Realtime Analytics with Apache Pinot and Apache Flink

Understand how Realtime Analytics can be done for a Real Industry Use case With Apache Pinot and Apache Flink

What you'll learn
Understand how Realtime analytics can be done for a Real World business case of Online Cab Service Company
Understand how Apache Flink can be used for Realtime Data Processing
Understand how you can Join across multiple streams in Apache Flink
Learn how to Lookup data in Flink from external data stores
Learn how to Use Apache Pinot to run Realtime Analytical Queries
Learn how Realtime Upserts are possible in Apache Pinot
Learn how Apache Kafka acts as the Connecting layer between the various components in a Realtime Analytics System
Learn how to create Dashboards for Realtime data in Apache Superset
Everything in this course is use case focussed so that you can directly Apply this to a Real Life project

Requirements
Having prior Knowledge of Java and SQL is helpful but not Mandatory
Everything is thought within the course itself, So no Prior background is needed

Description
In Today's Fast paced Business Environment, the ability to
Extract Actionable Insights
from data in a
Realtime manner
is very Important. Real-time Analytics can act as a differentiating factor between various Companies.
Knowing how Realtime Analytics can be done, is a very important Skill set which is necessary right now and will be necessary in the future as well.
In this Course I have covered how you can do
Realtime Analytics
using
Apache Pinot
and
Apache Flink
with the help of a real industry use case. You will Understand how Real-time Analytics can be done for an
Online Cab Service Company.
It is necessary to not just know the Theory but also implement Things Hands On. So this course has a lot of
Hands On Sessions
to show you how things can be implemented. Also at every step we will be focusing on the actual Business use case which is being solved
This Course Covers the following Topics:
Understand Why Realtime Analytics is Needed.
Understand Where Realtime Analytics comes in for a Use Case like Online Cab Service Company.
Architecture of a Realtime Analytics System.
An Introduction to Apache Kafka and also an illustration of how Kafka acts helps connect all the Components of a Real-time Analytics System.
Basic Concepts of Apache Flink.
Flink Dynamic Tables and Versioned Tables.
Concepts Like Checkpoints and Watermarks in Apache Flink.
Different types of Joins in Apache Flink Like Regular Joins and Temporal Joins.
Realtime data ingestion and data upserts in Apache Pinot.
Running Analytical Queries in Apache Pinot.
Creating Dashboards for Realtime data in Apache Superset
By the end of this course, You will have a working Realtime Analytics System in your local system for an Online Cab Service Company.
Who this course is for:
For Developers Who want to Learn how Realtime Analytics Actually Happen for a Real World Use Case
For Curious Techies Who are curious on how Big data technologies Work
For Data Engineers Who are interested to Learn more about how Pinot and Flink fit in a bigger ecosystem
For Anyone Who Wants to Apply Realtime Analytics for the projects they are working on Currently
For Anyone Who wants to take on a new Role where you want to work Realtime Analytics

More Info