The Applied SQL Data Analytics Workshop: Develop your practical skills and prepare to become a professional data analyst

by Matt Goldwasser, Upom Malik, Benjamin Johnston

Overview

Take a step-by-step approach to learning SQL data analysis in this interactive workshop that uses fun exercises and activities to make learning data analytics for beginners easy and approachable.

Key Features

• Explore ways to use SQL for data analytics and gain key insights from your data
• Study advanced analytics, such as geospatial and text analytics
• Discover ways to integrate your SQL pipelines with other analytics technologies

Book Description

Every day, businesses operate around the clock and a huge amount of data is generated at a rapid pace. Hidden in this data are key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. Are you ready to enter the exciting world of data analytics and unlock these useful insights?

Written by a team of expert data scientists who have used their data analytics skills to transform businesses of all shapes and sizes, The Applied SQL Data Analytics Workshop is a great way to get started with data analysis, showing you how to effectively sieve and process information from raw data, even without any prior experience.

The book begins by showing you how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you'll learn how to write SQL queries to aggregate, calculate and combine SQL data from sources outside of your current dataset. You'll also discover how to work with different data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you'll finally be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation.

By the end of The Applied SQL Data Analytics Workshop, you'll have the skills you need to start identifying patterns and unlocking insights in your own data. You will be capable of looking and assessing data with the critical eye of a skilled data analyst.

What you will learn

• Understand what data analytics is and why it is important
• Experiment with data analytics using basic and advanced queries
• Interpret data through descriptive statistics and aggregate functions
• Export data from external sources using powerful SQL queries
• Work with and manipulate data using SQL joins and constraints
• Speed up your data analysis workflow by automating tasks and optimizing queries

Who this book is for

If you are a database engineer who is looking to transition into analytics or someone who knows SQL basics but doesn't know how to use it to create business insights, then this book is for you.

Product Details

ISBN-13:	9781800205376
Publisher:	Packt Publishing
Publication date:	02/28/2020
Sold by:	Barnes & Noble
Format:	eBook
Pages:	484
Sales rank:	330,916
File size:	23 MB
Note:	This product may take a few minutes to download.

About the Author

Matt Goldwasser is a lead data scientist at T. Rowe Price, where he leverages machine learning techniques to solve business problems. Upom Malik is a data scientist who has been working in the technology industry for over 6 years. He uses SQL and other tools to solve interesting challenges in finance, energy, and consumer tech. Benjamin Johnston is a senior data scientist and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition to solution research and development, through to final deployment.
Matt Goldwasser is the Head of Applied Data Science at the T. Rowe Price NYC Technology Development Center. Prior to his current role, Matt was a data science manager at OnDeck, and prior to that, he was an analyst at Millennium Management. Matt holds a bachelor of science in mechanical and aerospace engineering from Cornell University.
Upom Malik is a data science and analytics leader who has worked in the technology industry for over 8 years. He has a master's degree in chemical engineering from Cornell University and a bachelor's degree in biochemistry from Duke University. As a data scientist, Upom has overseen efforts across machine learning, experimentation, and analytics at various companies across the United States. He uses SQL and other tools to solve interesting challenges in finance, energy, and consumer technology. Outside of work, he likes to read, hike the trails of the Northeastern United States, and savor ramen bowls from around the world.
Benjamin Johnston is a senior data scientist for one of the world's leading data-driven MedTech companies and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition to solution research and development, through to final deployment. He is currently completing his Ph.D. in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years of experience in medical device design and development, working in a variety of technical roles, and holds first-class honors bachelor's degrees in both engineering and medical science from the University of Sydney, Australia.

Table of Contents

Table of Contents

1. Introduction to SQL for Analytics
2. SQL for Data Preparation
3. Aggregate and Window Functions
4. Importing and Exporting Data
5. Analytics Using Complex Data Types
6. Performant SQL
7. The Scientific Methods and Applied Problem Solving