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How to Use DBT to Get Actionable Insights from Data?

Workfall

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights.

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Tackling Real Time Streaming Data With SQL Using RisingWave

Data Engineering Podcast

Summary Stream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable.

SQL 173
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Adding Anomaly Detection And Observability To Your dbt Projects Is Elementary

Data Engineering Podcast

While there are numerous products available to provide that visibility, they all have different technologies and workflows that they focus on. To bring observability to dbt projects the team at Elementary embedded themselves into the workflow. How have the scope and goals of the project changed since you started working on it?

Project 130
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Data Quality Engineer: Skills, Salary, & Tools Required

Monte Carlo

These specialists are also commonly referred to as data reliability engineers. To be successful in their role, data quality engineers will need to gather data quality requirements (mentioned in 65% of job postings) from relevant stakeholders. About 61% request you also have a formal computer science degree.

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DataOps For Business Analytics Teams

DataKitchen

If the IT or data engineering team can’t respond with an enabling data platform in the required time frame, the business analyst does the necessary data work themselves. This ad hoc data engineering work often means coping with numerous data tables and diverse data sets using Alteryx, SQL, Excel or similar tools. .

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Unlocking Your dbt Projects With Practical Advice For Practitioners

Data Engineering Podcast

Summary The dbt project has become overwhelmingly popular across analytics and data engineering teams. Dustin Dorsey and Cameron Cyr co-authored a practical guide to building your dbt project. In this episode they share their hard-won wisdom about how to build and scale your dbt projects. Introducing RudderStack Profiles.

Project 147
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Using Trino And Iceberg As The Foundation Of Your Data Lakehouse

Data Engineering Podcast

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Multiple open source projects and vendors have been working together to make this vision a reality. Data lakes are notoriously complex.

Data Lake 262