis and deep data exploration, especially for users who need quick insights from complex data sources. It provides a simplified interface to directly access live data from SAP BW/4HANA, SAP S/4HANA, and SAP Datasphere without requiring predefined dashboards or reports. With intuitive drill-downs, filtering, and pivoting options, the Data Analyzer makes it easy to investigate data in detail, answer specific business questions on the fly, and uncover trends or outliers.
Ideal for analysts and decision-makers, the Data Analyzer maintains all existing SAP BW structures, hierarchies, and authorizations, ensuring users can trust the data's accuracy and governance while exploring it freely.
Working with SAP BW hierarchies
Nearly all businesses use hierarchies to classify their products, services, and even their organization. SAP BW users love to work with the hierarchies they know from SAP BW. And exactly here SAP Analytics Cloud brings value to those end users as it is possible to select and activate any hierarchy which belongs to a specific characteristic (dimension). Even if a BW hierarchy is activated in a BW query, SAP Analytics Cloud will simply show & use it within a table. The following video simply shows an easy example using a time hierarchy during story creation. In charts you can drill up and down and in tables you can open and close the hierarchy nodes. It’s simple!
Fully flexible & dynamic: Working with dimension and measure input controls
Use dimension and measure input controls for full end user flexibility in SAP Analytics Cloud. See in the following video how easy it is to exchange dimensions and measures coming from a SAP Analytics Cloud live model based on a SAP BW query.
This can be also used for KPI comparisons. In the following example I show daily sales data based on a SAP BW Live model in SAC. In this case I can compare the KPI's I wand to see.
Time series forecasting based on your SAP BW query data
Time series forecasting allows you make confident decisions on time series data by predicting future values based on the historical values. Time series data is data that contains a value over time, for instance revenue by month or call volume by week. In SAP Analytics Cloud you can easily create a Time Series Forecasting based on your live SAP BW data! The following video shows an easy example how this look like.
Powerful plug & play feature: SAP Analytics Cloud connects easily to SAP BW Queries which contains "two" structures
Structures are objects that you define in the BW Query design environment. A structure forms the basic framework of the axes in a table (rows or columns). It consists of structural components. We differentiate between key figure structures and characteristic structures. Structural components of key figure structures are always based on the key figure selections (basic key figures, restricted key figures, and calculated key figures). Characteristic structural components cannot contain key figure selections. The setup of the structure determines the sequence and number of key figures or characteristic values in the columns and rows of the query. You can also navigate through the structures in the executed query. Additionally you can also set filters for them. If you are using two structures (for example, a key figure structure in the columns and a characteristic structure in the rows), a table with fixed cell definitions is created.
One additional detail is important to know which . If your SAP BW query contains two structures, the cell editor becomes available. But what does this mean?
The cell definition is a useful functionality within a SAP BW Query which helps us to uniquely define each cell that is present at the intersection of two structures. The term cell for the function Defining Exception Cells should not be confused with the term cell in Microsoft Excel. The formulas or selection conditions that you define for a cell always take effect at the intersection between two structural components.
Cell-specific definitions allow you to define explicit formulas and selection conditions for cells as well as implicit cell definitions. This means that you can override implicitly created cell values. This function allows you to design much more detailed queries.
In addition, you can define cells that have no direct relationship to the structural components. These cells are not displayed and serve as containers for help selections or help formulas.
This all considered when having a SAP BW query with 2 structures which contains cells.
SAP Analytics Cloud shows its powerful capabilities, as its able to read and work with BW Queries using two structures easily. This shows how tight our integration between SAP Analytics Cloud and SAP BW works and in the following video you can see how easy it works. The video shows a BW query with a key figure structure in the columns and a characteristic structure in the rows. In addition the members of the characteristic structure are ordered in a folder/hierarchy structure which can be easily created via drag & drop during the query design. Let’s see how this works in the following video.
For those who are interested into this topic. There are many use cases for SAP BW Queries with two structures. One would be a YoY comparison with own calculations and cumulations (and I am not talking about the option to just drop a 0MONTH dimension into the data model which would not cover your own calculations and cell restrictions).
Here you can see an example how the cell editor in the SAP BW Query would look like.
