About the Book
- Page ID
- 52827
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This book provides a practical foundation in Data Analytics, designed for readers who may already have some familiarity with on-premises or cloud computing environments but are new to the broader analytics landscape. It introduces the concepts, processes, and tools used to transform raw data into meaningful information that can support understanding, decision-making, and real-world problem-solving.
Beginning with the foundations of data analytics and the roles of analysts, scientists, and engineers, the book follows the data journey from collection and ingestion through cleaning, preparation, exploratory analysis, and statistical reasoning. It then explores data visualization and storytelling, predictive analytics and machine learning, business intelligence, and programming-based analytics using tools such as Python, R, SQL, and Jupyter Notebooks.
Throughout the book, it connects technical concepts to practical applications, industry examples, hands-on exercises, and case studies. The goal is not simply to introduce analytics tools, but to help readers understand how data moves through an analytics workflow, how analytical choices are made, and how insights can be communicated effectively across traditional, cloud, and emerging data environments.