ETL Tools MySQL Structured Data 
ProjectPro
JUNE 6, 2025
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., Need for Apache Sqoop How Apache Sqoop works? Need for Flume How Apache Flume works?
ProjectPro
OCTOBER 28, 2015
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., Need for Apache Sqoop How Apache Sqoop works? Need for Flume How Apache Flume works?
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ProjectPro
JUNE 6, 2025
Transform unstructured data into structured data by fixing errors, redundancies, missing numbers, and other anomalies, eliminating unnecessary data, optimizing data systems, and finding relevant insights. Data Integration and ETL Tools ETL is necessary for data modeling and vice versa.
ProjectPro
JUNE 6, 2025
Project Idea : Build a data engineering pipeline to ingest and transform data, focusing on runs, wickets, and strike rates. Use the ESPNcricinfo Ball-by-Ball Dataset to process match data. Store raw data in AWS S3, preprocess it using AWS Lambda, and query structured data in Amazon Athena.
ProjectPro
JUNE 6, 2025
Identifying patterns is one of the key purposes of statistical data analysis. For instance, it can be helpful in the retail industry to find patterns in unstructured and semi-structured data to help make more effective decisions to improve the customer experience.
ProjectPro
JUNE 6, 2025
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.
Knowledge Hut
DECEMBER 26, 2023
The responsibilities of Data Analysts are to acquire massive amounts of data, visualize, transform, manage and process the data, and prepare data for business communications. They also make use of ETL tools, messaging systems like Kafka, and Big Data Tool kits such as SparkML and Mahout.
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