And this can be easily consumed again 1:1 by SAP Analytics Cloud.
Blend your SAP BW Queries live (or blend them with your local data)
SAP Analytics Cloud allows data blending. In the next video you will see two charts in a SAP Analytics Cloud story. Each of the charts has a live data model based on a dedicated SAP BW query. The first query has only actuals data, while the second query has only budget data. In SAC you can blend those two lived models based on those two SAP BW queries directly in the story. Let's see how this works.
You can also blend a SAC model based on acquired data with a SAC model based on live data. For example data coming from a live model based on a SAP BW Query, while the other SAC model is based on local data coming from an MS Excel file.
Custom Hierarchies/Groups for SAP BW Live data models
This one is a really cool feature. Story designers want to organize members of different dimension groups. When working on a story, you can define custom hierarchies on BW dimensions. These hierarchies can be used in charts, tables, input controls, and filters. The definition of a new hierarchy always starts from the flat dimension values.
Custom ordering of measures in Tables based on a live connection
If you show tables based on SAP BW live models, often there is a need to change the order of measures. This feature can easily be accessed in the designer panel of a SAP Analytics Cloud Story.
Export Story based on SAP BW Live Data to PowerPoint (or PDF) using story filters (in realtime or as batch export)
Did you know that we have integrated the ability to export story content to Microsoft PowerPoint, allowing users to easily include stories in their presentations and streamline their workflow. Each exported story page will be one image on a PowerPoint slide. This feature has the same capabilities and limitations as exporting stories to PDF or Google Slides. But there is one interesting thing you should know about this feature – you can start a batch export by story filters (needs to be active). In the next example you can see, that I create a PowerPoint export and SAC should also consider my filters on the dimension distribution channel.
This is for the MS Office fans. Analyse your SAP BW live data directly in MS Excel and MS PowerPoint
The SAP Add-in for Microsoft Excel and the SAC Add-in for Microsoft PowerPoint bring SAP data and analytics directly into Microsoft Office applications, enhancing productivity and decision-making capabilities within familiar tools.
The SAP Add-in for Excel is designed for users to access and interact with SAP data directly within Excel, supporting tasks like data retrieval, manipulation, and real-time updates. This add-in is particularly useful for departments like finance and logistics, where users need to work with SAP data for planning, reporting, and analysis without leaving Excel. The following video shows live data from SAP BW/4HANA and SAP Datasphere in the Excel workbook (running in the browser version of MS Excel).
The SAC Add-in for PowerPoint connects SAP Analytics Cloud insights with PowerPoint, allowing users to embed live data visualizations, reports, and dashboards into presentations. This integration is valuable for business users who present data-driven insights, as it keeps presentations up-to-date with real-time data from SAC. Users can share dynamic, interactive insights in their presentations, making it ideal for leadership briefings, sales pitches, and board meetings where timely data is crucial.
Linking SAP BW Variables in SAC
If your story has e.g. two models based on SAP BW queries which contains variables, you can link the SAP BW variables so that changing one variable in a model will update the data from the other model as well. In the following video we have data from two SAP BW queries, and you will see how this nice feature works.
Display of images in tables based on SAP BW XXL attributes information
You noticed this feature maybe also in the SAP note 27150230 as “Display of images in table based on BW XXL attributes”: https://launchpad.support.sap.com/#/notes/2715030
Let's have a look how this look like. It is possible to logically assign XXL attributes to a BW characteristic InfoObject. Based on the MIME type selected, the system can interpret the XXL attribute as an audio file, a video file, text, or an image. XXL attributes first must be defined as an XXL InfoObject type before being available as XXL attributes for other characteristics.
You can make use of the information’s stored in an XXL attribute and use them in SAC tables – to be clearer: in my example I want to show product pictures stored in an XXL attribute which is assigned to a BW characteristic InfoObject (here product). I will not show all relevant steps which are needed but you simply need to create an XXL attribute with the corresponding Data & Mime Type.
Next you must assign it to the relevant BW characteristic InfoObject. Switch to the master data maintenance view for your BW characteristic InfoObject. You can now upload your pictures to the relevant characteristic values.
