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SQL for Data Engineering: Success Blueprint for Data Engineers

ProjectPro

At the heart of these data engineering skills lies SQL that helps data engineers manage and manipulate large amounts of data. Did you know SQL is the top skill listed in 73.4% of data engineer job postings on Indeed? Almost all major tech organizations use SQL. use SQL, compared to 61.7%

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How Windward Built Real-Time Logistics Tracking and AI Insights for the Maritime Industry

Rockset

The steps Windward takes to create proprietary data and AI insights As Windward operated in a batch-based data stack, they stored raw data in S3. They used MongoDB as their metadata store to capture vessel and company data.

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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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12 Must-Have Skills for Data Analysts

Knowledge Hut

Analyzing data with statistical and computational methods to conclude any information is known as data analytics. Finding patterns, trends, and insights, entails cleaning and translating raw data into a format that can be easily analyzed. Using databases efficiently is an important data analyst technical skill.

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Mythbusting: The Venerable SQL Database and Today’s Real-Time Analytics

Rockset

So I don’t fault you for resisting my message, which is that the SQL database that came of age in the 80s still has a critical role to play today in moving data-driven companies from batch to real-time analytics. In many tech circles, SQL databases remain synonymous with old-school on-premises databases like Oracle or DB2.

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

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Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. The distinction we’re making here are tools, such as PostgreSQL that can be used as transactional databases, versus BigQuery, a data warehouse.