The definition of batch is fast changing with quickly maturing technology landscape
in Cloud, batch is no longer about processing when business is away. It is about
ingesting as the transactions occur, structure the data to be ready for consumption
quickly. ETL paradigm has shifted into ELT and a lot of Enterprise tools have
demonstrated benefits of ELT in place of ETL. Over the last 10 years, with transactional
systems ecosystem gaining more maturity, T in ETL / ELT is no longer part of the
conversation but significant investments in changing the way data is extracted,
loaded, and managed. With low-code, no-code and zero ETL frameworks, E & L also
may see the fate of T in the years to come.
Recently, a lot of intelligence is being built into data engineering processes and platforms. If
machines can become intelligent with the advent of the IoT, why not data platforms? This session
will discuss the radical shift we are seeing in embedding intelligence into data engineering. Given the
broad scope of this topic, we will focus on the key use cases that the industry is deploying today to
drive efficiencies in the creation /management of data platforms and thereby improve confidence in
the data provided to business users.
Data engineering and Generative AI’s synergies can create powerful solutions that enable enterprises to make better decisions, automate processes, and improve customer experiences. Join us for an interactive session and demo to explore how enterprises can build, customize, and deploy these powerful solutions anywhere.
