Udemy A beginners guide to Data Warehouse and Big Data Udemy
Price: USD 125

    Course details

    This course is a beginner's course that will show you how to implement a basic data warehouse solution using Microsoft SQL Server, Microsoft SQL Server Integration Services SSIS and Microsoft SQL Server Data Tools -SSDT. Also covered in this course is an introduction to Big data and it's concepts.
    Big data is a big buzz word and everyone seems to be talking about it, but what exactly is big data ? Where is this data coming from, how is it being processed, and how are the results being used?
    Big data can be characterised as data that has high volume, high variety and high velocity. Data includes numbers, text, images, audio, video, or any other kind of information you might store on your computer. Volume, velocity, and variety are sometimes called "the 3 V's of big data."
    Examples includes social media network analysing their members' data to learn more about them and connect them with content and advertising relevant to their interests, or search engines looking at the relationship between queries and results to give better answers to users' questions.
    You will learn how to implement ETL ( Extract, Transform, Load) process using SQL Server Integration services .
    This course will show you how to design fact and dimension tables which are the two main types of table used in data warehouse . You will learn the star and starflake techniques used to design dimension tables.

    What You Will Learn :

    • Understanding Star and Snowflakes techniques for schema designs
    • Implementing ETL process
    • Developing ETL process using SSIS and SSDT
    • Physical data warehouse design using SQL views
    • Designing a data warehouse
    • Implementing a data warehouse
    • Big data Concepts
    • High volume data
    • High variety data
    • High variety data
    • Google's big data approach
    • Understanding Clusters
    • Concept of a Node
    • Google File System
    • MapReduce
    • Hadoop

    Updated on 21 January, 2017
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