Introduction to Big Data and Data Analytics

After successful completion of this course, participants will understand:

Introduction to Big Data-what is 4Vs (volume, velocity, variety and veracity) in Big Data- Generation, extraction and management
How Big Data analytic differs from legacy data analytic
In-house justification of Big Data
Introduction to Hadoop Ecosystem- familiarity with all Hadoop tools like Hive, Pig, SPARC –when and how they are used to solve Big Data problem
How Big Data is extracted to analyze for analytics tool-how Business Analysis’s can reduce their pain points of collection and analysis of data through integrated Hadoop dashboard approach
Bigdata, Machine Learning, and Artificial Intelligence: Fundamental Concepts

Overview of Bigdata:

Main characteristics of Big Data-volume, variety, velocity and veracity
Data Warehouses – static schema, slowly evolving dataset
Hadoop/Spark Based Solutions – no conditions on structure of dataset
Typical pattern : HDFS, MapReduce (crunch), retrieve from HDFS
Batch- suited for analytical/non-interactive
Volume : CEP streaming data
Typical choices – CEP products (e.g. Infostreams, Apama, MarkLogic etc)
Less production ready – Storm/S4
NoSQL Databases – (columnar and key-value): Best suited as analytical adjunct to data warehouse/database

Chief Technology Officers, Product Managers, Technical Managers and IT Professionals.

3-day instructor-led training

Storm – Real time processing in Big Data
Predictive analytics in Business Intelligence
- Fundamental Techniques & Machine learning based BI

11 Sep 2017

The trainer is very approachable and I gained a lot of knowledge from the course.”

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“Instructor has many scenarios and call procedures examples to show.”

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