Terminologies Used in Big Data Environments – Types of Digital Data – Classification of Digital Data – Introduction to Big Data – Characteristics of Data – Evolution of Big Data – Big Data Analytics – Classification of Analytics – Top Challenges Facing Big Data – Importance of Big Data Analytics – Data Analytics Tools.
Numpy: Numpy Data types, Scipy, Jupyter, Statsmodels and Pandas Package – Scikit learn, R programming .
Introducing Hadoop – Hadoop Overview – RDBMS versus Hadoop – HDFS (Hadoop Distributed File System): Components and Block Replication – Processing Data with Hadoop – Introduction to MapReduce – Features of MapReduce, YARN, HBASE
Data Munging: Introduction to Data Munging, Data Pipeline and Machine Learning in Python – Data Visualization Using Matplotlib – Interactive Visualization with Advanced Data Learning Representation in Python.
Introduction to NoSQL: Types of NoSQL Databases-Key-value store, Document store ,Column family, Graph store, CAP theorem – CAP Theorem NoSQL databases, MongoDB: RDBMS Vs MongoDB – Mongo DB Database Model – Data Types, Sharding –Types of sharding, Introduction to Hive – Hive Architecture – Hive Query Language (HQL).
Reference Book:
1.Alberto Boschetti, Luca Massaron, “Python Data Science Essentials”, Packt Publications, 2nd Edition, 2016. 2. VDT Editorial Services, Big Data, Black Book, Dream Tech Press, 2015. 3. Yuxi (Hayden) Liu, “Python Machine Learning”, Packt Publication, 2017
Text Book:
1.Frank Pane, “Hands On Data Science and Python Machine Learning”, Packt Publishers, 2017. 2. Seema Acharya, Subhashini Chellapan, “Big Data and Analytics”, Wiley, 2015
