SQL for Data Analytics: Perform fast and efficient data analysis with the power of SQL - Tapa blanda

Upom Malik; Matt Goldwasser; Benjamin Johnston

 
9781789807356: SQL for Data Analytics: Perform fast and efficient data analysis with the power of SQL
Tapa blanda
ISBN 10: 1789807352 ISBN 13: 9781789807356
Editorial: Packt Publishing, 2019

Sinopsis

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 business insights from data, this book is for you.

SQL for Data Analytics covers everything you need progress from simply knowing basic SQL to telling stories and identifying trends in data. You ll be able to start exploring your data by identifying patterns 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 understand how to become productive with SQL with the help of profiling and automation to gain insights faster.

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

What you will learn

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

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.

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

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca de los autores

Upom Malik is a data science and analytics leader who has worked in the technology industry for over eight years. He holds 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 throughout the United States. He uses SQL and other tools to solve complex challenges in finance, energy, and consumer technology. Outside of work, he enjoys reading, hiking the trails of the Northeastern United States, and savoring ramen bowls from around the world.

Matt Goldwasser is Vice President and Head of AI and Data Science for Global Distribution at T. Rowe Price. He leads strategic initiatives using machine learning (ML) and advanced analytics across the organization. With over 8 years at T. Rowe Price, he brings expertise in applied data science, MLOps, and AWS, with a strong focus on operationalizing AI at scale. Previously, Matt held multiple roles at OnDeck, leading marketing analytics and building predictive models and automated ML pipelines. He also worked in data engineering, risk analysis, and product management at Millennium Management, GE, and the Port Authority of NY and NJ. He is known for turning complex challenges into scalable solutions and bridging strategy with hands-on innovation.

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 ML, 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 a first-class honors bachelor's degree in both engineering and medical science from the University of Sydney, Australia.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Packt Publishing
Año de publicación
2019
Idioma
Inglés
ISBN 10 
1789807352
ISBN 13 
9781789807356
Encuadernación
Tapa blanda
Número de páginas
386
Contacto del fabricante
no disponible
Persona responsable
no disponible