Business Data Analytics detailed syllabus for Industrial Engineering & Management (IEM) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the IEM students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Industrial Engineering & Management 5th Sem scheme and its subjects, do visit IEM 5th Sem 2021 regulation scheme. For Professional Elective-IV scheme and its subjects refer to IEM Professional Elective-IV syllabus scheme. The detailed syllabus of business data analytics is as follows.
Course Objectives:
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Unit I
OVERVIEW OF BUSINESS ANALYTICS 9
Introduction – Drivers for Business Analytics – Applications of Business Analytics: Marketing and Sales, Human Resource, Healthcare, Product Design, Service Design, Customer Service and Support – Skills Required for a Business Analyst – Framework for Business Analytics Life Cycle for Business Analytics Process.
Unit II
ESSENTIALS OF BUSINESS ANALYTICS 9
Descriptive Statistics – Using Data – Types of Data – Data Distribution Metrics: Frequency, Mean, Median, Mode, Range, Variance, Standard Deviation, Percentile, Quartile, z-Score, Covariance, Correlation – Data Visualization: Tables, Charts, Line Charts, Bar and Column Chart, Bubble Chart, Heat Map – Data Dashboards.
Unit III
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Unit IV
ANALYTICS USING HADOOP AND MAPREDUCEFRAM EWORK 9
Introducing Hadoop – RDBMS versus Hadoop – Hadoop Overview – HDFS (Hadoop Distributed File System) – Processing Data with Hadoop – Introduction to MapReduce -Features of MapReduce – Algorithms Using Map-Reduce: Matrix-Vector Multiplication, Relational Algebra Operations, Grouping, and Aggregation – Extensions to MapReduce
Unit V
OTHER DATA ANALYTICAL FRAMEWORKS 9
Overview of Application Development Languages for Hadoop – PigLatin – Hive – Hive Query Language (HQL) – Introduction to Pentaho, JAQL – Introduction to Apache: Sqoop, Drill, and Spark, Cloudera Impala – Introduction to NoSQL Databases – Hbase and MongoDB.
Course Outcomes:
On completion of the course, the student will be able to:
- Identify the real world business problems and model with analytical solutions.
- Solve analytical problem with relevant mathematics background knowledge.
- Convert any real world decision making problem to hypothesis and apply suitable statistical testing.
- Write and Demonstrate simple applications involving analytics using Hadoop and MapReduce
- Use open source frameworks for modeling and storing data.
Reference Books:
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For detailed syllabus of all the other subjects of Industrial Engineering & Management 5th Sem, visit IEM 5th Sem subject syllabuses for 2021 regulation.
For all Industrial Engineering & Management results, visit Anna University IEM all semester results direct link.