Business Intelligence Master Program

Business Intelligence Master Program

Business Intelligence Masters Program Training

Business Intelligence Master Program in Business Analytics equips candidates with the skill sets required for managerial, techno-functional roles in analytics. Its curriculum has been uniquely designed to meet these features and provides exposure to relevant tools like SQL, Data Warehousing, Informatica, Microsoft BI & Tableau. The Business Intelligence Master Program provides the right exposure to real-world applications, ensuring that the professionals are equipped to apply their learning in the industry. The industry-oriented pedagogy, hands-on exposure, and highly acclaimed faculty help the candidates gain analytics competencies thereby preparing them for business and techno-functional roles in analytics.

About the Program

During an Business Intelligence and Analytics degree, students learn how to combine and make use of statistics, data science and computer engineering, while also developing analytical and mathematical skills.The Business Intelligence Master program is designed to hone your expertise in data analytics and help you master the implementation of data science concepts such as data exploration, visualization, and hypothesis testing. Our Business Analytics course will train you to apply statistics and predictive analytics techniques in a business environment, transforming you to become job-ready.

Learning Path Curriculum

Establish a conceptual understanding of business intelligence (BI) and analytics, and acquire practical, tool-based skills. This learning path covers everything from Microsoft Power BI and IBM Crystal Reports to Looker, Tableau, and Google Analytics.

Theory, Terminology, and Concepts

  • Client/Server Concepts
  • Database and Database Objects

Data Definition using SQL

  • Databases
  • Data Types
  • Tables
  • Constraints and Indexes
  • Views

Basic Data Manipulation using SQL

  • Recurring SQL Constructs
  • Adding data
  • Modifying data
  • Removing data
  • Searching data

Advanced Data Manipulation using SQL

  • Expressions
  • Grouping and Aggregate Functions
  • Joining Tables

Transactions

  • Transaction Concepts
  • SQL for working with Transaction

Import/Export

  • Tools for Import/Export
  • SQL for Import/Export

Subject-Oriented
Data warehouses are mainly used for our analyzing. Normally it is used for Top N Analysis of our company data. Say like who is the Best customer for last 5 year?. This characteristic shows the subject matter.
Time-Variant
Want to introduce the new trend in your product then need to analyze a large amount of data. This type totally helps us to introduce new tricks in our business.
Nonvolatile
Once data entry into the warehouse, then it should not be changed. Mainly data warehousing concepts use to analyze what has occurred.
Integrated
Integrated is almost equal to subject-oriented characteristics. Put data inconsistent format which we got from different sources. Need to troubleshoot the naming conflicts in this process.

Working with Informatica Developer 9

  • GUI, Mappings, Mapplets, Transformations, Content Sets, Data Objects

Analyst Collaboration

  • Reviewing information from the Analyst
  • Comments/Tags
  • Creating/adding to Reference tables

Developer Profiling

  • Join Analysis Profiling
  • Column Profiling
  • Multi-Object Profiling
  • Mappings and transformations
  • Mid-stream profiling
  • Comparative profiling

Data Standardization

  • Cleanse, transform and parse data
  • Develop data standardization mapplets and mappings

Matching

  • Grouping data
  • Analyze Detail Report
  • DQ Matching
  • Cluster Analysis Report
  • Matching Mapplets

Identity Matching

  • Build Matching mappings using Identity matching
  • Identity Populations and Strategies

Consolidation

  • Associate and Consolidate data

Data Quality Assistant

  • Build Mappings to create and populate the DQA tables
  • Perform manual Consolidation and Bad Record Management

PowerCenter Integration

  • Run DQ Mappings in PowerCenter

Object Import/Export

  • Import Projects using both Basic and Advanced methods
  • Export Projects

Parameters

  • How to use Parameters in Data Quality mappings, transformations and reference tables

Workflows

  • How to create different objects in DQ workflows modules. Examples: mapping task, Notification Task, Human Task etc.

SQL Server Intelligence Service (SSIS)

  • Introduction to Integration Services
  • Control Flow Basics & Control Flow Tasks
  • Data Flow Basics & Data Flow Transformations
  • Expressions
  • Scripts
  • Debugging SSIS Packages
  • Package Reliability & Execution

SQL Reporting Server (SSRS)

  • Introduction to SSRS
  • Server and Client Components
  • Report Wizard and Control Properties
  • Tables and Grouping
  • Using Parameters
  • Sub report functionality
  • Integration of SSRS with VS

SQL Analysis Service (SSAS)

  • Introduction to SSAS
  • OLTP and OLAP
  • Schema’s and Dimensions
  • Measures and Aggregates
  • Creating Cube and Browsing Cube
  • Working with Data Source
  • Introduction and Overview
    • Why Tableau? Why Visualization?
    • Level Setting – Terminology
    • Getting Started – creating some powerful visualizations quickly
    • The Tableau Product Line
    • Things you should know about Tableau

    Getting Started

    • Connecting to Data and introduction to data source concept
    • Working with data files versus database server
    • Understanding the Tableau workspace
    • Dimensions and Measures
    • Using Show Me!
    • Tour of Shelves (How shelves and marks work)
    • Building Basic Views
    • Help Menu and Samples
    • Saving and sharing your work

    Analysis
    Creating Views

    • Marks
    • Size and Transparency
    • Highlighting
    • Working with Dates
    • Date aggregations and date parts
    • Discrete versus Continuous
    • Dual Axis / Multiple Measures
    • Combo Charts with different mark types
    • Geographic Map Page Trails
    • Heat Map
    • Density Chart
    • Scatter Plots
    • Pie Charts and Bar Charts
    • Small Multiples
    • Working with aggregate versus disaggregate data
    • Analyzing
    • Sorting & Grouping
    • Aliases
    • Filtering and Quick Filters
    • Cross-Tabs (Pivot Tables)
    • Totals and Subtotals Drilling and Drill Through
    • Aggregation and Disaggregation
    • Percent of Total
    • Working with Statistics and Trend lines

    Getting Started with Calculated Fields

    • Working with String Functions
    • Basic Arithmetic Calculations
    • Date Math
    • Working with Totals
    • Custom Aggregations
    • Logic Statements

    Formatting

    • Options in Formatting your Visualization
    • Working with Labels and Annotations
    • Effective Use of Titles and Captions
    • Introduction to Visual Best Practices

    Building Interactive Dashboard

    • Combining multiple visualizations into a dashboard
    • Making your worksheet interactive by using actions and filters
    • An Introduction to Best Practices in Visualization

    Sharing Workbooks

    • Publish to Reader
    • Packaged Workbooks
    • Publish to Office
    • Publish to PDF
    • Publish to Tableau Server and Sharing over the Web

    Putting it all together

    • Scenario-based Review Exercises
    • Best Practices

Software Testing Jobs Out Look

With our Master’s in Business Intelligence and Data Analytics, you can command the top salary in a number of analyst positions in the field of your choice.

FAQ's

There are many ways to find second highest salary of Employee in SQL, you can either use SQL Join or Subquery to solve this problem. Here is SQL query using Subquery
Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. A data warehouse is often built to enable Data Analytics
Data marts are generally designed for a single subject area. An organization may have data pertaining to different departments like Finance, HR, Marketing etc. stored in a data warehouse and each department may have separate data marts. These data marts can be built on top of the data warehouse.
Deployment group is a global object which consists of objects from one or more folders. Deployment group is used to copy objects from one or more folders to another folder or repository. You can create, edit, or delete deployment groups. You can copy a deployment group and the objects in the deployment group to a target repository.
Pmcmd command in Informatica is used to run a workflow in command prompt.