Remove Data Warehouse Remove Data Workflow Remove High Quality Data Remove SQL
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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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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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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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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). Data lakes are notoriously complex. Data lakes are notoriously complex. Your first 30 days are free! Your first 30 days are free!

Data Lake 262
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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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Modern Customer Data Platform Principles

Data Engineering Podcast

A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Data Lake 147
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Build vs Buy Data Pipeline Guide

Monte Carlo

During data ingestion, raw data is extracted from sources and ferried to either a staging server for transformation or directly into the storage level of your data stack—usually in the form of a data warehouse or data lake. There are two primary types of raw data.