What is SAP Analytics Cloud?
Business Intelligence (BI) is booming business. More and more companies want to be able to make data-based decisions and implement data-based policies. A lot companies hold a wealth of information in the form of data. Often stored in systems such as SAP HANA. However, it can be difficult to gain insight into this data. To make this easier, tools have been developed that focus specifically on analyzing and primarily visualizing data. Examples include Tableau and Power BI. SAP’s answer to these tools is SAP Analytics Cloud (SAC)
With SAP Analytics Cloud, you can visualize data very easily, especially from SAP systems. In fact, the use of data from SAP systems was specifically considered during the development of SAC. However, SAC is also great to use in cases where an SAP system is not used, such as when using Excel, CSV files or an Oracle database. SAC is thus a data visualization tool par excellence. But SAC can do a bit more than traditional data visualization tools.
Data modeling and datarangling: the first step towards good data visualization
After loading the data from an external source such as an SAP database, you still need to clean up the data and prepare it for visualization. This process is called datarangling. SAC has a clear menu where you can specify for each column what data type is in the column and what should happen with the empty fields in the column. You can also add or remove additional columns. So this is where you can really get the data ready for analysis and visualization.
In order to visualize data in a good, informative, but above all correct way, a data visualization tool needs a definition of how the data to be used are interrelated. In other words, a data model must exist and be defined within the visualization tool. In SAC’s data modeler, you can connect tables in a visually clear way. As a result, SAC knows what the relationship between the data from the various tables is and can therefore query the data for further data analysis without problems.
Easy data visualization, analysis and planning
Once the data is loaded, wrangled and modeled properly, the data needs to be visualized for analysis in an organized way. This visualization is done by building a dashboard, which in SAC is called a ‘Story’. These stories are developed in such a way that even less technically literate users can easily build a story. A story uses graphics to create an overview of the data that, if built correctly, allows for a quick visual analysis of the data. An advantage of the stories in SAC is that you can build them interactively. That means that if you click on a value, bar or line in a graph, the other graphs in the story will change to show the specific data and connection to the selected data. So if someone clicks on the data of “Region X” in a graph in the story, the other graphs will show their data in relation to region X. This makes analysis extra easy. A particular advantage of SAC, over competing tools, is its extensive GEO representations. These are interactive ‘maps’ that allow you to very clearly map the activity per country, region or city, thus enabling quick analysis per area.
Another useful feature of SAC is scheduling. Besides making data visually transparent, planning was an important goal of the developers when developing SAC. For one thing, in SAC, through the Smart Insights feature, you can quickly see which factors had the greatest influence on a particular data point. It immediately becomes clear in which area a lot of a particular product is sold or, on the contrary, little. You can then respond accordingly. Smart Discovery goes a bit further than Smart Insights and uses machine learning algorithms to find and analyze correlations between data in the dataset. This feature also allows you to analyze alternative scenarios (what-if scenarios). In addition, based on the patterns in the data, you can predict outcomes and thus anticipate future developments now.
In conclusion, SAP Analytics Cloud is a very valuable analysis tool, which quickly and user-friendly aggregates all data and enables you to quickly make data-driven decisions or implement data-driven policies.
Questions? Or want to discover more about SAC?
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