There are many reporting options that also include business intelligence. We have examined and compared the two market leaders: SAP's mothership in the field of analytics, the "SAP Analytics Cloud" vs. the Microsoft hero "Power BI". In the following article, you will find all the important information to help you decide which BI tool is best for you.
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Table of contents
1. What is business intelligence?
Business intelligence tools are used to prepare data and present it clearly so that decision-relevant insights can be gained from the information. In a first step, data from various sources is collected, merged and prepared in a user-friendly way. Subsequently, BI tools support data analysis and allow interactive visualizations. The analysis is facilitated by the use of artificial intelligence, for example. In addition, BI tools help to present analysis data in a clear and easily understandable form. The information gained through BI improves both strategic and tactical decision-making and helps to optimize business processes.
2. What is Power BI?
Power BI was launched by Microsoft in 2015 for data visualization and preparation. Typically, data models and reports are created on the Power BI desktop, which must be installed on the local computer. The reports are then consumed in the cloud-based "Power BI Service". It is also possible to customize reports and collaborate with colleagues or in teams.
3. What is the SAP Analytics Cloud (SAC)?
The SAP Analytics Cloud (or SAC) is a solution launched by software manufacturer SAP in 2015. SAC offers the core functions of business intelligence, predictive analytics, planning and application development in a fully integrated solution. As its name suggests, it is a Cloud product that is used as "software as a service" in the browser.
4. SAP Analytics Cloud vs Power BI in direct comparison
Microsoft Power BI (primarily based on MS Office or on the functions included in MS Office 365) is a self-service BI solution that is often requested by individual specialist departments. The SAP Analytics Cloud (SAC)on the other hand is usually requested by IT.
By means of practical evaluation projects, s-peers AG has conducted a meaningful comparison between Microsoft Power BI vs. SAC. One focus of the evaluation was to perform a functional trial with a system environment in the SAP backend (primarily SAP BW data sources). In an extended sense, the system environment also included the analytics engine of SAP ERP systems (ECC 6.0 or S/4 HANA). In the following, we summarize the most important results of our evaluation of SAC vs. Power BI for you.
Microsoft Power BI, as well as the SAP Analytics Cloud (SAC), each offer the function of combining infrastructure and security of on-premise data with cloud data. There are basically two different types of connectivity:
Live connection:
During the live connection, models are created from different data sources from on-premise or cloud systems. Stories and reports are then created on this basis. Online analyses are performed without data replication - i.e., no data is moved to the cloud. This applies equally to Power BI and the SAP Analytics Cloud.
Data importing:
With this type of connection, the data is imported (i.e. loaded) from the various source systems into the respective solution. From there, the imported data can be used to carry out analytical processes. In the case of SAP Analytics Cloud, the data is imported or copied into SAC's own in-memory database (SAP 4HANA). With Microsoft, the data is imported into Power BI's own SQL database.
As part of our evaluation, the respective data connections for the SAP BW, SAP 4HANA, Excel/CSV and Oracle database systems were tested.
We concluded the following:
- With a BW Live Connection (BW Live) in a Power BI story, only a single connection can be used. Additional connectivity is not possible.
- With BW Live, only one query can be used - after that, no further BW queries can be built into the same Power BI story.
- Within the SAP Analytics Cloud, non-SAP databases can only be connected via BO universes live or a via third-party software (APOS Live Data Gateway).
SAC is particularly suitable for data connections to SAP products such as the SAP Business Warehouse (BW), the SAP HANA database or the ERP system SAP S/4HANA. Power BI, on the other hand, comes up trumps with its connection to Microsoft technologies such as Azure and Microsoft SQL Server.
Connection types:
Both Power BI and the SAC have different connection types. Depending on the connection type, different data sources can be connected. Both BI tools include an import connection, where data can be replicated to the cloud and stored in a data model even before the report is created. In addition, Power BI offers a connection type called DirectQuery, which stores the data structure, such as column names, in Power BI. The transaction data itself remains in the data source. Typically, such a connection is possible to relational data sources.
Instead of DirectQueries, the SAC uses so-called live connections. With live connections, no data is stored in the cloud, but is retrieved from the data source exclusively at the time of report execution and displayed in the dashboard. The actual data thus remains in the source system behind the company's firewall.
Only the report information and the meta information are contained in the Cloud. With a live connection, changes within the database have an immediate effect on the data displayed in the dashboard and thus enable real-time reporting. For example, key figure names can also be dynamic and contain the current date. With a live connection, the authorisation check of the source system also takes place in addition to the SAC authorisations. A live connection can be established in the SAC to various SAP products.
Detailed information on which data sources can be connected to SAC and Power BIand with which connection types can be found in the corresponding link.
SAP BW data sources can also be connected to Power BI. However, compared to the SAC Live connection described previously, many of the backend functions offered by SAP are not fully supported by Power BI. The following section performs the analysis on this.
