Data Analytics Essentials You Always Wanted To Know: Self Learning Management

Data Analytics Essentials You Always Wanted To Know

Self Learning Management

Vibrant Publishers and Dr. Bianca Szasz

Published by Vibrant Publishers, 2024.

While every precaution has been taken in the preparation of this book, the publisher assumes no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein.

DATA ANALYTICS ESSENTIALS YOU ALWAYS WANTED TO KNOW

First edition. February 29, 2024.

Copyright © 2024 Vibrant Publishers and Dr. Bianca Szasz.

ISBN: 978-1636511191

Written by Vibrant Publishers and Dr. Bianca Szasz.

Online Resources

Congratulations! You now have access to practical templates of the Data Analytics concepts that you will learn in this book. Data analytics often involves the use of structured data tables to organize information in a way that's conducive to more efficient analysis. Here are the titles of ten table templates that will help you organize data for efficient analysis.

They are:

●Data Quality Assessment Table

●User Demographic Analysis Table

●Sales Performance Analysis Table

●Website Traffic Analysis Table

●Customer Feedback Analysis Table

●Inventory Management Analysis Table

●Marketing Campaign Analysis Table

●Financial Transaction Analysis Table

●Product Quality Analysis Table

●Employee Performance Analysis Table

●Additional videos and articles for reference

To access the templates, follow the steps below:

1.Go to www.vibrantpublishers.com

2.Click on the ‘Online Resources’ option on the Home Page

3.Login by entering your account details (or create an account if you don’t have one)

4.Go to the Self-Learning Management series section on the Online Resources page

5.Click the ‘Data Analytics Essentials You Always Wanted To Know’ link and access the templates.

More information on how to use the templates

Each of these tables is designed to gather and organize data critical for analytics in various domains, allowing for efficient querying, reporting, and decision-making processes in organizations. In other words, the tables help the users make the first steps in data analytics. The templates can be used in a variety of industries and for a variety of purposes. Here is more information on how to use them.

Data Quality Assessment: The Data Quality Assessment Table can be used to assess the quality of a dataset by identifying and correcting errors, inconsistencies, and missing values. This is an important step in any data analysis project, as it ensures that the results are accurate and reliable.

User Demographic Analysis: The User Demographic Analysis Table can be used to analyze the demographic characteristics of a user base, such as age, gender, location, and occupation. This information can be used to better understand user needs and preferences, and to develop more targeted marketing and product development strategies.

Sales Performance Analysis: The Sales Performance Analysis Table can be used to analyze sales data over time to identify which type of products are most often sold, which products are more profitable, or in what sales region the company has the most sales. This information can be used to set sales goals, develop sales strategies, and motivate sales teams.

Website Traffic Analysis: The Website Traffic Analysis Table can be used to analyze website traffic data to identify popular pages, visitor sources, and visitor behavior. This information can be used to improve the user experience, optimize marketing campaigns, and increase website conversions.

Customer Feedback Analysis: The Customer Feedback Analysis Table can be used to analyze customer feedback data to identify areas for improvement and develop new products and services. This information can also be used to track customer satisfaction levels over time.

Inventory Management Analysis: The Inventory Management Analysis Table can be used to track inventory levels, identify trends in demand, and optimize inventory levels. This information can help businesses to avoid stockouts and overstocking and to improve their bottom line.

Marketing Campaign Analysis: The Marketing Campaign Analysis Table can be used to track the results of marketing campaigns and identify which campaigns are most effective. This information can be used to optimize marketing budgets and improve campaign ROI.

Financial Transaction Analysis: The Financial Transaction Analysis Table can be used to track and analyze financial transactions to identify trends, patterns, and potential fraud. This information can be used to improve financial management and make better financial decisions.

Product Quality Analysis: The Product Quality Analysis Table can be used to track and analyze product quality data to identify areas for improvement. This information can be used to improve product design, manufacturing processes, and quality control procedures.

Employee Performance Analysis: The Employee Performance Analysis Table can be used to track and analyze employee performance data to identify top performers, areas for improvement, and training needs. This information can be used to develop performance management plans, reward high-performing employees, and improve employee engagement.

Overall, the downloadable 10 Excel templates related to the data analytics field are a valuable resource for anyone who wants to use data to improve their work. The templates are easy to use and can be customized to meet the specific needs of each user.

Here are some specific examples of how the templates can be used in different industries:

E-commerce: The User Demographic Analysis Table can be used to identify the target market for an e-commerce company. The Sales Performance Analysis Table can be used to track sales data over time and identify trends. The Website Traffic Analysis Table can be used to identify popular products and pages.

Retail: The Inventory Management Analysis Table can be used to track inventory levels and avoid stockouts. The Marketing Campaign Analysis Table can be used to track the results of marketing campaigns and identify which campaigns are most effective. The Customer Feedback Analysis Table can be used to identify areas for improvement and develop new products and services.

Manufacturing: The Product Quality Analysis Table can be used to track and analyze product quality data to identify areas for improvement. The Financial Transaction Analysis Table can be used to track and analyze financial transactions to identify trends, patterns, and potential fraud.

Happy self-learning!

Data Analytics Essentials

You Always Wanted To Know

First Edition

© 2024, By Vibrant Publishers, USA. All rights reserved. No part of this publication

may be reproduced or distributed in any form or by any means, or stored in a database

or retrieval system, without the prior permission of the publisher.

