Rafał Skorupa | Digital transformation | 24.06.2020
Business Intelligence class tools, like other types of software, are beginning to take their permanent place in the cloud. At present, however, we can observe another important change in the area of Business Intelligence, meaning: taking advantage of the field that has followed a separate path until now – Artificial Intelligence (AI). As part of this article, we’ll look at the possibilities of using Artificial Intelligence in the Data Analysis process.
Microsoft, Qlik and Tableu have been listed among the leading providers of Business Intelligence systems by Gartner for years now. Solutions based on Artificial Intelligence are already offered by each of these leading companies.
Learn more: Business Intelligence services
Gartner’s Magic Quadrant is a guide for business representatives when it comes to choosing a tool. It is worth observing the contest between so-called visionaries. Here Gartner indicates providers who know the market and have the potential to change it. SAP is one such visionary – and today we will take a closer look at what this well-known player has to offer. Since it is widely known that the cloud is a development direction for Business Intelligence tools, SAP has also decided to create something that will be a cloud alternative to the on-premises SAP BusinessObjects. The SAP Analytics Cloud tool (SAC), which has been available on the market since 2018, is currently the main direction of development for SAP in the field of data analysis and reporting. Let’s look at how SAP redefines work with analytical tools.
Data democracy has recently been a hot topic, promoting widespread access of users without specialized IT knowledge to unassisted data analysis, among others. Until now, such users were dependent on Business Intelligence specialists. Introducing the benefits of Artificial Intelligence to its analytical tool, SAP tries to meet the needs of users who do not have high-level analytical or IT qualifications. Let’s look at some interesting functionalities supporting data analysis that we can find in the SAP Analytics Cloud.
Let’s imagine for a moment that we are analyzing sales data for beverages and we want to start with some basic information on sales results in recent years. According to the traditional approach, we would try to search for the report on our platform, hoping that it was titled in a way that is intuitive enough for us… But what about the possibility of using a search box in a different way, and – instead of looking for a specific report title – trying to ask a question which we want to find out the answer to?
Here are some examples of how Search to Insight uses Natural Language Processing to build reports based on search engine queries:
Query: “Gross margin time chart by location”
Query: “Show me the top 5 products in Location Reno in 2016 Q1”
The text query processing function works quite well, provided that we use the names of the dimensions available in the analytical model prepared beforehand by someone else in the queries. Fortunately, the user can display an available list of objects which they can use in their queries. Search to Insight works well for basic queries related to the aggregation of available metrics. However, if our queries exceed the capabilities of this tool, we can still count on AI support in the form of another module called Smart Discovery.
The tool for report building in SAC, based on the existing data model, gives us the opportunity to use Machine Learning mechanisms. Machine Learning facilitates the discovery of patterns and statistically important relationships for our data source. When running such an analysis for a previously used sales model, the user only needs to indicate what element of the model will be the subject of the study (whether it will be a dimension or a measure), and then indicate which other elements are to be assessed in terms of the impact on the analyzed variable as part of the model.
For example, by indicating the gross margin measure as the main object of our analysis, we can get the following result:
Simple mechanism for “what-if” analysis. It allows you to assess the impact of changing particular model parameters on the variable you are studying, such as changing the discount value for selected products. It is a highly desirable functionality for business users, although in my view it still requires some refinement so that the presented results are more understandable to users.
The presented Smart Discovery tool is not the last functionality that SAC has to offer in the field of Augmented Analytics. After verifying the correctness of historical data, SAC can help us look to the future thanks to its Smart Predict functionality.
As part of predictive services, SAC offers three types of predictive models:
The operating principle is similar for each type of model.
When assessing SAC functionalities in the field of data prediction, we can claim that their main advantage is simplicity of use, which will allow you to undertake complex analysis with no need for advanced statistical knowledge. This is why this tool should not be compared with other Machine Learning tools available on the market, which have much more developed capabilities, but therefore require a more in-depth knowledge of statistics.
After finding out more about the capabilities of Business Intelligence tools which use Machine Learning and the possibilities they open up for users, the following question may arise: “Do we still need Business Intelligence specialists?” My answer is: definitely! The competences of Business Intelligence specialists will still be necessary to create analytical models in such a way that will allow for their proper use in the above-mentioned Self-Service Reporting tools in modern SAP Analytics Cloud systems. Specialist BI knowledge will also be priceless in terms of integrating data from many different sources and building more complex analytical applications.
Self-Service Reporting tools equipped with the power of Artificial Intelligence uncover new possibilities for users who are looking for Business Intelligence tools. And while we’re still not using the full potential of Machine Learning, one thing is certain: AI is the future of BI! Business Intelligence specialists equipped with new tools will be able to provide consistently better business solutions. If your organization is facing new analytical challenges, take advantage of the extensive experience of Business Intelligence specialists to help make full use of the potential of your tools and achieve your business goals.