In SAP Analytics Cloud you just need to add a table to your story, activate the XXL attribute and thats it. You will immediately see the pictures directly from SAP BW/4HANA. Start exploring your data, create some filters and the view will change. Fully dynamic. Of course, there are other options instead of uploading pictures, but this is the easiest and fastest way.
If you are interested how to achieve this with SAP Datasphere, just have a look into this blog:
https://community.sap.com/t5/technology-blogs-by-sap/how-to-visualize-images-in-sap-analytics-cloud-...
Generic Hyperlink Example: Using hyperlink to SAP S/4HANA to provide more context to your end users
When creating a story in SAP Analytics Cloud, you may want to hyperlink to another story, a specific page in your story, or to a website. This can be a great way to provide more context to the message you’re trying to convey. So far so good but did you know that you can apply selected dimension as filter when connecting to a page within your story or a different story within your SAP Analytics Cloud environment?
And then you have all dimension values available to create a fully dynamic and generic URL to external applications/pages and can send the dimension values as parameters.
This would also work with SAP S/4HANA, if you want to jump with a sales order number in SAP Analytics Cloud into a transaction in SAP S/4HANA. Let's see how this would look like.
Bookmark the current state of a story in SAP Analytics Cloud and send it to your peers
You can create bookmarks in SAP Analytics Cloud to save different states of a story.
For example, you have several pages in your story that have filters, input controls, or prompts applied to them. You don't want to spend time resetting all of them each time you want to see a different scenario. You would like to open the story, see one scenario, and then quickly switch to another scenario. You can even create global bookmarks so that anyone who can view the story can also see the different scenarios.
This works also well, when using SAP BW live models.
Explore SAC and check the context menu and all the options. You will find several features which are really helpful.
One example are in-cell charts. Just click on a measure and in the context menu you will see this option.
Just click on one of the bars and on the right side you can find in the designer the option to show variance pins.
And you will see the change immediately.
As I wrote. Explore the options in the context menu. You will find many nice features inside.
Variables, Variable Popup, Variants & Filtering
I mentioned already the variants which. If you save them in SAC you can see them for example in Analysis Office (and the other way round). You can create a user variant which is only visible to you, or you can create a global variant which is visible for all SAP BW users who opens this query. If you have a variable popup screen with many variables inside, it is a nice way to just bookmark your selected filter values easily.
It works plug & play and there is no need to change the model in SAC.
Another nice feature which end users like is the possibility to copy & paste filter values from their clipboard into the variable popup. Both story viewers and designers can now make changes to story and page filter selections faster, especially when working with a large list of values. You can now simply copy and paste filter values into the input control to either overwrite or append the existing selection when working with BW models.
If you have a SAC live model which is based on a SAP BW query you can see that variables can be easily reused. And if you save the combination of filter values in the variable popup in Analysis Office, you can reuse them in SAC. There is nothing to do - just open your story and it will work. But did you know that you can also set variable filters as page filters in the SAC story for your BW query variables?
Flexible date handling in SAP Analytics Cloud with BW Live Connection
Wouldn’t it be nice to have an easy option to implement date comparisons and flexible date filters with less effort in SAC based on the BW live connection? Maybe even to allow that the story creators & end users can set up this by themselves? Or a feature that allows them to select the key date for a story and have all charts and widgets adjust accordingly? This was delivered with the Flexible date handling in SAP Analytics Cloud by using the BW Live Connection.
The effect is the same like in the classic design and you can see how it works in the following video.
Anyhow this feature has been improved so I will extend this part later a little bit more.
Using dynamic text to access the content from the SAP BW Query variables
The dynamic text feature is a very powerful feature. It allows you to put any content from filters, input controls, system information and of course BW Query variable input/content wherever you want as text.
Please note that you can make use of dynamic texts in the headers of charts and tables as well.
In my example I want to filter countries in a variable popup from the BW Query and it should be placed in the title of the SAC story.
Now you can access a lot of information delivered by the SAC story or the SAP BW Query.
I will select the variable from SAP BW which has been created on the dimension/characteristic "Country". Whatever I enter in the BW Query variable popup will be placed as dynamic at the selected place.
You can close the window using "Create" and a place holder has been inserted at the location where you want to see your dynamic text. Now you can refresh your SAC story to see the SAP BW query variable prompt. In my example I select Germany and France as filter values.