Paperback ISBN 10: 1-63651-118-X

Paperback ISBN 13: 978-1-63651-118-4

Ebook ISBN 10: 1-63651-119-8

Ebook ISBN 13: 978-1-63651-119-1

Hardback ISBN 10: 1-63651-120-1

Hardback ISBN 13: 978-1-63651-120-7

Library of Congress Control Number: 2022938403

This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. The Author has made every effort in the preparation of this book to ensure the accuracy of the information. However, information in this book is sold without warranty either expressed or implied. The Author or the Publisher will not be liable for any damages caused or alleged to be caused either directly or indirectly by this book.

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SELF-LEARNING MANAGEMENT SERIES

About the Author

Bianca Szasz is a Romanian with a Ph.D. in Space Engineering from Japan. With over 14 years of experience in engineering and a dedicated focus of 4 years on data analytics, her journey is proof of the transformative potential of data.

She played a pivotal role in the Shinen2 University space mission. Next, she embraced the role of Special Assistant Professor at Nagoya University where she guided graduate students as part of the Leadership Development Program for Space Exploration and Research.

Her book Data Analytics Essentials is the result of both her in-depth knowledge of the subject and her intellectual curiosity. What ignited her interest in data analytics was its potential to transform entire sectors.

She has used data analytics in a variety of innovative projects over her career, notably to perform post-processing of the wind tunnel test results in Germany, and analyzing high enthalpy heating test results during her doctoral research in Japan. Due to these experiences and many others, she was able to see firsthand how data analytics tremendously boosts research and engineering projects. Her passion for data analytics goes beyond applications in the workplace - she has a strong desire to educate those who are unfamiliar with data analytics.

What experts say about this book!

I think this text is a comprehensive yet succinct manual. It gives a usable introduction to data analytics and is easy to read and comprehend. An added benefit is that the book contains real-world case studies and interesting facts to help enhance existing knowledge.

A key strength of this text is the option to choose the topics that you want to focus on and the resources that you want to use. This flexibility makes self-directed learning a great option for busy professionals who want to add data analytics skills to their repertoire. If you're interested in self-directed learning for data analytics, there are a few things you need to do to get started, and this text will help!

– David E Reva, Instructor - CIS,

Kalamazoo Valley Community College

The book is written in a way that makes it easier for complete beginners like me to understand the world of data analytics. Every chapter has a helpful summary and a quiz to test your knowledge. Fascinating!

– Chiara Colombo, Sr Contracts Analyst,

Yahoo! Inc.

An absolutely valuable book that can help structure your knowledge in data science and data analytics. If you are at an advanced level, the book may not be for you. However if you are looking to shape your experience or are interested in switching careers to data analytics, this book is a great help. It provides an overview of the field, presents a structured knowledge set, and gives a good understanding of the topic.

– Darya Yegorina, DBA, Chief of Staff Strategy & Sales Ops,

Verizon

This book is a comprehensive and detailed map of Data Analytics, which professionals can use in the initial years of their career. The book covers everything you need to know at the beginning of the journey and will help you make wise decisions such as which software tool to use to solve a specific problem and what are its advantages and disadvantages. The book abounds with practical examples, quizzes, and good practice tips.

– Cătălin Neacșu,

Doctor of Philosophy (Ph.D) in Physics

The book is an excellent resource for anyone interested in data analytics. Whether you're a student, professional, or simply a curious learner, this book provides the knowledge and tools needed to navigate and excel in the world of data analytics.

– Tamer Abu Rouk,

Space Engineer

Great book! It helped me understand all we can do with data analytics tools and, thanks to this book, I have started to implement some data analytics techniques at my own job!

– Sara Szasz,

Chief Economist

This book is excellent as it provides a versatile guide to data analytics for all levels, catering both to beginners as well as for those more experienced in the field. Beginners will appreciate how it simplifies complex concepts, offering clear, structured chapters that make learning the basics both manageable and engaging. For seasoned analysts, the book is a valuable reference, delving into advanced topics with clarity and offering practical, real-world applications of various analytics tools.

– Dana Neacșu,

Competitive Analyst

Table of Contents

1Introduction to Data Analytics

1.1 What is Data Analytics?

1.2 How is Data Analytics Different From Data Science?

1.3 The Importance of Data Analytics in Today's World

1.4 Brief History of Data Analytics

1.5 Key Concepts in Data Analytics

Quiz

Chapter Summary

2Data Collection and Management

2.1 Planning for Data Collection

2.2 Sources of Data

2.3 Types of Data

2.4 Data Preprocessing

2.5 Data Storage and Retrieval

Quiz

Chapter Summary

3Types of Data Analytics

3.1 Descriptive Analytics

3.2 Inferential Analytics

3.3 Predictive Analytics

3.4 Prescriptive Analytics

Quiz

Chapter Summary

4Techniques and Tools for Data Analytics

4.1 Data Analytics Techniques

4.2 Data Analytics Tools

4.3 Best Practices

Quiz

Chapter Summary

5What Does a Data Analyst Do?

5.1 The Data Analytics Process

5.2 Defining the Questions

5.3 Collecting Data

5.4 Cleaning the Data

5.5 Analyzing the Data

5.6 Visualizing and Sharing the Findings