We live in an era of digitalization. It’s a bit cliche, I know. However, have you ever taken a moment to understand what that means? Our lives are now digitally connected. We send and receive information almost every minute of the day, we take pictures, send emails, approve events, check the weather forecast, the traffic, websites… The list is endless, generating huge amount of data that is recorded. Accepting the cookies in a website means your browsing is tracked. From the time you spend reading an article to where you make clicks. If recorded anonymously, it can be useful for statistical purposes. For example, when I check the analysis of my website, I can see what posts the users are reading the most and how long they spend on a page. That can help me to understand if there is any interest in the content of the posts or if I need to make adjustments. The engagement is more important than the number of visits. You can have many visits, but they are not good if people are just checking the homepage and they move out.
With the internet, the social networks, the mobile phones and the smart watches the creation of data has increased exponentially. Now companies have a lot of information and sometimes they are unable to analyze effectively. There is a lot of data and not everything is relevant. This will depend on your purpose. Information needs to be filtered and analyzed in order to understand the global behavior, finding trends and patterns. This has created new IT jobs in the last decade. For example, data scientists or big data analysts.
This means companies need powerful databases to be able to store all the data. Which then means powerful processors and sophisticated software to process it to make it understandable for users. Good analysis will help in decision support, which may need to be done in real time. Remember when it was normal to wait 10 minutes until you got to the web page you wanted to see. Nowadays that is unthinkable.
With the advances in big data, technology is going further and now the patterns found in the data are being used to predict future outcomes. This is machine learning. Artificial Intelligence is being used to automate systems with the outcomes of machine learning. All these technologies combined are the base of what SAP calls the Intelligent Enterprise.
You may be thinking ok, Cristina, all that is interesting, but I need real examples to understand. Think about creating personalized experiences for your customers (post coming soon about this topic). You can know what they are going to like and present this to them based on what customers with similar patterns like. That creates engagement. You can automate those proposals with artificial intelligence after machine learning found the patterns. For example, when Netflix suggests you other movies that you would like, or the same with Spotify and music. Sometimes it feels like technology knows you better than yourself.
The concept of Intelligent Enterprise for SAP is about automation. It moves around the concept of allowing the machines to predict the future, support and make the better decisions in every area of the business. Let’ discuss in more detail the SAP products in the market regarding this.
- SAP HANA. It is the in-memory database of SAP released in 2011. It is also an environment for data modeling. To be able to do so, it is required to install tools like Eclipse or SAP Hana Studio (that is an Eclipse plug-in). Some products of SAP are designed to run exclusively on the database HANA. For example, SAP S/4HANA, SAP C/4HANA or SAP BW/4HANA. There are several ways of deployment for this database on-premise and Cloud (DBaaS – Database as a Service).
Image: SAP HANA deployment options. Source: SAP blog.
- BW/4HANA (Business Warehouse). This is a data warehouse product. SAP BW/4HANA provides capability to integrate, transform, and consolidate business information from SAP applications and non-SAP data sources. SAP BW/4HANA is the evolution of the previous SAP BW and runs specifically on HANA. It can be delivered on premise or cloud.
- SAP Data Warehouse Cloud. This is a DWaaS (Data Warehouse as a Service). This is the newest SAP data warehouse product. It is more end user-oriented than BW/4HANA. Data modeling can be undertaken by business users. It can be integrated with BW/4HANA and is based on HANA Cloud. According to SAP, Data Warehouse Cloud is not replacing BW/4HANA, it is complementary. The concept of Spaces is also interesting.
- SAP Data Intelligence (SAP Data HUB). Big data solution, providing capability to manage data from any source (wherever it resides) and applying machine learning and workflows to automate processes. SAP Data Hub helps to digest the information before BW/4HANA has access to it. This product makes it possible to implement intelligent business applications. SAP Data Intelligence was released in 2019 as the evolution of SAP Data Hub (when it was delivered as SaaS). It includes some functionality that existed in SAP Leonardo like artificial intelligence and machine learning. SAP Leonardo died as a brand in 2019. However, some of these technologies are still being used in SAP. This product has several options for on-Cloud and on-Premise deployments. SAP Vora is the component of SAP Data Intelligence for big data digestion.
Image: Big Data integrated with BW/4HANA. Source: SAP blog.
- Business Objects BI (Business Intelligence). BO/BI is a suite for data reporting, visualization and sharing. This product runs on top of the data warehouse product and it is used to give meaning to raw data for analysis, it provides tools to build reports. SAP BI is an On-Premise solution.
- SAP Lumira is a self-service tool included in the license of BO/BI. It allows users to build analytics and dashboards using data from SAP sources. They can build interactive maps, charts, info graphics, dashboards and other applications. It is also commercialized as a standalone solution. On-premise and Cloud deployment.
- SAP Analytics Cloud is a business intelligence solution that includes predictive analytics and planning capabilities into one environment. Artificial intelligence is used for decision support to support .
Image: SAP Analytics Cloud. Source: SAP blog.
- SAP Crystal reports. This is the affordable version of the SAP Business Intelligence. It is commercialized specially for small and medium businesses.
In case you are still wondering what big data or machine learning is, I leave you below two SAP videos where I think they explain those concepts in an easy way.
Big Data and Analytics: