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How AI Can Be Utilized to Achieve Seamless Data Integration Experience

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Key Takeaways

⇨ AI is growing to be a natural actor in businesses' lives and it can be utilized in the data integration updates.

⇨ Hand-built coding in data processing is becoming an outdated way of collecting and processing data in SAP systems due to delays and risks of manual mistakes.

⇨ An example of utilization of AI exhibited by Precog shows that it can be a pivotal concept which will assist in making data integration and analytics processes seamless across unified systems of SAP's BTP.

As time progresses, so does technological advancement. Artificial Intelligence (AI) is gradually becoming a natural actor in businesses’ lives, overtaking various types of operations and transforming legacy systems. Among those operations stands progress in a faster, easier, and more efficient way of integrating data across SAP systems.

For years organizations have used a traditional way of integrating hundreds and thousands of their data sources through coding. The connections between those sources were made through hand-built codes which proved to be a slow and time-consuming process. Alongside the timing issues, businesses also experienced problems with connectivity and possibilities of inaccuracy. A demand for automated and unified solutions that would eliminate delays and risks in data analytics appeared on the market.

Enter Precog’s AI-powered ELT platform – a solution, designed specifically for SAP Datasphere and business technology platform (BTP). Precog aims to make it easier to get data out of APIs by utilizing AI and machine learning to SAP’s Datasphere and BTP. The platform is meant to help navigate the processing of data from different SAP applications like Concur, SuccessFactors, Ariba, and S/4HANA as well as non-SAP applications.

This way, AI extracts data from API sources without any human intervention and sends it off to an SAP Datasphere system which helps companies to process data more easily in a unified BTP. When all the data is stored inside Datasphere, organizations can then create the analytics and machine learning they need to run their businesses better.

Precog’s approach to the utilization of AI and machine learning capabilities in data integration efforts shows that there is a way for SAP users to kill two birds with one stone: it is possible to make the process of collecting and processing data across API connectors easier while also lifting the risks of manual mistakes and delays in operations from traditional coding at the same time. Although artificial intelligence will inevitably become a vital part of our lives, it is important to understand that its utilization can become a valuable asset across various business functions, including data integration and processing.

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