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How to Become a Data Engineer in 2024?

Knowledge Hut

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is Data Science? What are the roles and responsibilities of a Data Engineer? What is the need for Data Science?

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Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

Since the inception of the cloud, there has been a massive push to store any and all data. The problem is that these databases belong to the OLTP (online transaction processing) category of databases, which are not built to handle billions of rows and take anywhere from 30 minutes to a few hours to return the resultset for one SQL query.

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Data Mesh: Moving from Concept to Reality

Ascend.io

This is the transcript for this seminal conversation of how a global media company is evolving its data strategy toward a working data mesh. The webinar was held in March 2022, as a conversation between Simon Smith, Chief Data Officer at News Corp. He is two years into implementing a major data transformation across the company.

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Data Scientist vs Data Engineer: Differences and Why You Need Both

AltexSoft

Explaining the difference, especially when they both work with something intangible such as data , is difficult. If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. Data science vs data engineering.

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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. What is Kafka?

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The Good and the Bad of Databricks Lakehouse Platform

AltexSoft

The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. The relatively new storage architecture powering Databricks is called a data lakehouse.

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