Combining and Shaping Data

This course covers both conceptual and practical aspects of pulling together from different data sources, with different schemas and orientations, into a cohesive whole using Excel, Python, and various tools available on the Azure cloud platform.
Course info
Level
Beginner
Updated
Jun 21, 2019
Duration
3h 28m
Table of contents
Course Overview
Exploring Techniques to Combine and Shape Data
Combining and Shaping Data Using Spreadsheets
Combining and Shaping Data Using SQL
Combining and Shaping Data Using Python
Integrating Data from Disparate Sources into a Data Warehouse
Working with Streaming Data Using a Data Warehouse
Description
Course info
Level
Beginner
Updated
Jun 21, 2019
Duration
3h 28m
Description

Connecting the dots between data from different sources is becoming the most sought-after skill these days for everyone ranging from business professionals to data scientists. In this course, Combining and Shaping Data, you will gain the ability to connect the dots by pulling together data from disparate sources and shaping it so that extracting connections and relationships becomes relatively easy. First, you will learn how the most common constructs in shaping and combining data stay the same across spreadsheets, programming languages, and databases. Next, you will discover how to use joins and vlookups to obtain wide datasets, and then use pivots to shape that into long form. You will then see how both long and wide data can be aggregated to obtain higher level insights. You will work with Excel spreadsheets and SQL as well as Python. Finally, you will round out the course by integrating data from a variety of sources and working with streaming data, which helps your enterprise gain real-time insights into the world around you. When you are finished with this course, you will have the skills and knowledge to pull together data from disparate sources, including from streaming sources, to construct integrated data models that truly connect the dots.

About the author
About the author

A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
(Music playing) Hi, my name is Janani Ravi, and welcome to this course on Combining and Shaping Data. A little about myself, I have a master's degree in electrical engineering from Stanford and have worked at companies such as Microsoft, Google, and Flipkart. At Google I was one of the first engineers working on real-time collaborative editing in Google Docs, and I hold four patents for its underlying technologies. I currently work on my own startup, Loonycorn, a studio for high quality video content. Connecting the dots is becoming the most sought after skill these days for everyone ranging from business professionals to data scientists. In this course, you will gain the ability to connect the dots by pulling together data from disparate sources and shaping it so that extracting connections and relationships become relatively easy. First, you will learn how the most common constructs in shaping and combining data stay the same across spreadsheets, programming languages, and databases. Next, you will discover how to use joins and VLOOKUPS to obtain wide datasets and then use pivots to shape that into long form. You will then see how both long and wide data can be aggregated to obtain higher level insights. You will work with Excel spreadsheets, SQL, as well as Python. Finally, you will round out the course by integrating data from a variety of sources and working with streaming data, which helps your enterprise gain real-time insights into the world around you. When you're finished with this course, you will have the skills and knowledge to pull together data from disparate sources, including from streaming sources to construct integrated data models that truly connect the dots.