Chapter 1

Introduction to Big Data

The 5 V's of Big Data and its applications

medium • 1 min read

Big data infrastructure and distributed storage

medium • 2 min read

Hadoop ecosystem overview (HDFS, YARN, MapReduce)

medium • 3 min read

Data lakes vs Data warehouses

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ETL versus ELT pipelines

medium • 5 min read

Chapter 2

Data Exploration and Preprocessing

Handling missing data and outliers

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Data transformation, scaling, and normalization

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Exploratory Data Analysis (EDA) techniques

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Feature engineering methodologies

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Data visualization principles and libraries (Matplotlib, Seaborn)

medium • 5 min read

Chapter 3

Apache Spark and In-Memory Computation

Spark architecture, RDDs, and DataFrames/Datasets

medium • 1 min read

Spark SQL and catalyst optimizer

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Spark Streaming and real-time analytics

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Machine Learning with Spark MLlib

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GraphX and graph processing

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Chapter 4

Advanced Big Data Analytics

Mining massive datasets (PageRank, Locality Sensitive Hashing)

medium • 1 min read

Recommender systems (Collaborative filtering, matrix factorization)

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Time series analysis and forecasting methodologies

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Market Basket Analysis and Apriori algorithm

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Sentiment analysis and web scraping

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Chapter 5

Data Science in Production

Model deployment, API creation, and monitoring

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MLOps lifecycle and reproducibility

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A/B testing and experimentation frameworks

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Data governance, ethics, and privacy constraints

medium • 4 min read

Case studies of big data in modern enterprises

medium • 5 min read