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

Rockset

This enrichment data has changing schemas and new data providers are constantly being added to enhance the insights, making it challenging for Windward to support using relational databases with strict schemas. 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

Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights. With DBT, they weave powerful SQL spells to create data models that capture the essence of their organization’s information. The data warehouse, role, database, schema, credentials, etc.

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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. They then arrange the data in a suitable format that is simple to understand.

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SQL for Data Engineering: Success Blueprint for Data Engineers

ProjectPro

If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. Data engineers can perform any quality checks using the DDL commands in SQL.

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

Rockset

Rockset is the real-time analytics database in the cloud for modern data teams. Get faster analytics on fresher data, at lower costs, by exploiting indexing over brute-force scanning. 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. Cloud data warehouses solve these problems. What is a data warehouse? What’s the difference between a transactional database and a data warehouse?