To prepare for the respective analyses, large amounts of data are "improved" as part of the modelling. The processing for quality enhancement generally includes:
- Definition of categories
- Definition of hierarchical relationships and expansion around these hierarchies
- Definition / modelling of key figures and dimensions
- Definition of units and currencies
- Create and add your own formulas
- Data wrangling (preparation or cleaning of raw data)
All common functions (union, join, hierarchies, advanced calculations, smart grouping and value formatting) were reviewed as requirements in our evaluation of SAP Analytics Cloud vs. Microsoft Power BI.
Result:
In particular when grouping values to be compared, the Power BI functions are more mature. However, when it comes to data preparation and calculation using SAP BW Live, the figures provided in Power BI have significant gaps:
- Local calculations do not affect the numbers provided, which ignores the created cumulative aggregation of a BEx query. Power BI only uses the base figures here, and the result of the cumulated query could therefore potentially be interpreted incorrectly due to incorrect numerical material.
- Aggregation is also incorrect when dealing with different currencies or units of measurement: These are not taken over by Power BI. For example, values from USD, EUR and CHF are added, aggregated and displayed unspecified - without any indication that they are different currencies.
- The application of hierarchies is also difficult: Microsoft Power BI can only process one hierarchy per dimension. In addition, neither time-dependent hierarchies nor those of multiple versions can be used. With SAP Analytics Cloud (SAC) however, several hierarchies can exist for each characteristic and be individually selected by users.
- Another disadvantage of Power BI is the lack of text variables: When using the Microsoft product, this function must be dispensed with completely. In contrast, SAP BW presents users with changeable default values (e.g., frequently used calendar years).
- In addition, defined sort orders (by text or key) cannot be transferred from SAC to Microsoft Power BI - so that, for example, when displaying calendar months, the output is "April" or "Aug". In addition, the sort order is not subsequently customizable.
- At the same time, Microsoft Power BI lacks other important features such as currency conversion and numerical formatting. The lack of sufficient scalability also further reduces the required user-friendliness and thus the suitability for standard reporting.
As self-service solutions, Power BI and SAC both offer the right conditions for generating clear, appealing and meaningful stories from data. Charts (comparison, distribution, composition and performance) are supported in various forms - as are numerical visualisations such as KPIs and tag clouds.
With regard to special characteristics such as geo representations, SAC predominates, e.g. with ESRI Charts, Power BI in GEO JSON Support. Thus, it is always necessary to take a close look at what is already being used or will be used in the future. In particular, the visualization types Heat Map Layer, Symbol Maps and Flow Map are very well served by SAP Analytics Cloud. In contrast, these chart types cannot be implemented with Power BI.
Even the IBCS® notation concept, which has many advantageous features, is only available (and already integrated) in SAC and not in Power BI. One essential factor when it comes to self-service BI is that potential arbitrariness needs to be prevented as far as possible for various graphic display options, as efficiently standardised visualisation is the only way of guaranteeing the highest possible informative value, and thus better decision-making.
Despite increasing calls for self-service BI, many mandatory BI use cases are becoming increasingly complex. At the same time, organisations need a more individual and flexible workflow to meet their requirements. As such, one of the tasks in our evaluation was to be able to create complex dashboards in a highly individualised way via scripting.
When comparing the two front-end solutions, the corresponding functions were tested with SAC's Application Designer. This proved to be very successful, although its range of functions does not yet completely match that of the Lumira Desinger. However, further development of the SAC Application Designer is expected in the near future.
The SAP Analytics Cloud also proved to be very interesting during our evaluation with regard to the stringent pursuit of the so-called "closed loop".
In addition to options for calling up data in the transaction system, SAC Data also offers the option of programmatic access. For example, users can generate a sales activity in the SAP CRM system directly from a SAC report or trigger a purchase order in SAP Ariba. In short, report recipients are able to proactively perform interactions in the operational system - additionally enhanced by the integrated SAC functionalities for planning, analysis and forecasting.
The representation of all these functions in a uniform analytical platform is a genuine difference-maker. This is also confirmed by Gartner's Magic Quadrant, which cites SAP as one of only two providers currently with a product of this kind. Microsoft Power BI on the other hand is offered as a pure self-service solution at the moment.
5. Summary of the analysis and investigation of both BI tools
Power BI focuses primarily on requirements for agile analyses and self-service business intelligence. However, the software shows functional gaps with regard to enterprise reporting with the SAP back-end, and these are particularly obvious when trying to connect to SAP BW data sources, as many of the functions offered in SAP Analytics Cloud are not fully supported by Mircosoft Power BI.
The SAP Analytics Cloud (SAC) always implements standard reporting reliably and with maximum efficiency. It is a sophisticated SAP predictive analytics tool that also offers comprehensive possibilities for the reporting of the future:
SAC, as a predictive analytics tool, is considered visionary - thanks, among other things, to Smart Insights and new functions with control through machine learning (incl. NLP-based search). Its integrated functionality for planning, analysis and prediction on a unified platform is a key differentiator. The same applies to the Digital Boardroom, based on interactive dashboards, which is as attractive as it is beneficial for executives with possible analyses and simulations in real time. Thus, with the help of SAC, efficiency in the company can be increased.
