ARCHBISHOP KAVUKATTU CENTRAL LIBRARY
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Data Analytics Essentials You Always Wanted to Know: (Record no. 44948)

MARC details
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003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260629072914.0
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781636511184
040 ## - CATALOGING SOURCE
Transcribing agency AKCL
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Item number SZA-D
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Szasz, Bianca
245 ## - TITLE STATEMENT
Title Data Analytics Essentials You Always Wanted to Know:
Remainder of title From Raw Data to Actionable Insights - Journey Through the Essentials of Data Analytics /
Statement of responsibility, etc. by Bianca Szasz
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. USA:
Name of publisher, distributor, etc. Vibrant Publishers,
Date of publication, distribution, etc. 2024.
490 ## - SERIES STATEMENT
Series statement Self-Learning Management Series
520 ## - SUMMARY, ETC.
Summary, etc. Data Analytics Essentials You Always Wanted To Know is an approachable and captivating guide to understand the complicated world of data<br/><br/><br/>Data analytics is becoming increasingly important in today's data-driven society, and so has the demand for data analysts. Data Analytics Essentials You Always Wanted to Know (Data Analytics Essentials) is a comprehensive yet succinct manual, perfect for you if you are trying to understand the fundamentals of data analytics. It gives a concise introduction to data<br/>analytics and its current applicability.<br/><br/>Upon reading this book, you will get:<br/><br/> A fundamental comprehension of data analytics, including its types<br/>An understanding of data analytics processes, software tools, and a range of analytics methodologies<br/>A comprehension of what daily tasks and procedures the data analysts follow<br/>An investigation into the vast field of big data analytics, covering its possibilities and challenges<br/>An understanding of the existing legal frameworks, as well as ethical and privacy issues in data analytics<br/>Application-based learning using a variety of real-world case studies<br/>This book is a great tool for professionals switching to a career in data analytics and for students who want to learn the basics of data analytics. It will give you a strong foundation by explaining everything in an easy-to-understand language.<br/><br/>Data Analytics Essentials goes beyond a theoretical manual and contains real-world case studies and fun facts to help you enhance your knowledge. The chapter summaries and self- assessment tests along with every chapter will help you test yourself as you move from one concept to the next.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Science
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element AI
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial Intelligence
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine Learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data Mining
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data Analytics
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction to Data Analytics<br/><br/>1.1 What is Data Analytics?<br/><br/>1.2 How is Data Analytics Different From Data Science?<br/><br/>1.3 The Importance of Data Analytics in Today's World<br/><br/>1.4 Brief History of Data Analytics<br/><br/>1.5 Key Concepts in Data Analytics<br/><br/>Quiz<br/><br/>Chapter Summary<br/><br/><br/>2. Data Collection and Management<br/><br/>2.1 Planning for Data Collection<br/><br/>2.2 Sources of Data<br/><br/>2.3 Types of Data<br/><br/>2.4 Data Preprocessing<br/><br/>2.5 Data Storage and Retrieval<br/><br/>Quiz<br/><br/>Chapter Summary<br/><br/><br/>3. Types of Data Analytics<br/><br/>3.1 Descriptive Analytics<br/><br/>3.2 Inferential Analytics<br/><br/>3.3 Predictive Analytics<br/><br/>3.4 Prescriptive Analytics<br/><br/>Quiz<br/><br/>Chapter Summary<br/><br/><br/>4. Techniques and Tools for Data Analytics<br/><br/>4.1 Data Analytics Techniques<br/><br/>4.2 Data Analytics Tools<br/><br/>4.3 Best Practices<br/><br/>Quiz<br/><br/>Chapter Summary<br/><br/><br/>5. What Does a Data Analyst Do?<br/><br/>5.1 The Data Analytics Process<br/><br/>5.2 Defining the Questions<br/><br/>5.3 Collecting Data<br/><br/>5.4 Cleaning the Data<br/><br/>5.5 Analyzing the Data<br/><br/>5.6 Visualizing and Sharing the Findings<br/><br/>Quiz<br/><br/>Chapter Summary<br/><br/><br/>6. Big Data Analytics<br/><br/>6.1 What is Big Data?<br/><br/>6.2 Challenges of Big Data Analytics<br/><br/>6.3 Technologies for Big Data Analytics<br/><br/>6.4 Case Studies in Big Data Analytics<br/><br/>6.5 The Future of Big Data Analytics<br/><br/>Quiz<br/><br/>Chapter Summary<br/><br/><br/>7. Ethics and Privacy in Data Analytics<br/><br/>7.1 Ethics in Data Analytics<br/><br/>7.2 Privacy in Data Analytics<br/><br/>7.3 Regulatory Frameworks for Data Analytics<br/><br/>7.4 Future of Ethics and Privacy in Data Analytics<br/><br/>Quiz<br/><br/>Chapter Summary<br/><br/><br/>8. Real-World Case Studies on Data Analytics<br/><br/>8.1 Case Study 1: Walmart - Transforming Retail through Data Analytics<br/><br/>8.2 Case Study 2: Netflix Recommendation System<br/><br/>8.3 Case Study 3: Improving Healthcare Outcomes with Data<br/><br/>Analytics – the Oxford/AstraZeneca COVID-19 vaccine<br/><br/>Quiz<br/><br/>Chapter Summary<br/><br/><br/>9. Glossary<br/><br/> <br/><br/>10. Bibliography<br/>
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    Dewey Decimal Classification     ARCHBISHOP KAVUKATTU CENTRAL LIBRARY ARCHBISHOP KAVUKATTU CENTRAL LIBRARY 06/29/2026 1199.00   006.312 SZA-D 69303 06/29/2026 1199.00 06/29/2026 Books