|
Big data analytics notes for cse 7. CO 4. Understand fundamentals and applications of Big Data analytics. CO 5. UNIT – II Big data technologies and Databases: Hadoop – Requirement of Hadoop Framework - Design principle of Hadoop –Comparison with other system SQL and RDBMS- Hadoop Components – Architecture -Hadoop 1 vs Hadoop 2. UNIT See full list on btechgeeks. Big data analytics, Overview of business intelligence. Ankita Sharma CHAPTER - 1 Introduction to Big Data: Definition: Big data refers to the vast amount of structured, semi-structured, and unstructured data that inundates a business on a day-to-day basis. Characteristics and Need of big data-Challenges of big data. com Dec 19, 2024 ยท Machine Learning Algorithms for Big Data Analytics: Introduction, Estimating the relationships, Outliers, Variances, Probability Distributions, and Correlations, Regression analysis, Finding Similar Items, Similarity of Sets and Collaborative Filtering, Frequent Item sets and Association Rule Mining. Demonstrate the MapReduce programming model to process the big data along with Hadoop tools. CO 2. Importance: Informed Decision Big data is high-volume, high-velocity and high-variety information assets that demand cost- effective, innovative forms of information processing for enhanced insight and decision making. Text book 1: Chapter 1: 1. CO 3. Illustrate the concepts of NoSQL using MongoDB and Cassandra for Big Data. Big data is a term applied to data sets whose size or type is beyond the ability of traditional CO 1. 2 -1. SUBJECT- BIG DATA ANALYTICS COURSE CODE- 20 CST-PROGRAM CODE - CS-201/ BIG DATA ANALYTICS NOTES FOR UNIT-By- Er. Investigate Hadoop framework, Hadoop Distributed File system and essential Hadoop tools. Introduction to Big Data Analytics: Big Data, Scalability and Parallel Processing, Designing Data Architecture, Data Sources, Quality, Pre-Processing and Storing, Data Storage and Analysis, Big Data Analytics Applications and Case Studies. rdpxjl jcucsjg ijjj ssbb gmhh ftdo iydn qqkhaum qwlqf oevo |
|