If you now click on "Set" the values will be passed to SAP BW and the story will show the data for Germany and France. And the placeholder which has been created for the dynamic text, will show the filtered countries.
Support for tuple filters (Filter data that is organized in multiple dimensions)
SAP Analytics Cloud supports tuple filters in SAP BW queries. This includes filtering with multiple dimensions in addition to using the “AND” and “OR” operators. You can create filters by selecting multiple data points in the widget.
Tuple Filters in SAP Analytics Cloud (SAC) offer powerful data filtering capabilities, enabling users to create precise data views by filtering on specific intersections of dimensions. This flexibility is especially beneficial in complex reporting scenarios where standard single-dimension filters would be insufficient.
Detailed Overview of Tuple Filters
Custom Combination Filtering: Tuple filters operate by defining conditions across two or more dimensions. For example, if you have data for “Region,” “Product Category,” and “Quarter,” a tuple filter allows you to specify conditions like showing data for "Electronics in North America for Q1 and Q2." This goes beyond typical filters by creating a subset based on exact intersections.
Nested Condition Support: Tuple filters support the creation of nested conditions, allowing users to add multiple dimension values and set specific rules that apply only to those values. For instance, you could filter a report to show “Q1 and Q2 data for Electronics in North America, but only for stores with revenues above $1 million.”
Simplifies Multi-Dimensional Data Views: Tuple filters help simplify data exploration by providing an immediate way to drill down into highly relevant data intersections. Users don’t need to apply multiple individual filters across dimensions, which can become complicated in large datasets.
Use Cases for Tuple Filters in SAP Analytics Cloud
Sales Performance by Region and Product Category
- Scenario: A sales manager wants to review sales performance data but only for certain product categories in specific regions and time periods.
- Solution: Using tuple filters, the manager can select intersections like "Sales data for Consumer Electronics in North America and Europe for Q3 and Q4," providing an at-a-glance view of how these products performed in those regions and quarters.
Financial Analysis for Specific Departments and Time Frames
- Scenario: A financial analyst needs to review expenses across departments but only for select periods and specific cost centers.
- Solution: By using tuple filters, the analyst can isolate data intersections like "Q1 and Q2 expenses for the Marketing and R&D departments in the North American division," allowing focused financial analysis on particular budget segments without having to export and manually filter data.
Product Launch Impact Analysis by Market and Time Period
- Scenario: A product manager wants to analyze the impact of a recent product launch in target markets and specific months.
- Solution: Tuple filters allow the manager to examine "sales of the newly launched product in Europe and Asia for January and February," helping evaluate initial launch success without unrelated data cluttering the report.
Retail Inventory Management by Store and Category
- Scenario: A retail chain’s inventory team needs to monitor stock levels for specific categories within top-performing stores.
- Solution: Tuple filters help the team drill down into "inventory data for Clothing and Accessories in high-revenue stores in the South and East regions," assisting with inventory planning and replenishment decisions for prioritized locations.
HR Analytics for Workforce Insights by Department and Location
- Scenario: An HR team is conducting an analysis of employee retention rates for certain departments across global locations.
- Solution: Tuple filters enable the team to focus on "retention rates in the Sales and Engineering departments for North America and Europe," allowing them to assess and address potential issues specific to these areas.
What about "Navigation Attributes" & "Display Attributes" from SAP BW?
What is the difference between "Display Attributes" and "Navigation Attributes"? Display attributes can only be used for display purpose, which means that they will only act as a detail of a characteristic.
Navigation attributes are very different. They are attributes which can be used like any other characteristic in SAP BW. If we declare an attribute of a characteristic as navigation attribute, we can do functions like filtering or drilldown on this attribute like we do on any other characteristic.
How SAC deals with this different attribute types?
********* Display Attributes *********
A characteristic InfoObject in SAP BW can have display attributes which contains additional information’s. For example, you can have the customer number as a characteristic and e.g. add the customer location, customer segment in the backend to this characteristic as attributes. You can usually activate attributes in the SAP BW query, and they will be shown – e.g. in SAP Analysis Office. It is also possible to activate these attributes in SAP Analytic Cloud as well.