Any questions?
- We can provide you with expert support to expand and exploit the potential of your reporting technology as efficiently as possible.
- Would you like more information on our evaluation and comparison of SAC and Power BI?
- We would also be happy to explain the insights gained from this to you in person at any time.
- Get in touch with us!
6. Differences at a glance
The following tables compare some BI functionalities of Power BI and the SAC and present them clearly.
6.1 Differences in business intelligence features
| Power BI | SAC | |
|---|---|---|
| Visualisations | ||
| Geo-visualisation | Yes | Yes |
| Value driver tree | Yes | Yes (planning) |
| Measuring instrument diagrams | Yes | Custom widget in analytics designer |
| Waterfall diagrams | Yes | Yes |
| Bar and line chart | Yes | Yes |
| Boxplot | Custom visual e.g. by Brad Sarsfield | Yes |
| R visualisation | Yes | Yes |
| Customised diagrams | Custom visuals | Custom widget in analytics designer |
| Reporting compliant with international business communication standards | Custom visuals | Standard |
| Augmented analytics | ||
| Time series forecast | Yes | Yes |
| Forecast | AutoML | Smart predict |
| Automatic reports via analysis of the data set | Insights | Smart discovery |
| Automatic identification of groups | Yes | Smart grouping |
| Automatic analysis of individual visualisations | Analyze -> Explain the increase/decrease/distribution | Smart insights |
| Natural language | Q&A | Search insights |
| Cooperation | ||
| Calendar + process management | No | Yes |
| Comments | Yes | Yes |
| Share | Yes | Yes |
| Mobile | Yes | Yes |
| Self-service | Yes | Yes |
| Planning | No | Yes |
| Applications | Power apps | Analytics designer |
6.2 Cost differences
Cost often also plays a role when making a final decision on a BI tool. Costs depend strongly on a company's needs and the licences required. The licence fees are mostly charged by the manufacturers based on the number of users/user bundles on a monthly basis. Only Power BI Premium refers to the allocated hardware capacity. The following tables provide an overview of the licences currently available in Power BI and the SAC.
Power BI
| Power BI | Basic functions with limitations such as the fact that files with a size of can be imported with a maximum of 1GB. |
| Power BI Pro | Power BI Pro is geared toward users who publish reports, share dashboards and collaborate with colleagues in workspaces. |
| Power BI Premium (single user licence) | In addition to the features of the Power BI Pro license, the Premium license includes features such as paginated reports and artificial intelligence (AutoML, impact analysis). |
| Power BI Premium | This offering allocates capacity in the Power BI service exclusively to individual organizations and allows unlimited content distribution. |
SAC
| Analytics hub | Access to the Analytics Hub which serves as a "single point of access" for various BI solutions. |
| Business intelligence (named user) | All BI functionalities including collaboration. |
| Business intelligence (concurrent session) | All BI functionalities including collaboration. Due to the concurrent user license model, different users can use the same license, but not all of them can access the program at the same time. |
| Planning standard | Enter plan data |
| Planning professional | Create planning models, currency conversion tables, value driver trees, data locking, data actions, and validation rules. |
7. How does the pricing work?
SAP and Microsoft reserve the right to make individual adjustments to the list prices. As such, prices may vary depending on characteristics such as the size of the company, system landscape and customer relationship. Costs therefore have to be assessed for each individual case.
You are welcome to contact us for an individual assessment of SAC purchase options and costs.
8. What do the external ratings say?
As can be seen from the table above, Power BI and SAC offer a wide range of possibilities for analysing and visualising business transactions.
It is therefore is worthwhile consulting external analyses of the "Business Application Research Center" (BARC)to compare BI offers as a whole. One of BARC's tasks is to conduct user surveys and evaluate criteria such as user-friendliness, forecasting capabilities and product strategy. In addition to a comprehensive range of functions, a key evaluation criterion is whether the platforms assessed have the ability to scale across a variety of industries and use cases.
According to BARC, both Microsoft with Power BI and SAP with SAC are among the market leaders. These are "well positioned in the market and lead it with powerful technology and solutions as well as thanks to good sales and market success". As can be seen from the figure below, SAP's SAC scores higher than Microsoft with Power BI in terms of market execution and product portfolio.
In addition to the market view, however, it is also important to apply the respective conditions and requirements to your own situation. The various options should be reviewed in detail to make an informed decision for the organisation as a whole. The enquiries examined here revolve primarily around a comparison between the functions of SAC and Power BI.
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Your SAP Analytics contact
Nadine Matt
Inhouse Sales Analytics
- nadine.matt@s-peers.com
