Data Processing and Analysis concepts to know as an aspiring data engineer🤖

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Data processing and analysis are key components of modern data engineering. Once data has been collected and stored, it must be processed and analyzed to extract meaningful insights.
Data processing may involve cleaning, filtering, and transforming data to ensure it is consistent and accurate.

Data analysis involves using statistical and machine learning techniques to identify patterns and relationships in the data.
Let’s look at the tools to master for data processing and analysis.

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• Knowledge of distributed computing frameworks such as Apache Spark, Apache Flink, and Hadoop MapReduce

• Experience with data processing and analysis tools such as Apache Hive, Apache Pig, and Presto
• Familiarity with data visualization tools such as Tableau, Power BI, and QlikView
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