Realtime Analytics with Apache Pinot and Apache Flink | Udemy


Realtime Analytics with Apache Pinot and Apache Flink | Udemy
English | Size: 1.49 GB
Genre: eLearning

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

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

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