In the following screenshots you can see how I show/hide the display attributes colour and product group for the characteristic product. This can be done by end user during the navigation or by the story creator if it should be activated already.
End User:
Right click on the dimension and select "Show/ide" and then "Properties".
Select the attributes and klick on "OK".
Now you can see the display attributes coming from SAP BW in your table.
Story creator:
Story designers can activate the attributes in a similar way. The only difference is that they do it directly in the designer.
********* Navigation Attributes *********
On SAP BW side the navigation attributes need to be assigned to the corresponding characteristic and must be declared as "Navigation Attributes":
ou can now activate them e.g. in a Composite Provider and they will be available in the SAP BW Query.
Hint: It's easy to identify “Navigation Attributes”. You can see it in the technical name of the relevant object. They always start with the BW characteristic to which you have assigned the navigation attribute followed by 2 underscore (“__”) and then the technical name of the attribute itself.
In my example ZSH_PR__0BH_CR and ZSH_PR__0BH_PG.
In SAC you can see them in the BW Live model among all the other dimensions.
That's what SAP BW customers would expect. Remember: Navigation attributes are attributes which can be used like any other characteristic in SAP BW. If we declare an attribute of a characteristic as navigation attribute, we can do functions like filtering or drilldown on this attribute like we do on any other characteristic. And that's what we can do now in the SAC story:
Report-Report Interface Support in SAP Analytics Cloud
This is one of the SAP Analytics Cloud features I really like. We enhanced the data navigation by integrating the Report-Report Interface (RRI), a feature traditionally available in SAP BW systems. RRI enables users to seamlessly transition between related reports, facilitating deeper data exploration and analysis.
Integration of RRI in SAP Analytics Cloud:
Functionality: RRI allows users to define "jump targets," enabling navigation from a source report to a target report or external web address. This is particularly useful for drilling down from summary reports to detailed analyses.
Implementation: To utilize RRI within SAC, configurations are made in the SAP BW backend using transaction RSBBS. Here, sender and receiver assignments are established, defining the source and target reports.
Usage in SAC: Once configured, users can access jump targets directly within SAC's Data Analyzer or stories. By right-clicking on a data point, the "Jump To" option appears, listing available targets for seamless navigation.
Benefits of RRI in SAC:
Enhanced Data Exploration: Users can move between reports without losing context, enabling comprehensive analysis across different data perspectives.
Improved Efficiency: RRI reduces the need to manually locate related reports, streamlining workflows and saving time.
Consistent User Experience: Integrating RRI into SAC provides a unified platform for data analysis, maintaining consistency across SAP tools.
I will show an easy example (though there are many many possibilities). In my case I have created a jump target in Report-Report Interface on the SAP BW backend side.
This screenshot shows that there is an entry for my SAP BW query. All tools which uses this SAP BW Query (and support the Report-Report Interface) will make use of the entry (e.g. SAP Analytics Cloud, Analysis Office).
You can make really specific assignments. Either you leave it fully generic, or you can define anything you want by using some specific options. In the generic mode the Report-Report Interface will try to identify and pass the filters to the right dimensions (if technical names are used for the SAP BW InfoObjects of course).
Anyhow my example will be easy. I will jump from a "high-level" SAP BW Query showing the cumulated sales values to a different SAP BW Query which shows "detailed" sales values for the specifc days. The Report-Report Interface notice that both queries use the same SAP BW InfoObjects (e.g. customer, order number with the relevant ID's) and passes the values from one query to another. As we are fully generic, we can jump from any dimension to the jump target.
In easy words: The job of the Report-Report Interface is nothing more that taking the dimension values (as filters) from a "sender" SAP BW Query and passes it to a "jump target" SAP BW Query. But wait, how this works? We use live models in SAC? That's the easy part. This works plug and play. All SAC live models which uses a specific SAP BW Query with specific Report-Report Interface assignments, will use this automatically. There is nothing to do on your side. The jump targets are visible in the context menu of SAP Analytics Cloud.
If you don't make any specific settings about the jump target, the Data Analyzer in SAP Analytics Cloud will open. Let's watch an example.
Let SAC track your KPIs: Send “Data Change Insights” based on SAP BW/4HANA live data via mail or to the home screen!
