Skip to main content

SSAS Tabular Mode with Azure Training - LIVE, Instructor Led

SSAS Online Training at SQL School is carefully designed to involve Datawarehouse Implementation, OLAP Data Modelling, Cube Development, Dimension Modelling, MDX Programing, DAX Expressions, MDX & DAX Reports, Data Mining with Forecasts and Tuning and Debugging operations. Classes are completely practical and interactive with one real-time Case Study.

Pre-requisites: Participant needs to have knowledge on SQL Server T-SQL Queries to join our Real-time Practical Data Modelling (SSAS) Training Course.

SSAS TRAINING HIGHLIGHTS :

  • Basic to Adv. ETL
  • Basic to Adv. DAX
  • Data Modelling
  • OLAP DB Design
  • Power Query
  • Basic to Adv. MDX
  • Kimball BI Design
  • Inmon BI Design
  • Star, Snowflake
  • Data Warehousing
  • OLTP, File Data
  • JSON, XML Data
  • Resume Guidance
  • MCSA MSBI Exam

SSAS LIVE Online
Training Course Contents:

Brochure DownloadRegister Now

SSAS Tabular Mode with Azure

Chapter 1: Tabular Mode Introduction

  • Databases : Types; OLTP, OLAP, DWH
  • Need for OLAP Databases and Cubes
  • OLTP versus OLAP Databases
  • DWH versus OLAP Databases
  • SQL Server Components & Features
  • SQL Server Analysis Services (SSAS)
  • SSAS Modes of Implementation
  • Tabular Mode: Advantages
  • Tabular Mode for OLAP Databases
  • SQL Server (Instance) Installation
  • Tabular Mode Server Installation
  • Management Studio (SSMS) Installation
  • Tabular Mode Server Connections
  • Server Properties; Data Directories
  • Visual Studio Tool: Purpose, Installation

Chapter 2:  Tabular Mode Cube Design

  • Using Visual Studio Tool : Tabular Mode
  • Cube Design – BISM and Explorer
  • Workspace and In-Memory Database
  • Cube Architecture: Measure Groups
  • Measures and Aggregations in Cube
  • Dimension Tables and Realtime Use
  • Attributes (Columns) and Members
  • Data Models For Cube Design
  • Data Source : Creations; Data Imports
  • Entity Selection and Data Source View
  • Data Models : Entity Relationships
  • Adding and Editing Relationships
  • Aggregated Measures and Attributes
  • Identify Measure Groups, Dimensions
  • Analyse in Excel. Cube Reports

Chapter 3: Cube Objects

  • OLAP Cube Design Concepts
  • OLAP Cube Objects in Tabular Mode
  • Understanding Grid View
  • Grid View Versus Relation View
  • Insert / Rename / Freeze Columns
  • Relationship Edits and Rules
  • Hierarchies: Creation & Precautions
  • Hierarchies Usage for Data Analytics
  • Perspectives : Purpose & Creation
  • Using Hierarchies and Perspectives
  • Excel Analytics with Hierarchies
  • Excel Analytics with Perspectives
  • Cube Partitions: Creation with SQL
  • Entity Partitions and Tuning Concepts
  • Grouping Entities – Snowflake

Chapter 4: CUBE Data Models

  • Data Modelling Concepts @ Databases
  • Data Models with OLAP Databases
  • Dimensions & Fact Table Identification
  • STAR Schema : Design Patterns
  • STAR Schema : Advantages & Cautions
  • SNOWFLAKE Schema : Design Patterns
  • STAR Versus SNOWFLAKE Schemas
  • OLTP Database Sources for OLAP
  • Cube Design with STAR Schema
  • STAR Schema Data Models with OLAP
  • SNOWFLAKE Data Models with OLAP
  • Snowflake Schema : Data Sources
  • Snowflake Schema : Cube Design
  • Azure Data Sources with OLAP Cubes
  • Using Azure SQL Databases with STAR

Chapter 5: Cube Deployment & MDX

  • OLAP Cube Deployments: Phases
  • Builds and Rebuilds – Output Results
  • Deployment Phase & Process Phase
  • Processing Options; Transactions
  • Processing Options : Donot Process
  • Deploy All and Deploy Changes Only
  • Cube Processsing Modes: In-Memory
  • Direct Query Options For Deployment
  • Cube Access from SSMS : Cube Browser
  • XMLA Scripts : OLAP DB Scripting
  • MDX: Multi Dimensional Expressions
  • MDX Queries : Auto & Manual Modes
  • MDX Queries: ORDER, TOP, WHERE
  • MDX Queries: MEMBERS, FILTERS
  • Generating MDX Queries from SSMS

