About this book
Summary
Dive into the World of Data Analytics with This 2025 Guide! Hey there, if you're looking to master data analytics from the ground up, this book is your ultimate companion. It kicks off with the basics in Part I, covering the data analytics landscape, including modern lifecycles like CRISP-DM and agile workflows. You'll explore core data structures: structured, unstructured, and semi-structured. Learn about key roles like data analyst, scientist, and ML engineer. Get an intro to AI and generative AI in analytics. Move to statistical foundations: descriptive stats, distributions, inferential methods like hypothesis testing and confidence intervals. Dive into correlation, linear regression, and applied linear algebra. Then, Python programming: setup, Pandas for manipulation, NumPy for computing, Scikit-learn for modeling. Part II dives into the workflow: relational databases, advanced SQL with joins, window functions, optimization. Data sourcing from enterprises, APIs, web scraping—including AI-powered and ethical aspects. Data prep: profiling, deduplication, missing data handling, outliers, transformations. Exploratory analysis: univariate, bivariate, multivariate with PCA, communicating findings. What sets this book apart is its 2025 focus—blending timeless foundations with cutting-edge trends like AI automation, real-time streaming, and cloud lakehouses that older books overlook. Unlike generic guides, it packs real-time case studies, like Uber's AI agents or Tesla's data structures, plus job skill enhancements tied to market data showing ML engineer growth at +34%. It bridges gaps other texts miss, like ethical scraping or sentiment analysis for brands, with hands-on Python applications and career pathways. No fluff; it's practical, updated for today's job market, giving you a competitive edge in high-demand roles. This author has no affiliation with the board and it is independently produced under nominative fair use.Book information
Genre
Technology, Science and Nature
Length
5 hrs 25 mins
Publish date
Nov 15, 2025
Language
English
About the Author
Azhar ul Haque Sario
Table of Contents
1PART I: FOUNDATIONS OF DATA ANALYTICS
11Business Intelligence Tools and Enterprise Reporting
2The Data Analytics Landscape (2025)
12Data Governance, Quality, and Ethical Practice
3Statistical and Probabilistic Foundations for Analytics
13PART IV: ADVANCED MODELING AND SPECIALIZATIONS
4Data Analytics Programming with Python
14Applied Supervised Machine Learning for Analytics
5PART II: THE CORE ANALYTICS WORKFLOW
15Unsupervised Machine Learning: Clustering and Dimensionality Reduction