MSBI Training in India

1. Basics and architecture of MSBI
2. Data Modeling, Representation, and Transformation
3. Fundamental concepts and architectures of SSIS, SSAS, and SSRS
4. Multidimensional modeling, ETL, and Transformations in SSIS
5. Creating graphical visualizations in SSRS
6. Getting a grasp of OLAP databases and tables in SSAS
7. Relationship types in SSAS

• Software Architects, ETL Developers, and Data Analysts
• Business Intelligence Professionals and people looking to upskill themselves in MSBI

Anybody can take up this online training course and get trained in MSBI.

A Data Scientist earns approximately Rs. 6,20,244 lakhs in India per year.

Data Science is one of the most trending streams in India. Hence, an increasing number of Data Science professionals are being recruited by top MNCs across the country.

Information Technology is one of the fastest growing sectors in India. Hence, a lot of lucrative job opportunities are emerging every day for the individuals with different skills. The Data Scientist is increasingly becoming the most desirable job profile in India. Learn Microsoft Business Intelligence from Intellipaat and get ahead in your career.

• Worldwide Business Intelligence and Analytics market to grow to $22.8 billion in revenue in the next two years – Gartner
• Average US Salary for a Microsoft BI Professional is $107,000 – Indeed

MSBI certification training course in India provides around 60 hours of lab practice sessions and real-life projects to improve the hands-on experience of the learner. This training covers all topics needed to score high in the MCSE: Business Intelligence Certification.

Introduction to Business Intelligence, understanding the concept of Data Modeling, Data Cleaning, learning about Data Analysis, Data Representation, Data Transformation.

Introduction to ETL, the various steps involved Extract, Transform, Load, using a user’s email ID to read a flat file, extracting the User ID from email ID, loading the data into a database table.

Introduction to Connection Managers – logical representation of a connection, the various types of Connection Managers – Flat file, database, understanding how to load faster with OLE DB, comparing the performance of OLE DB and ADO.net, learning about Bulk Insert, working with Excel Connection Managers and identifying the problems.

Learning what is Data Transformation, converting data from one format to another, understanding the concepts of Character Map, Data Column and Copy Column Transformation, import and export column transformation, script and OLEDB Command Transformation, understanding row sampling, aggregate and sort transformation, percentage and row sampling.

Understanding Pivot and UnPivot Transformation, understanding Audit and Row Count Transformation, working with Split and Join Transformation, studying Lookup and Cache Transformation, Integrating with Azure Analysis Services, elastic nature of MSBI to integrate with the Azure cloud service, scale out deployment option for MSBI, working with cloud-borne data sources and query analysis. Scaling out the SSIS package, deploying for tighter windows, working with larger amount of data sources, SQL Server vNext for enhancing SQL Server features, more choice of development languages and data types both on-premise and in the cloud.

Understanding data that slowly changes over time, learning the process of how new data is written over old data, best practices.Detail explanation of three types of SCDs –Type1, Type2 and Type3, and their differences.

Understanding how Fuzzy Lookup Transformation varies from Lookup Transformation, the concept of Fuzzy matching

Learning about error rows configuration, package logging, defining package configuration, understanding constraints and event handlers.

Get introduced to the SSRS Architecture, components of SSRS Report Building tool, learning about the data flow in different components.

Understanding the concepts of Matrix and Tablix, working with Text Box, learning about formatting, row/column grouping, understanding sorting, formatting, concepts of Header, Footer, Totals, Subtotals and Page Breaks.

Learning about Parameters, filter and visibility expression, understanding drill-through and drill-down, defining variables, custom code.

Introduction to various aspects of Bar Chart, Line Chart, Combination Chart, Shape Chart, Sub Reports,Integration of Power Query and M language with SSRS, working with additional data sources in MSBI, rich transformation capabilities addition to MSBI, reusing M functions build for PBIX in SSRS.

Learn how to build a Dashboard with Sparklines, Data Bars, Map Charts, Gauge Charts and drilling into reports, the basics of ad hoc reporting.

Data Bar, Sparkline, Indicator, Gauge Chart, Map Chart, Report Drilling, What is Ad hoc reporting?

Understanding Report Cache, Authorization, Authentication and Report Snapshot, learning about Subscriptions and Site Security.

Understanding the concept of multidimensional analysis, understanding SSAS Architecture and benefits, learn what is Cube, working with Tables and OLAP databases, understanding the concept of Data Sources, working with Dimension Wizard, understanding Dimension Structure, Attribute Relationships, flexible and rigid relationship.

Learning about Process Dimension, the Process database, creation of Cube, understanding Cube Structure, Cube browsing, defining the various categories, Product Key and Customer Key, Column Naming, processing and deploying a Cube, Report creation with a Cube.

Hands-on Exercise – Create a Cube and name various columns Deploy a cube after applying keys and other rules Create reports with a cube

Understanding Data Dimensions and its importance, the various relationships, regular, referenced, many to many, fact, working on Data Partitions, and Data Aggregations.

