DATA MANAGEMENT TOOLS

Paper Code: 
DAC 232
Credits: 
4
Periods/week: 
4
Max. Marks: 
100.00
Objective: 

Students will learn how to start working with MS Excel right from basics to Tables, and advanced in data manipulation with database management system.

Course Outcomes (COs):

 

Course outcome (at course level)

Learning and teaching strategies

Assessment Strategies

Students will be able to:

CO6. Use spreadsheets to perform statistical computations and display numerical and graphical summaries of data sets.

CO7. Use sensitivity analysis on data.

CO8. Use and identify the descriptive statistics for different problems.

CO9. Use of predefined functions in analysis of datasets.

CO10. Analyze the concept of database in data management.

Approach in teaching:

Interactive Lectures, Discussion, Demonstrations, Group activities, Teaching using advanced IT audio-video tools 

Learning activities for the students:

Effective assignments, Giving tasks.

 

Assessment Strategies

Class test, Semester end examinations, Quiz, Practical Assignments, Individual and group projects

 


 

12.00
Unit I: 

Data Tabulation in Excel

Creating a Table, Adding, Deleting new rows or columns, Moving a Table, Removing duplicate rows from a table. Sorting and filtering a table, auto filter, advanced filter, formatting of table.

series, auto fill series, Cell referencing (Relative, Absolute, Mixed).

Data from other sources: Importing external data from different database files. Creating Custom Views of your Worksheet.

 

12.00
Unit II: 

Functions: Functions and its parts, some useful mathematical and statistical Functions in spreadsheet (eg. SUM, COUNT, MAX, MIN, IF, COUNTIF, CEILING, FLOOR, TRUNC, ABS, FACT, INT, LOG, MOD, POWER, ROUND, EXP), logical functions (IF, AND, OR). Date & Time functions (NOW, DATE, TIME, DAY, MONTH, YEAR, HOUR, MINUTE, SECOND).

 

 

12.00
Unit III: 

Decision Making & Advance Spread-Sheet Tools: Financial Functions (PV, NPV, IPR, Rate, FV, PMT, NPER), Vlookup, Hlookup. What if analysis (Data tables, Scenario, Goal seek, Sub-total, Pivot Table), Macros, Protection.

Graphical methods: line graph, bar graph, pie chart, histogram, scatter plot.

Descriptive Statistics (mean, median, mode, standard deviation, sample variance, Range).

 

12.00
Unit IV: 

Introduction: Database Management Systems

Definition, Characteristics of DBMS, Architecture & Security, Types of Data Models, Concepts and constraints of RDBMS, Introduction to Structured Query Language, MySql Installer, Download sample Database, Loading Sample Database.

 

12.00
Unit V: 

Data definition and Manipulation

SQL Process, SQL Commands – DDL, DML, DCL, DQL, SQL Constraints, Data Integrity, Data Types, SQL Operators, Expressions, Querying Database, Retrieving result sets, Sub Queries, Syntax for various Clauses of SQL, Functions and Joins.

 

ESSENTIAL READINGS: 
  1. Microsoft Excel 2016 - Data Analysis and Business Modeling PHI Publication 2017
  2. Denise Etheridge,“ Excel Data Analysis”,Wiley Publication,Third Edition
  3. R. Elmarsi and S.B. Navathe, “Fundamentals of Database Systems”, Addison Wesley, 7th Ed., 2015.
  4. James R. Groff & Paul N. Weinberg, “The Complete Reference SQL”, McGraw Hill Education, 3 Edition, 2017

 

REFERENCES: 

REFERENTIAL  READING: 

  1.  Abraham Silberschatz, Henry Korth, S. Sudarshan, “Database Systems Concepts”, 7th Edition, McGraw Hill, 2019.
  2.  Bipin Desai, “An Introduction to Database Systems”, Galgotia Publications, 2015.
  3.  Hector Guerrero ,“Excel Data Analysis - Modeling and Simulation”, Springer
  4. Financial Analysis and Modeling using Excel and VBA: Chandan Sengupta, Wiley
  5. Chris Newman ,”Sams Teach Yourself MySQL in 10 Minutes” , Sams Publishing; 1 edition (May 19, 2006)

 

Journals:

E-RESOURCES: 

 

 

 

 

Academic Year: 
2023-24
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