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SQL for Data Analytics Upom Malik

SQL for Data Analytics By Upom Malik

SQL for Data Analytics by Upom Malik

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Condition - Very Good
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Summary

SQL for Data Analytics teaches everything you need to know to progress from basic SQL to identifying trends and creating compelling narratives with data. With this book, you will be able to look at data with the critical eye of an analytics professional and extract meaningful insights that will improve your business.

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SQL for Data Analytics Summary

SQL for Data Analytics: Perform fast and efficient data analysis with the power of SQL by Upom Malik

Take your first steps to become a fully qualified data analyst by learning how to explore large relational datasets

Key Features
  • Explore a variety of statistical techniques to analyze your data
  • Integrate your SQL pipelines with other analytics technologies
  • Perform advanced analytics such as geospatial and text analysis
Book Description

Understanding and finding patterns in data has become one of the most important ways to improve business decisions. If you know the basics of SQL, but don't know how to use it to gain the most effective business insights from data, this book is for you.

SQL for Data Analytics helps you build the skills to move beyond basic SQL and instead learn to spot patterns and explain the logic hidden in data. You'll discover how to explore and understand data by identifying trends and unlocking deeper insights. You'll also gain experience working with different types of data in SQL, including time-series, geospatial, and text data. Finally, you'll learn how to increase your productivity with the help of profiling and automation.

By the end of this book, you'll be able to use SQL in everyday business scenarios efficiently and look at data with the critical eye of an analytics professional.

Please note: if you are having difficulty loading the sample datasets, there are new instructions uploaded to the GitHub repository. The link to the GitHub repository can be found in the book's preface.

What you will learn
  • Perform advanced statistical calculations using the WINDOW function
  • Use SQL queries and subqueries to prepare data for analysis
  • Import and export data using a text file and psql
  • Apply special SQL clauses and functions to generate descriptive statistics
  • Analyze special data types in SQL, including geospatial data and time data
  • Optimize queries to improve their performance for faster results
  • Debug queries that won't run
  • Use SQL to summarize and identify patterns in data
Who this book is for

If you're a database engineer looking to transition into analytics, or a backend engineer who wants to develop a deeper understanding of production data, you will find this book useful. This book is also ideal for data scientists or business analysts who want to improve their data analytics skills using SQL. Knowledge of basic SQL and database concepts will aid in understanding the concepts covered in this book.

About Upom Malik

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. 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. 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.

Table of Contents

Table of Contents
  1. Understanding and Describing Data
  2. The Basics of SQL for Analytics
  3. SQL for Data Preparation
  4. Aggregate Functions for Data Analysis
  5. Window Functions for Data Analysis
  6. Importing and Exporting Data
  7. Analytics Using Complex Data Types
  8. Performant SQL
  9. Using SQL to Uncover the Truth - A Case Study

Additional information

CIN1789807352VG
9781789807356
1789807352
SQL for Data Analytics: Perform fast and efficient data analysis with the power of SQL by Upom Malik
Upom Malik
Used - Very Good
Paperback
Packt Publishing Limited
2019-08-23
386
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

Customer Reviews - SQL for Data Analytics