Learning about SSAS Cube, the various types of Cubes, the scope of Cube and comparison with Data Warehouse.

The various operations on Cube, the limitations of OLAP Cubes, the architecture of in-memory analytics and its advantages.

Deploying cube with existing data warehouse capabilities to get self-service business intelligence, understanding how in-memory analytics works.

Hands-on Exercise – Deploy cube to get self-service business intelligence

Logical model of the schema used by the Cube, components of Cube, understanding Named Queries and Relationships.

An overview of the Dimensions concept, describing the Attributes and Attributes Hierarchies, understanding Key/Value Pairs, Metadata Reload, logical keys and role-based dimensions.

Hands-on Exercise – Create role based dimensions, Use Attributes Hierarchies

Understanding the Measure of Cube, analyzing the Measure, exploring the relationship between Measure and Measure Group, Cube features and Dimension usage.

Working with Cube Measures, deploying analytics, understanding the Key Performance Indicators, deploying actions and drill-through actions on data, working on data partitions, aggregations, translations and perspectives.

Hands-on Exercise – Work with Cube Measures, Deploy analytics, Deploy actions and drill-through actions on data, Make data partitions

Understanding Multidimensional Expressions language, working with MDX queries for data retrieval, working with Clause, Set, Tuple, Filter condition in MDX.

Hands-on Exercise – Apply Clause, Set and filter condition in MDX query to retrieve data

Learning about MDX hierarchies, the functions used in MDX, Ancestor, Ascendant and Descendant function, performing data ordering

Hands-on Exercise – Create MDX hierarchies, Perform data ordering in ascending order, in descending order

Data Analysis Expressions (DAX), Using the EVALUATE and CALCULATE functions, filter DAX queries, create calculated measures, perform data analysis by using DAX

Hands-on Exercise – Use the EVALUATE and CALCULATE functions, filter DAX queries, create calculated measures, perform data analysis by using DAX

Designing and publishing a tabular data model, Designing measures relationships, hierarchies, partitions, perspectives, and calculated columns

Hands-on Exercise – Design and publish a tabular data model, Design measures relationships, hierarchies, partitions, perspectives, and calculated columns

Configuring and maintaining SQL Server Analysis Services (SSAS), Non-Union Memory Architecture (NUMA), Monitoring and optimizing performance, SSAS Tabular model with vNext, Excel portability, importing model from Power BI Desktop, importing a Power Pivot model, bidirectional cross-filtering relationship in MSBI.

Hands-on Exercise – Configure and maintain SQL Server Analysis Services (SSAS), Monitor and optimize performance

Reading data with R Server from SAS, txt, or excel formats, converting data to XDF format; Summarizing data, rxCrossTabs versus rxCube, extracting quantiles by using rxQuantile; Visualizing data (rxSummary and rxCube, rxHistogram and rxLinePlot) Processing data with rxDataStep Performing transforms using functions transformVars and transformEnvir Processing text using RML packages Building predictive models with ScaleR Performing in-database analytics by using SQL Server

Hands-on Exercise – Read data with R Server from SAS, txt or excel formats, convert data to XDF format; Summarize data, Extract quantiles by using rxQuantile; Visualize data (rxSummary, rxCube, rxHistogram and rxLinePlot) Perform transforms using functions transformVars and transformEnvir Build predictive models with ScaleR Perform in-database analytics by using SQL Server

Analyzing Data with SQL Server Reporting Services

Project 1 : Configuration and Logging

Industry : General

Problem Statement :  How to integrate data from multiple sources into the SQL Server

Topics : In this SQL Server Integration Services (SSIS) project you will extensively work on multiple data from heterogeneous source into SQL Server. As part of the project you will learn to clean and standardize data and automate the administrative work. Some of the tasks that you will be performing are adding logs to SSIS package, configuration and saving it to an XML file. Upon completion of the project you will have hands-on experience in handling constraints, error row configuration and event handlers.

Highlight :

• Integrate data from heterogeneous sources
• Working with Connection Manager
• Deploying data modeling

Project 2 – SSAS Cube Using BI Data Tools 2012

Industry : Sales

Problem Statement : How to create the SSAS Cubes for faster reporting

Topics – In this project you will be work on large volume of data and use it for creating reports and dashboards for sales performance in order to derive valuable insights. You will deploy the sales database in sql server and build SSAS Cubes. Upon completion of the project you will be well-versed to work in a real world business scenario to analyze various parameters and instances in order to derive business insights.

Highlights :

• Create multidimensional cubes
• Deploying MDX query language
• Working with in-memory analytics.

Project 3 – Building Dashboard

Data – Sales

Topics – In this project you will be working on SQL Server Reporting Services (SSRS) and deploying it for building dashboards in a business environment. The Business Intelligence Report that you create will be used to calculate sales based on the years and currencies that you choose. Some of the tasks that you will be performing as part of this project are – design and create Gauge and Map Charts, Spark lines and Data Bar and perform drill-through Reports, and ad hoc Reporting.