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No-Code Technology Powers Data Innovation at Databricks

No-Code Technology Powers Data Innovation at Databricks


The data and artificial intelligence landscape is undergoing a transformational change with the integration of no-code technologies to increase efficiency and innovation.

One company leading this effort is Databricks Inc., whose recent developments promise to streamline data management and processing through open source efforts and advanced automation.

Tony Baer of DbInsights talks to theCUBE about no-code technology.

“We've seen a wave of innovation,” said John Farrier, executive analyst at CUBE Research. “We're in a period where we're likely to see a lot of big moves. Databricks is in it for the long haul and has made a strong play by declaring that they're going open source.”

Farrier spoke with Sanjeev Mohan (pictured left), principal at SanjMo, and Tony Baer (right), principal at dbInsight LLC, at the Data + AI Summit, broadcast exclusively from SiliconANGLE Media's livestreaming studio, theCUBE. They discussed Databricks' recent advancements in integrating data and AI, focusing on open source efforts, automation and the competitive landscape between Databricks and Snowflake Inc. (*disclosures below).

Open source and your own control

Databricks is pushing the envelope with its commitment to the open source format and is moving to push the boundaries of the industry, but this approach comes with challenges, particularly in Baer's view that Databricks retains too much control over these projects.

“I think there's a lot of interest on the open source side,” he said. The challenge for Databricks is that, aside from Apache Spark, the company's open source history has been projects that have been primarily Databricks-driven. I think open source, and especially open sourcing Unity, is a great development. On the other hand, I think there's also a perception that Databricks has to overcome that they actually have control over this.

Databricks' open source strategy, particularly tools like Lakehouse Federation, allows it to connect various data sources, including SAP SE and Salesforce Inc. Mohan said this integration makes data sharing and ETL processes easier without the need for extensive coding.

“Imagine what Databricks is doing with Lakehouse Federation and the new ETL they're doing with LakeFlow, where you can connect to not only Snowflake but also SAP Salesforce,” he said. “You can do ETL, you can share data, you can do clean rooms. I feel like both Snowflake and Databricks are really innovating and helping their customers.”

The future of integration, automation and no-code technology

Integration and automation have been at the forefront of recent innovation in the data and AI space, and Databricks has introduced new efforts to integrate its data and AI stack, moving beyond traditional tabular formats to enable seamless interactions of complex data, Mohan noted.

“You need a format, but you don't need it for everything,” he said. If you have structured data and you're putting a compute engine on top of it, you need a table format. But if you're doing AI, the table format doesn't matter. If you're doing data sharing, you need data sharing as a standard, but you don't need a table format. There's a lot of work being done to standardize the access points.

The competition between Databricks and Snowflake is expected to drive more innovation as the two companies cater to different user bases but work toward similar goals. Baer said the evolution of the ecosystems around these platforms will also encourage third-party innovation, helping to grow and advance the industry as a whole.

“We have Snowflake and Databricks, and they're not going to continue to coexist. We have to figure out how to streamline this. I think that's still a really big problem. The reality is, every organization is going to have these competing platforms,” ​​he said.

Databricks continues to innovate with no-code technology, setting new standards in efficiency and accessibility for data management. Our focus on user-friendly solutions is essential to enable businesses to leverage advanced data capabilities without the need for deep technical expertise.

Below is the full video interview, which is part of SiliconANGLEs and theCUBE Research’s coverage of the Data + AI Summit.

(* Disclosure: theCUBE is a paid media partner of Data + AI Summit. Neither Databricks, nor any other sponsor of theCUBE's event coverage, has any editorial control over content on theCUBE or SiliconANGLE.)

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