Did you know that you can track your KPI's from any source (including SAP BW) with SAP Analytics Cloud and can be notified via mail (including a link and a PDF), mobile app and the SAC homescreen? If not, just read my blog:
https://community.sap.com/t5/technology-blogs-by-sap/let-sac-track-your-kpis-send-data-change-insigh...
I have used the “Data Change Insights” feature in SAC and created a demo based on a live connection to SAP BW/4HANA (Note: though I am using SAP BW/4HANA as data source, this should also work with SAP BW on HANA or SAP S/4HANA as live data source).
The Data Change Insights feature helps you discover chart-level data changes that are important and relevant to you when you aren’t opening and using analytic applications. It needs to be enabled by application designers, so that application users can set daily, weekly or also monthly subscriptions and configure value ranges to trigger data change insights.
Read the blog with a step-by-step guide.
You can also watch this video, to see the result:
What-If-Simulation in a SAC Story based on a SAC Live Model (e.g. SAP BW/4HANA)
I have often received the question if it is possible to create a "What-If-Simulation" in a SAC Story based on a SAC Live Model (in my example SAP BW/4HANA). As a result the following SAP Blog is available:
https://community.sap.com/t5/technology-blogs-by-sap/what-if-simulation-in-a-sac-story-based-on-a-sa...
Just follow the steps mentioned in the blog and you can to it as well.
You can watch also this video which shows the result in SAP Analytics Cloud:
I have added the same demo also in my new SAP Analytics Cloud live demo on SAP BW/4HANA using the Optimized Design Experience.
Data Point Commenting with the live connection to SAP BW on HANA and SAP BW/4HANA
As of QRC2 2023 we introduced a significant enhancement in SAP Analytics Cloud (SAC): the ability to add comments to data sourced via live connections from SAP BW systems. This feature leverages existing commenting functionalities in SAP BW/4HANA, which has been extended to SAP BW 7.50 on HANA, allowing users to create, view, edit, and delete comments directly within SAC. Importantly, all comments are stored within the SAP BW systems, ensuring that no commenting data resides in the cloud - a crucial consideration for industries with stringent data security requirements, such as defense, banking, and the public sector.
The integration also ensures compatibility with other SAP front-end tools; comments made in SAC are accessible and editable in SAP Analysis for Microsoft Office, and vice versa. Users can interact with comments through data point comments displayed in tables, dedicated comment widgets, or via the JavaScript API.
Overall, this enhancement enriches collaborative analytics and planning processes within SAC by seamlessly integrating commenting capabilities across SAP's ecosystem. For more details (including pre-requisites) visit the following blog: https://community.sap.com/t5/technology-blogs-by-sap/comments-on-bw-bpc-live-connections-in-sap-anal...
Let's see the this again in the my main demo:
What about Version mapping (e.g. with value type from SAP BW)
From SAC planning models you know, that there are different categories — money you actually made (Actual), money you’re going to make (Forecast), and money you are going to spend (Budget). SAP Analytics Cloud allows you to choose the granularity of each of these categories. And exactly this is also possible if you have the version or the value type in your SAP BW query. You can manually map the characteristic values coming from the SAP BW query – e.g. from the value type to the corresponding dimension values in SAP. This is one of the tasks you can perform directly in the SAP Analytics Cloud model.
This will open the door for some nice features you can use within SAP Analytics Cloud - e.g. Actual vs Budget comparisons, Variances incl IBCS. Let's see how this look like if you finished the version mapping in the SAP Analytics Cloud live model:
Just try this on your own and look what else can be done with the version when accessing a SAP BW Query live with SAP Analytics Cloud.
Show your live data on Geo Maps
In SAP Analytics Cloud you can show your live data on Geo Maps. There are several blogs which covers this already, as this is already supported for a long time. There is also a master SAP note you can check for further details: https://apps.support.sap.com/sap/support/knowledge/en/2433853
Please note that also linked analysis and drill down in hierarchies works (choropleth Layers). Let's have a look into SAP Analytics Cloud again:
This is all for the moment and I hope you like it. Stay tuned for updates in this blog and for the next parts with SAP Datasphere and SAP S/4HANA.
Wish you all the best.
Adem
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