Remove Business Intelligence Remove Data Engineer Remove Data Lake
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Building Self Serve Business Intelligence With AI And Semantic Modeling At Zenlytic

Data Engineering Podcast

In this episode Paul Blankley and Ryan Janssen explore the power of natural language driven data exploration combined with semantic modeling that enables an intuitive way for everyone in the business to access the data that they need to succeed in their work. Business intelligence is a crowded market.

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Zenlytic Is Building You A Better Coworker With AI Agents

Data Engineering Podcast

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. The team at Zenlytic have leaned on the promise of large language models to build an AI agent that lets you converse with your data.

Building 278
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Business Intelligence In The Palm Of Your Hand With Zing Data

Data Engineering Podcast

Summary Business intelligence is the foremost application of data in organizations of all sizes. Zing Data is building a mobile native platform for business intelligence. Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day. Missing data?

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Reflecting On The Past 6 Years Of Data Engineering

Data Engineering Podcast

In that time there have been a number of generational shifts in how data engineering is done. Go to [dataengineeringpodcast.com/materialize]([link] Support Data Engineering Podcast Summary This podcast started almost exactly six years ago, and the technology landscape was much different than it is now.

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Announcing New Innovations for Data Warehouse, Data Lake, and Data Lakehouse in the Data Cloud 

Snowflake

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

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Insights And Advice On Building A Data Lake Platform From Someone Who Learned The Hard Way

Data Engineering Podcast

Summary Designing a data platform is a complex and iterative undertaking which requires accounting for many conflicting needs. Designing a platform that relies on a data lake as its central architectural tenet adds additional layers of difficulty. Missing data? Struggling with broken pipelines? Stale dashboards?

Data Lake 100
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Cloud Native Data Orchestration For Machine Learning And Data Engineering With Flyte

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.