AWS Cloud Data Engineering Tech Stack
Posted on 03 Oct 05:19 | by LeeAndro | 10 views
Published 10/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 68 lectures (3h 40m) | Size: 1.78 GB
AWS Cloud Data Eeering
Data Eeering Tools
ETL, Analytical, Querying and Streaming
Complete code Data Eeering tools in AWS Cloud Infrastructure
No programming experience needed
This course is useful for,
ETL Developers
Data Eeers
ETL Architects
Data Migration Specialists
Database Administrators
Database Developers
Data integration is the process of preparing and combining data for analytics, machine learning, and application development.
It involves multiple tasks, such as discovering and extracting data from various sources; enriching, cleaning, normalizing, and combining data; and loading and organizing data in databases, data warehouses, and data lakes. These tasks are often handled by different types of users that each use different products.
We will be working with the data platforms such as,
Data stores
S3
Relational Database Service ( RDS)
Third-party JDBC-accessible databases
Data streams
Kinesis Data Streams
Firehose
Glue data catalog
Classifiers
Crawlers
AWS Data Eeering ensures fast querying to run Data Analytics on a massive volume of data and feed data to different Business Intelligence Tools, Dashboards, and other applications.
Data eeers work in a variety of settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. Their ultimate goal is to make data accessible so that organizations can use it to evaluate and optimize their performance.
ETL, which stands for extract, transform and load, is a data integration process that combines data from multiple data sources into a single, consistent data store that is loaded into a data warehouse or other target system.
ETL Architects
Cloud Data Eeers
Cloud Eeers
ETL Developers
Cloud Data Integration Specialists
Data Architects
Cloud Data Warehouse Developers
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