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Exploring Processing Patterns For Streaming Data Integration In Your Data Lake

Data Engineering Podcast

Datafold also helps automate regression testing of ETL code with its Data Diff feature that instantly shows how a change in ETL or BI code affects the produced data, both on a statistical level and down to individual rows and values. The Lambda architecture has largely been abandoned, so what is the answer for today’s data lakes?

Data Lake 100
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Maintaining Your Data Lake At Scale With Spark

Data Engineering Podcast

This conversation was useful for getting a better idea of the challenges that exist in large scale data analytics, and the current state of the tradeoffs between data lakes and data warehouses in the cloud. What are some of the common antipatterns in data lake implementations and how does Delta Lake address them?

Data Lake 100
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StreamNative Brings Streaming Data To The Cloud Native Landscape With Pulsar

Data Engineering Podcast

You monitor your website to make sure that you’re the first to know when something goes wrong, but what about your data? Tidy Data is the DataOps monitoring platform that you’ve been missing. You monitor your website to make sure that you’re the first to know when something goes wrong, but what about your data?

Cloud 100
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An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications

Data Engineering Podcast

Select Star’s data discovery platform solves that out of the box, with an automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day.

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

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Building A Data Lake For The Database Administrator At Upsolver

Data Engineering Podcast

How does the introduction of a universal SQL layer change the staffing requirements for building and maintaining a data lake? What are the advantages of a data lake over a data warehouse if everything is being managed via SQL anyway?

Data Lake 100
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8 Essential Data Pipeline Design Patterns You Should Know

Monte Carlo

In this guide, we’ll explore the patterns that can help you design data pipelines that actually work. Table of Contents Common Data Pipeline Design Patterns Explained 1. Lambda Architecture Pattern 4. Kappa Architecture Pattern 5. Data Mesh Pattern 8. Batch Processing Pattern 2.