Mastering AWS Glue, QuickSight, Athena & Redshift Spectrum
What you'll learn
- Confidently work with AWS Serverless services to develop Data Catalogue, ETL, Analytics and Reporting on a Data Lake
- Develop deep knowledge in Glue, Athena, Redshift Spectrum and QuickSight
- Build a serverless data lake on AWS using structured and unstructured data
- Architect Serverless Analytics solutions on AWS cloud platform
Course content
- Preview05:23
- 04:20Pre-requisites - What you'll need for this course
- 01:46Course Objectives
- 02:59Course Content, Convention and Resources
Requirements
- Basic knowledge of database and data warehouse concepts
- Working knowledge of AWS Concepts and Tools like AWS Console, S3, VPC, Security Group, AZ, IAM, Role, Policy etc
- Basic working knowledge of any SQL style query language
- Working knowledge of Redshift would be an advantage, but is not mandatory. Course covers Redshift cluster development
- Course includes demo of all the labs. An AWS Account would be required to try labs hands-on.
Description
PS:
Please do NOT join the course if you do NOT have any basic working knowledge of AWS Console and AWS Services like S3, IAM, VPC, Security Groups etc. AWS Beginners may struggle understanding some of the topics.
Course explains all the labs. If you want to practice labs, it would require AWS Account and may cost $$.
Basic working knowledge of Redshift is recommended, but not a must.
This course has been designed for intermediate and expert AWS Developers / Architects / Administrators.
Course covers each and every feature that AWS has released since 2018 for AWS Glue, AWS QuickSight, AWS Athena, and Amazon Redshift Spectrum, and it regularly updated with every new feature released for these services.
Serverless is the future of cloud computing and AWS is continuously launching new services on Serverless paradigm. AWS launched Athena and QuickSight in Nov 2016, Redshift Spectrum in Apr 2017, and Glue in Aug 2017. Data and Analytics on AWS platform is evolving and gradually transforming to serverless mode.
Businesses have always wanted to manage less infrastructure and more solutions. Big data challenges are continuously challenging the infrastructure boundaries. Having Serverless Storage, Serverless ETL, Serverless Analytics, and Serverless Reporting, all on one cloud platform had sounded too good to be true for a very long time. But now its a reality on AWS platform. AWS is the only cloud provider that has all the native serverless components for a true Serverless Data Lake Analytics solution.
It's not a secret that when a technology is new in the industry, professionals with expertise in new technologies command great salaries. Serverless is the future, Serverless is the industry demand, and Serverless is new. It's the perfect time and opportunity to jump into Serverless Analytics on AWS Platform.
In this course, we would learn the following:
1) We will start with Basics on Serverless Computing and Basics of Data Lake Architecture on AWS.
2) We will learn Schema Discovery, ETL, Scheduling, and Tools integration using Serverless AWS Glue Engine built on Spark environment.
3) We will learn to develop a centralized Data Catalogue too using Serverless AWS Glue Engine.
4) We will learn to query data lake using Serverless Athena Engine build on the top of Presto and Hive.
5) We will learn to bridge the data warehouse and data lake using Serverless Amazon Redshift Spectrum Engine built on the top of Amazon Redshift platform.
6) We will learn to develop reports and dashboards, with a powerpoint like slideshow feature, and mobile support, without building any report server, by using Serverless Amazon QuickSight Reporting Engines.
7) We will finally learn how to source data from data warehouse, data lake, join data, apply row security, drill-down, drill-through and other data functions using the Serverless Amazon QuickSight Reporting Engines.
This course understands your time is important, and so the course is designed to be laser-sharp on lecture timings, where all the trivial details are kept at a minimum and focus is kept on core content for experienced AWS Developers / Architects / Administrators. By the end of this course, you can feel assured and confident that you are future-proof for the next change and disruption sweeping the cloud industry.
I am very passionate about AWS Serverless computing on Data and Analytics platform, and am covering A-to-Z of all the topics discussed in this course.
So if you are excited and ready to get trained on AWS Serverless Analytics platform, I am ready to welcome you in my class !
Who this course is for:
- Anyone who wants to learn AWS Serverless technologies for data and analytics should take this course
- Data Professionals seeking to learn Serverless Storage, Serverless ETL, Serverless Data Analysis and Serverless Reporting should take this course
Instructor
![Siddharth Mehta](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.3 Instructor Rating
- 5,700 Reviews
- 48,288 Students
- 10 Courses
Udemy's Top 10% of most engaging instructors
My name is Siddharth Mehta. I have career experience of more than 15 years in the IT Industry and am presently working as Enterprise Cloud Architect. I am published author on many online and print-media publications. I have taught thousands of students on Udemy and have number of courses on Data and Analytics.
Would you consider learning from just any hobbyist who knows programming or someone who just teaches programming without practically using it in the real world, or someone who has experience of using the technology in real world on multi-million dollar large-scale projects globally ? I will teach you everything I know about the subject, from my years of practical experience in the field of BI, Data, Analytics, Cloud and Data Science.
If you are interested in learning more about me, below are some of my career highlights:
I have career experience of more than 15+ years and am presently working in New York Metro region as Enterprise Architect for a life-sciences proprietary multi-tenant product technology portfolio, managing an ecosystem of ISVs and tenants. Below are some of my career highlights:
-|- International experience of working across geographies (US, UK, Singapore) for multi-national clients in Banking, Logistics, Government, Media Entertainment, Products, Life Sciences and other domains
-|- Lead architecture of multi-million dollar portfolios containing apps in Cloud, web, mobile, BI, Analytics, Data warehousing, Reporting, Collaboration, CMS, NoSQL and other categories.
-|- Official inventor of a patented application
-|- Published author/reviewer of whitepapers for Microsoft MSDN Library, Manning publication, Packt publication and others.
-|- Certifications: AWS Certified Solution Architect, TOGAF 9, CITA-F, HCAHD and more
In my present role, I remain responsible for Estimations like AO, IO, SI, IC & Security, Architecture Design, Technology Stack selection, Infra design, 3rd party products evaluation and procurement, and Performance engineering. Hands-On Technology experience of below tech:
-|- OS: Win, Linux
-|- Cloud: GCP, Azure, AWS
-|- Databases: Neo4j, AWS Neptune, Redis, Memcached, MongoDB, Cassandra, HBase, SQL Server, MariaDB, Postgres, Aurora, MySQL, SSAS, AWS Redshift, Google BigQuery, Azure Data Lake, AWS RDS, DynamoDB, Athena, AWS Elasticache
-|- Big Data: Google DataProc, AWS EMR, Kafka, Spark, Hive, Oozie
-|- Search: AWS Elasticsearch
-|- Web: Node.JS, Angular, jQuery, REST APIs, React
-|- ESB/ETL: AWS Lambda, Step Functions, AWS Kinesis, AWS Glue, Mulesoft, SSIS, AWS Data pipeline
-|- Data Science: R , Python, GGPlot 2, Numpy, Seaborn, Pandas, Skikit-learn, Spark ML, Data Mining, Regression & Classification algorithms
-|- Reports / Dashboards : Tableau, Qlikview, SSRS, AWS Quicksight, D3