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.
Table of Contents
- Introduction to SQL for Analytics
- SQL for Data Preparation
- Aggregate and Window Functions
- Importing and Exporting Data
- Analytics Using Complex Data Types
- Performant SQL
- The Scientific Methods and Applied Problem Solving
Matt Goldwasser is a manager on the data science team at T. Rowe Price, where he has leveraged machine learning techniques to solve business problems. In this role, he has helped the company build its data science capability from the ground up in the newly formed technology development center. Prior to his current role, Matt was a data science manager at OnDeck, where he led efforts to use machine learning to increase customer acquisition. He has a bachelors's in mechanical and aerospace engineering from Cornell University, where he met his wife. In his spare time, he enjoys teaching his infant son the basics of data science.
Upom Malik is a data scientist who has worked in the technology industry for over 6 years. He has a master's degree in chemical engineering from Cornell University and a bachelor's degree in biochemistry from Duke University. He uses SQL and other tools to solve interesting challenges in finance, energy, and consumer technologies. While working on analytical problems, he has lived out of a suitcase and spent a year as a digital nomad. 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 PhD in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years' 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.
