AWS Analytics - Athena Kinesis Redshift QuickSight Glue

Covering Data Science, Data Lake, Machine learning, Warehouse, Pipeline, Athena, AWS CLI, Big data, EMR and BI, AI tools

Created byKaushik Vadali

Last updated 11/2018

English

What you'll learn

Learn Data Analytics, Manage AWS Cloud infrastructure, Data Lakes, Handle huge data sets, bigdata and data analysis.
All the lectures come with practical demos for easy understanding.
Exploring AWS Analytics offerings and knowledge to handle data sicentist jobs

Course content

1 section • 10 lectures • 2h 38m total length

1 - AWS Analytics and Data Lakes10:47
Learn to build a single, searchable data catalog over a data lake, ingest and transform structured and unstructured data, and enable analytics, machine learning, and real-time insights.
2 - Amazon Athena - Interactive query service7:10
Explore Amazon Athena, an interactive query service for ad hoc analysis, paying only for the queries you run. Create tables, set formats and partitions, and store results in a bucket.
3 - Amazon CloudSearch - Managed search service16:20
Amazon CloudSearch is a fully managed, scalable search service that indexes data in domains, supports simple searches, multi-keyword queries, and searches using features and operators, with automatic monitoring and recovery.
4 - Amazon Elasticsearch Service11:36
Explore Amazon Elasticsearch Service for real-time search and log analytics. Deploy domains and clusters, index documents, and scale securely; pay only for what you use, with no minimum fee.
5 - Amazon Kinesis - Data Stream - Visualizing Web Traffic Using Amazon Kinesis23:56
Explore how Amazon Kinesis data streams collect, process, and visualize web traffic in real time, enabling real-time and batch analytics with firehose and analytics tools.
6 - Amazon Kinesis - Data Streams using AWS CLI8:40
Configure and use Amazon Kinesis data streams with the AWS CLI, create streams, manage access, monitor via the Kinesis dashboard, and decode encoded stream data with base64.
7 - Amazon Redshift - Data warehousing23:46
Explore Amazon Redshift as a fast, fully managed data warehousing solution on AWS. Leverage massively parallel processing, columnar storage, automated provisioning, backups, and security for scalable analytics and BI integration.
8 - Amazon QuickSight - Business Analytics Intelligence Service14:51
Power your analytics with Amazon QuickSight, enabling ad hoc analysis, fast visualizations, and publishable interactive dashboards from diverse data sources, accessible anytime on any device.
9 - Amazon Data Pipeline - Automate data movement18:36
Automate data movement and transformations with Amazon Data Pipeline, scheduling extract, transform, and load between on-premises sources and AWS services like S3, Redshift, and Glue for scalable analytics.
10 - AWS Glue – Managed ETL Service22:26
Discover how AWS glue provides a managed ETL service that ingests data from sources, infers schema with crawlers, and automates transformations into a target using a data catalog.

Requirements

Basic computer knowledge, Awareness of Cloud computing and good system with internet

Description

AWS emerging as leading player in the cloud computing, data analytics, data science and Machine learning.

AWS Analytics course lectures with practical demos

Lecture Duration (hh:mm:ss)

Amazon Athena - Interactive query service 00:07:10

Amazon CloudSearch - Managed search service 00:16:20

Amazon EMR 00:11:05

Amazon Elasticsearch Service 00:11:36

Amazon Kinesis - Data Streams - Visualizing Web Traffic Using Amazon Kinesis Data Streams 00:23:56

Amazon Kinesis - Data Streams using AWS CLI 00:08:40

Amazon Redshift - Data warehousing 00:23:46

Amazon QuickSight - Business Analytics Intelligence Service 00:14:51

Amazon Data Pipeline - Automate data movement 00:18:36

and Amazon Glue, Data Lakes

Who this course is for:

This course addresses basic to advanced concepts.