Data Analytics Essentials You Always Wanted To Know (Self-Learning Management Series)

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Upon reading this book, you will get: - A fundamental comprehension of data analytics, including its types- An understanding of data analytics processes, software tools, and a range of analytics methodologies - A comprehension of what daily tasks and procedures the data analysts follow - An investigation into the vast field of big data analytics, covering its possibilities and challenges- An understanding of the existing legal frameworks, as well as ethical and privacy issues in data analytics - Application-based learning using a variety of real-world case studies From raw data to actionable insights - journey through the essentials of data analytics. Data Analytics Essentials You Always Wanted To Know is an approachable and captivating guide to understand the complicated world of data 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 analytics and its current applicability. 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. 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.

Author(s): Bianca Szasz
Series: Self-Learning Management Series
Publisher: Vibrant Publishers
Year: 2024

Language: English
Pages: 218

Introduction to Data Analytics
1.1: What is Data Analytics?
1.2: How different is Data Analytics 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
Data 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
Types of Data Analytics
3.1: Descriptive Analytics
3.2: Inferential Analytics
3.3: Predictive Analytics
3.4: Prescriptive Analytics
Quiz
Chapter Summary
Techniques and Tools for Data Analytics
4.1: Data Analytics Techniques
4.2: Data Analytics Tools
4.3: Best Practices
Quiz
Chapter Summary
What 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
Quiz
Chapter Summary
Big Data Analytics
6.1: What is Big Data?
6.2: Challenges of Big Data Analytics
6.3: Technologies for Big Data Analytics
6.4: Case Studies in Big Data Analytics
6.5: The Future of Big Data Analytics
Quiz
Chapter Summary
Ethics and Privacy in Data Analytics
7.1: Ethics in Data Analytics
7.2: Privacy in Data Analytics
7.3: Regulatory Frameworks for Data Analytics
7.4: Future of Ethics and Privacy in Data Analytics
Quiz
Chapter Summary
Real-World Case Studies on Data Analytics
8.1: Case Study 1: Walmart - Transforming Retail through Data Analytics
8.2: Case Study 2: Netflix Recommendation System
8.3: Case Study 3: Improving Healthcare Outcomes with Data Analytics – the Oxford/AstraZeneca COVID-19 vaccine
Quiz
Chapter Summary
Glossary
Bibliography