Emerging technologies (IoT-SCP to B4 Information Core)
By: Bill Faison
It’s a different environment today since SAP released SAP BW 1.2A on October 1998. No longer are people looking just at 24 hours old relational data from SAP ERP system based. Today’s business world requires that any data warehousing can requires access to an increasingly complex sources to data such as data lakes are comprised of unstructured/non-relational data , social media, devices or data warehouse which contain structured data from enterprise systems or standardized data models.
Since October 1998, there has been new emerging technologies such as machine learning (ML) and Predictive Analytics that are being used to help business make faster and better business decision.
To meet this change, SAP release SAP BW/4HANA to handle these new data types and technologies.
Just as the types of data has changed and new technology advances are being used by the business, this has also changed or created new roles within the business community.
One role that has changed is the business user. Even though they are experts on the business process and are familiar with BI analytical tools, they are now faced with making decision or actions based many different types of data, and feel that the data is too complex and challenging to even know where to get started.
A new role that has emerged is the data scientist. They understand the complex data, and how to take advantage of new technologies such as machine learning and predictive analytics, but they are not business experts. To meet the needs of the business user, the data scientist can be caught up doing many repetitive task, instead of using their skill sets to resolve complex issues.
To bridge this gap between the business user and the data scientist, SAP has come up with a solution that is based on SAP Leonardo and SAP BW/4HANA. Part of SAP Leonardo offerings are Machine Learning and Predictive Analytics, which can be used with SAP BW/4HANA. Since the results of the predictive analytics results can be stored in SAP BW/4HANA, it now can be consumed by many different BI tools such as SAP Analytical Cloud (SAC), SAP Lumira, SAP Analysis for Microsoft Office, SAP Web Intelligence (WEBi) just to name a few.
How does this work?
The data scientist will build and automate machine learning models that generate predictions to discover patterns or recurring behaviors in SAP Predictive Analytics
The predications can be generated based on a schedule or in real-time by using the SAP Predictive Analytics scheduling. It also possible for to use the SAP BW/4HANA tools for the Data Orchestrating of the predications.
Once the predications are stored in SAP BW/4HANA, it’s now ready for the business user to run their analytics over the predication classification, regression, scores, forecasts, clusters or link analysis.