Architecting Big Data Solutions (Udemy.com)
How to architect big data solutions by assembling various big data technologies - modules and best practices
Created by: V2 Maestros
Produced in 2017
What you will learn
- Understand the differences between Traditional and Big Data Solutions
- Breakdown a Big Data solution into its modules
- Look at Technology options for each module
- Learn the advantages, short comings and use cases for each technology option
- Architect multiple real life use cases
Quality Score
Overall Score : 78 / 100
Course Description
Building Big Data solutions is radically different from how traditional software solutions were built. You cannot take what you learnt in the traditional data solutions world and apply them verbatim to Big Data solutions. You need to understand the unique problem characteristics that drive Big Data and also become familiar with the unending technology options available to solve them.
This course will show you how Big Data solutions are built by stitching together big data technologies. It explains the modules in a Big Data pipeline, options available for each module and the Advantages, short comings and use cases for each option.
This course is great interview preparation resource for Big Data ! Any one - fresher or experienced should take this course.
Note: This is a theory course. There is no source code/ programming included.Who this course is for:
- Anyone interested in Big Data
- Software Architects
- Students in IT
- Professional preparing for Big Data interviews
Instructor Details
- 3.9 Rating
97 Reviews
V2 Maestros
V2 Maestros is dedicated to teaching big data / data science courses to students all over the world. Our instructors have real world experience practicing big data and data science and delivering business results. Big Data Science is a hot and happening field in the IT industry. Unfortunately, the resources available for learning this skill are hard to find and expensive. We hope to ease this problem by providing quality education at affordable rates, there by building Big Data and Data Science talent across the world.
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