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Reducing The Barrier To Entry For Building Stream Processing Applications With Decodable

Data Engineering Podcast

Summary Building streaming applications has gotten substantially easier over the past several years. Despite this, it is still operationally challenging to deploy and maintain your own stream processing infrastructure. What was the process for adding full Java support in addition to SQL?

Process 182
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X-Ray Vision For Your Flink Stream Processing With Datorios

Data Engineering Podcast

Summary Streaming data processing enables new categories of data products and analytics. Unfortunately, reasoning about stream processing engines is complex and lacks sufficient tooling. Can you describe how Datorios is used in a day-to-day workflow for someone building streaming applications on Flink?

Process 147
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Find Out About The Technology Behind The Latest PFAD In Analytical Database Development

Data Engineering Podcast

Summary Building a database engine requires a substantial amount of engineering effort and time investment. Over the decades of research and development into building these software systems there are a number of common components that are shared across implementations. Go to dataengineeringpodcast.com/dagster today to get started.

Database 162
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Building ETL Pipelines With Generative AI

Data Engineering Podcast

Now that AI has reached the level of sophistication seen in the various generative models it is being used to build new ETL workflows. In this episode Jay Mishra shares his experiences and insights building ETL pipelines with the help of generative AI. Check out the agenda and register at Neo4j.com/NODES.

Building 162
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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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Building Linked Data Products With JSON-LD

Data Engineering Podcast

Summary A significant amount of time in data engineering is dedicated to building connections and semantic meaning around pieces of information. Linked data technologies provide a means of tightly coupling metadata with raw information. Go to dataengineeringpodcast.com/materialize today to get 2 weeks free!

Building 189
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Precisely Women in Technology: Meet Shweta

Precisely

Although technology has historically been a male-dominated industry, more women are continuing to enter the field. Precisely supports the growth of women in the industry and as a result, established the Precisely Women in Technology (PWIT) Program which supports women at the company. Why did you choose to pursue a career in technology?

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Putting the right LLMOps process in place today will pay dividends tomorrow, enabling you to leverage the part of AI that constitutes your IP – your data – to build a defensible AI strategy for the future.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.