The amount of data generated continues to grow rapidly, making it increasingly important for businesses to be able to wrangle this data and understand it quickly and efficiently. Although data wrangling can be challenging, with the right tools and techniques you can efficiently handle enormous amounts of unstructured data.
The book starts by introducing you to the basics of SQL, focusing on the core principles and techniques of data wrangling. You’ll then explore advanced SQL concepts like aggregate functions, window functions, CTEs, and subqueries that are very popular in the business world. The next set of chapters will walk you through different functions within SQL query that cause delays in data transformation and help you figure out the difference between a good query and bad one. You’ll also learn how data wrangling and data science go hand in hand. The book is filled with datasets and practical examples to help you understand the concepts thoroughly, along with best practices to guide you at every stage of data wrangling.
By the end of this book, you’ll be equipped with essential techniques and best practices for data wrangling, and will predominantly learn how to use clean and standardized data models to make informed decisions, helping businesses avoid costly mistakes.
publication date
2023-07-31
what you will learn
Build time series models using data wrangling
Discover data wrangling best practices as well as tips and tricks
Find out how to use subqueries, window functions, CTEs, and aggregate functions
Handle missing data, data types, date formats, and redundant data
Build clean and efficient data models using data wrangling techniques
Remove outliers and calculate standard deviation to gauge the skewness of data
key features
Implement query optimization during data wrangling using the SQL language with practical use cases * Master data cleaning, handle the date function and null value, and write subqueries and window functions * Practice self-assessment questions for SQL-based interviews and real-world case study rounds
approach
End-to-End Data Wrangling Principles have been curated with step-by-step explanations of essential concepts, practical examples, and self-assessment questions. You will begin by exploring SQL language and the best way to make use of SQL language to apply data wrangling concepts
audience
This book is for data analysts looking for effective hands-on methods to manage and analyze large volumes of data using SQL. The book will also benefit data scientists, product managers, and basically any role wherein you are expected to gather data insights and develop business strategies using SQL as a language. If you are new to or have basic knowledge of SQL and databases and an understanding of data cleaning practices, this book will give you further insights into how you can apply SQL concepts to build clean, standardized data models for accurate analysis.
short description
This book is an essential guide for anyone seeking to transform raw, unstructured data into meaningful insights. It simplifies the complex process of data wrangling by leveraging SQL commands such as aggregate functions, subqueries, and window functions, and is suitable for professionals looking to master the art of data wrangling.
subtitle
A hands-on guide to manipulating, wrangling, and engineering data using SQL
keywords
Data Analysis, Data Modeling, Data Wrangling, Data Aggregation, Data Transformation, Data Processing, SQL, CTE, Windows Function, Messy Data, Null Values, Data Cleaning, Data Types, Sub Queries, Data Formats, SQL Commands, SQL Syntax, Data Model, Time series model, Redundant Data
Product ISBN
9781837630028
