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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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What is Data Extraction? Examples, Tools & Techniques

Knowledge Hut

Whether you're a seasoned data scientist or just stepping into the world of data, come with me as we unravel the secrets of data extraction and learn how it empowers us to unleash the full potential of data. What is data extraction? Primary Focus Structuring and preparing data for further analysis.

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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.

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Azure Data Engineer Interview Questions -Edureka

Edureka

Dynamic data masking serves several important functions in data security. It is possible to use Azure SQL Database, Azure SQL Managed Instance and Azure Synapse Analytics. It can be set up as a security policy on all SQL Databases in an Azure subscription. It has no effect on the actual data stored in the database.

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Data Marts: What They Are and Why Businesses Need Them

AltexSoft

A data warehouse (DW) is a data repository that allows for storing and managing all the historical enterprise data, coming from disparate internal and external sources like CRMs, ERPs, flat files, etc. Initially, DWs dealt with structured data presented in tabular forms. Hybrid data marts.

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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.