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What is Data Extraction? Examples, Tools & Techniques

Knowledge Hut

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. AWS Lake Formation architecture.

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Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., then you are on the right page. Need for Apache Sqoop How Apache Sqoop works?

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. Step 1- Automating the Lakehouse's data intake.

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Difference between Pig and Hive-The Two Key Components of Hadoop Ecosystem

ProjectPro

Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. It is Hive that has enabled Facebook to deal with 10’s of Terabytes of Data on a daily basis with ease. Hive is similar to a SQL Interface in Hadoop.

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Top ETL Use Cases for BI and Analytics:Real-World Examples

ProjectPro

Over the past few years, data-driven enterprises have succeeded with the Extract Transform Load (ETL) process to promote seamless enterprise data exchange. This indicates the growing use of the ETL process and various ETL tools and techniques across multiple industries.

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Azure Data Engineer Skills – Strategies for Optimization

Edureka

Data engineering is a new and evolving field that will withstand the test of time and computing advances. Certified Azure Data Engineers are frequently hired by businesses to convert unstructured data into useful, structured data that data analysts and data scientists can use.