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Python for Data Engineering

Ascend.io

Read More: Data Automation Engineer: Skills, Workflow, and Business Impact Python for Data Engineering Versus SQL, Java, and Scala When diving into the domain of data engineering, understanding the strengths and weaknesses of your chosen programming language is essential. show() So How Much Python Is Required for a Data Engineer?

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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

Java Big Data requires you to be proficient in multiple programming languages, and besides Python and Scala, Java is another popular language that you should be proficient in. Java can be used to build APIs and move them to destinations in the appropriate logistics of data landscapes.

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12 Must-Have Skills for Data Analysts

Knowledge Hut

The most popular databases for which data analysts need to be proficient are SQL and NoSQL databases. Data modeling and database management: Data analysts must be familiar with DBMS like MySQL, Oracle, and PostgreSQL as well as data modeling software like ERwin and Visio.

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Top 20+ Big Data Certifications and Courses in 2023

Knowledge Hut

Programming Languages : Good command on programming languages like Python, Java, or Scala is important as it enables you to handle data and derive insights from it. Big Data Frameworks : Familiarity with popular Big Data frameworks such as Hadoop, Apache Spark, Apache Flink, or Kafka are the tools used for data processing.

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Data Engineer Learning Path, Career Track & Roadmap for 2023

ProjectPro

Good skills in computer programming languages like R, Python, Java, C++, etc. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Thus, having worked on projects that use tools like Apache Spark, Apache Hadoop, Apache Hive, etc., High efficiency in advanced probability and statistics.

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The Top 25 Data Engineering Influencers and Content Creators on LinkedIn

Databand.ai

He also has more than 10 years of experience in big data, being among the few data engineers to work on Hadoop Big Data Analytics prior to the adoption of public cloud providers like AWS, Azure, and Google Cloud Platform. On LinkedIn, he focuses largely on Spark, Hadoop, big data, big data engineering, and data engineering.

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The Good and the Bad of the Elasticsearch Search and Analytics Engine

AltexSoft

First publicly introduced in 2010, Elasticsearch is an advanced, open-source search and analytics engine that also functions as a NoSQL database. It is developed in Java and built upon the highly reputable Apache Lucene library. What is Elasticsearch? The engine’s core strength lies in its high-speed, near real-time searches.