Chapter 6: DAX – Level 1

  • DAX: Data Analysis Expressions
  • Role of DAX in Data Analytics
  • Implementations of DAX in OLAP
  • DAX : Entities & Naming Format
  • DAX Data Types and Operators
  • DAX Expressions : Purpose, Usage
  • DAX Queries: Purpose, Usage
  • DAX Functions : High Level Usage
  • DAX Expressions : Calculated Columns
  • DAX Column for Cube Design
  • ISBLANK() and IF() Functions
  • CALCUALTE () and SUM Functions
  • Understanding DAX Measures
  • Column Operations and Data Types
  • Calculation Operations, In-Memory

Chapter 7: DAX – Level 2

  • DAX Functions and Real-time Use
  • Filter Functions in DAX
  • ALL, ALLSELECTED
  • ALLEXCEPT, CALCULATE
  • CALCULATETABLE, FILTER
  • LOOKUPVALUE, OFFSET
  • Calculation Groups and Use
  • Cube Calculations & Deployments
  • Table Manipulation DAX Functions
  • ADDCOLUMNS & SUMMARIZE
  • GROUPBY, DATATABLE
  • UNION, EXCEPT
  • INTERSECT, ROW
  • NATURALINNERJOIN
  • NATURALOUTERJOIN

Chapter 8: DAX – Level 3

  • Logical DAX Functions
  • IFERROR, SWITCH
  • IF and AND (&&)
  • OR(||), NOT
  • COALESCE
  • USERPRINCIPALNAME()
  • USERELATIONSHIP
  • RELATEDTABLE
  • Text DAX Functions
  • UPPER, LOWER
  • LEFT, RIGHT, LEN
  • CONCATENATE
  • CONCATENATEX
  • ROW, SEARCH, REPT
  • MID, FIND, EXACT

Chapter 9: DAX – Level 4

  • Statistical DAX Functions
  • COUNTROWS, COUNTX
  • DISTINCTCOUNT
  • COUNTBLANK
  • COUNT, COUNTA
  • MIN, MINA & MINX
  • MAX, MAXA & MAXA
  • AVERAGE, AVERAGEA, AVERAGEX
  • Parent and Child Functions
  • PATH, PATHITEM
  • PATHCONTAINS
  • PATHLENGTH
  • Math & Trig Functions
  • SUM Vs SUMX

Chapter 10: DAX – Level 3

  • Time Intelligence Functions
  • OPENINGBALANCEMONTH
  • OPENINGBALANCEQUARTER
  • OPENINGBALANCEYEAR
  • CLOSINGBALANCEMONTH
  • CLOSINGBALANCEQUARTER
  • CLOSINGBALANCEYEAR
  • PREVIOUSDAY, PREVIOUSMONTH
  • FIRSTNONBLANK, NEXTMONTH
  • PREVIOUSQUARTER
  • TOTALMTD, TOTALQTD
  • TOTALYTD, NEXTDAY
  • PARALLELPERIOD
  • SAMEPERIODLASTYEAR

Chapter 11: DAX – Level 4

  • Date & Time Functions
  • CALENDAR, CALENDARAUTO
  • DATE, DATEDIFF, TIME
  • DATEVALUE, NOW
  • DAY, YEAR, MONTH
  • QUARTER, HOUR
  • MINUTE, SECOND
  • EDATE, EOMONTH
  • DAX Calculations with Joins
  • KPI: Key Performance Indicator
  • Using KPIs with DAX Concepts
  • Using KPIs with MDX Queries
  • KPIs Versus DAX Calculations
  • Translations & Cube Access

Chapter 12: Power BI Integrations

  • Using OLAP Cubes with Power BI
  • Storage Modes, Power BI In-Memory
  • Import and Connect LIVE Options
  • Creating Calendar Table in Power BI
  • Cumulative Total/ Running Total
  • Display Top Products for each region
  • DAX shortcuts in Power BI Desktop
  • Performance Advantages with OLAP
  • MDX Queries with SSMS Tool
  • Using MDX and DAX in Power BI
  • RLS: Row Level Security & DAX
  • Implementing RLS in Tabular Mode
  • Implementing RLS in Power BI
  • DAX Expressions for RLS
×