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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery | Frequency Of Classes |
|---|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based | Weekends |
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Microsoft CorporationBelhaven University, Mississippi |
The Syllabus
- Module 01 – Introduction to SQL
- Module 02 – Database Normalization and Entity Relationship Model
- Module 03 – SQL Operators
- Module 04 – Working with SQL: Join, Tables, and Variables
- Module 05 – Deep Dive into SQL Functions
- Module 06 – Working with Subqueries
- Module 07 – SQL Views, Functions, and Stored Procedures
- Module 08 – Deep Dive into User-defined Functions
- Module 09 – SQL Optimization and Performance
- Module 10 – Advanced Topics
- Module 11 – Managing Database Concurrency
- Module 12 – Programming Databases Using Transact-SQL
- Module 13 – Microsoft Courses: Study Material
- Module 01 – INTRODUCTION TO POWER BI
- Module 02 – DATA EXTRACTION
- Module 03 – DATA TRANSFORMATION – SHAPING & COMBINING DATA
- Module 04 – DATA MODELLING & DAX
- Module 05 – DATA VISUALIZATION WITH ANALYTICS
- Module 06 – POWER BI SERVICE (Cloud), Q & A AND DATA INSIGHTS
- Module 07 – POWER BI SETTINGS, ADMINISTRATION & DIRECT CONNECTIVITY
- Module 08 – EMBEDDED POWER BI WITH API & POWER BI MOBILE
- Module 09 – POWER BI ADVANCE & POWER BI PREMIUM
- Module 01 – Non-Relational Data Stores and Azure Data Lake Storage
- Module 02 – Data Lake and Azure Cosmos DB
- Module 03 – Relational Data Stores
- Module 04 – Why Azure SQL?
- Module 05 – Azure Batch
- Module 06 – Azure Data Factory
- Module 07 – Azure Data Bricks
- Module 08 – Azure Stream Analytics
- Module 09 – Monitoring & Security
- Module 01 – Introduction to Data Visualization and The Power of Tableau
- Module 02 – Architecture of Tableau
- Module 03 – Charts and Graphs
- Module 04 – Working with Metadata and Data Blending
- Module 05 – Advanced Data Manipulations
- Module 06 – Working with Filters
- Module 07 – Organizing Data and Visual Analytics
- Module 08 – Working with Mapping
- Module 09 – Working with Calculations and Expressions
- Module 10 – Working with Parameters
- Module 11 – Dashboards and Stories
- Module 12 – Tableau Prep
- Module 13 – Integration of Tableau with R
MSBI SSIS Course Content
- Module 01 – What is BI?
- Module 02 – ETL Overview
- Module 03 – Working with Connection Managers
- Module 04 – Data Transformations
- Module 05 – Advance Data Transformation
- Module 06 – Slowly Changing Dimensions
- Module 07 – Overview of Fuzzy Look-up Transformation and Lookup and Term Extraction
- Module 08 – Concepts of Logging & Configuration
MSBI SSRS Course Content
- Module 09 – Introduction to SSRS
- Module 10 – Matrix and Tablix Overview
- Module 11 – Parameters and Expression
- Module 12 – Reports and Charts creation
- Module 13 – Dashboard Building
- Module 14 – Reports and Authenticity
MSBI SSAS Course Content
- Module 15 – Getting started with SSAS
- Module 16 – Structures and Processes
- Module 17 – Type of Database Relationship
- Module 18 – SSAS Cube
- Module 19 – Cube: Operations & Limitations
- Module 20 – Cube and In-memory Analytics
- Module 21 – Data Source View
- Module 22 – Dimensions
- Module 23 – Measures & Features of Cube
- Module 24 – Measures and Features of Cube Cont.
- Module 25 – Working with MDX
- Module 26 – Functions of MDX
- Module 27 – BI Semantic Model
- Module 28 – Plan and deploy SSAS
- Module 29 – Microsoft Courses ( Self-Paced Course)
- Module 01 – Data Warehousing and Cleansing Concepts
- Module 02 – Informatica Installation and Configuration
- Module 03 – Working with Active and Passive Transformation
- Module 04 – Working with Expression Transformation
- Module 05 – Working with Sorter, Sequence Generator and Filter Transformation
- Module 06 – Working with Joiner Transformation
- Module 07 – Working with Ranking and Union Transformation
- Module 08 – Syntax for Rank and Dense Rank
- Module 09 – Router Transformation
- Module 10 – Source Qualifier Transformation and Mappings
- Module 11 – Slowly Changing Dimension in Informatica
- Module 12 – Mapplet and Loading to Multiple Designer
- Module 13 – Performance Tuning in Informatica
- Module 14 – Repository Manager
- Module 15 – Best Practices in Informatica
- Module 16 – Workflow Informatica
- Module 17 – Parameters and Variables
- Module 18 – Error Handling and Recovery in Informatica
- Module 19 – High Availability and Failover in Informatica
- Module 20 – Working with Different Utilities in Informatica
- Module 21 – Flat File Processing (Advanced Transformations)
- Module 22 – Dynamic Targeting
- Module 23 – Working with Java Transformations
- Module 24 – Unconnected Stored Procedure Usage
- Module 25 – Advanced Concepts in SCD
- Module 26 – Incremental Data Loading and Aggregation
- Module 27 – Constraint-based Loading
- Module 28 – XML Transformation and Active Lookup
- Module 29 – Profiling in PowerCenter
- Module 30 – Workflow Creation and Deletion
- Module 31 – Database Connection
- Module 32 – Relational Database Tables
- Module 33 – LinkedIn Connection
- Module 34 – Connection with Sources
- Module 35 – Pushdown Optimization and Partitioning
- Module 36 – Cache Management
- Module 01 – Qlik Sense Introduction and Installation
- Module 02 – Qlik Sense Features
- Module 03 – Qlik Sense Data Model
- Module 04 – Creating a Data Model
- Module 05 – Advanced Data Modeling
- Module 06 – Qlik Sense Enterprise
- Module 07 – Qlik Sense Visualization
- Module 08 – Set Analysis
- Module 09 – Advanced Set Analysis
- Module 10 – Qlik Sense Charts
- Module 11 – Advanced Charts
- Module 12 – Master Library
- Module 13 – Qlik Sense Storytelling
- Module 14 – Mashups
- Module 15 – Extensions
- Module 16 – Security
- Module 01 – Installation and Configuration
- Module 02 – Managing Instances and Databases
- Module 03 – Optimizing and Troubleshooting
- Module 04 – Managing Data
- Module 05 – Implementing Security
- Module 06 – Implementing High Availability
- Module 01 – Introduction to Data Warehouse
- Module 02 – Architecture of Data Warehouse
- Module 03 – Data Modeling concepts
- Module 04 – Data Normalization
- Module 05 – Dimension & Fact Table
- Module 06 – SQL parsing, Cubes & OLAP
- Module 07 – Erwin Design Layer Architecture (self paced)
- Module 08 – Forward & Reverse Engineering (self paced)
Instructors
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