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30-Day Money-Back Guarantee
Development Database Design & Development SQL Server

SQL Server Analysis Services - SSAS, Data Mining & Analytics

Develop SSAS cubes from data warehouse on Multidimensional & Tabular modes with Dimensional & Data Mining Models
Rating: 4.3 out of 54.3 (1,173 ratings)
7,540 students
Created by Siddharth Mehta
Last updated 3/2019
English
30-Day Money-Back Guarantee

What you'll learn

  • Downloadable Course Content - FREE SQL Server 2016 EBook, 150+ Interview Questions, 100+ curated reference material links, 70+ MDX / DAX Queries, Links to 1 Sample OLTP Database and 1 Sample Data Warehouse with sample data - schema diagrams - documentation - dimensional modeling workbook, 1 Sample Multidimensional OLAP Database + 1 Sample Tabular OLAP Database containing fully functional cube with sample data, and Full project developed in the course.
  • By end of this course, you should be able to work with actual clients, technology architects, or team leads on a large scale SQL Server Analysis Services / MDX / Data Mining Project
  • Learn SQL Server Analysis Services ( SSAS ) Multi-dimensional as well as Tabular, Multidimensional Data Expressions ( MDX ) query language, Data Analysis Expressions (DAX) expression language and Data Mining on latest version of SQL Server - 2016 on a fast track with more practicals and limited theory necessary for fundamentals.
  • Develop Data Mining Models on algorithms like Decision Trees, Naive Bayes, Clustering, Neural Network, Time Series, Linear Regression and Sequence Clustering
  • Test your knowledge with more than 150 SSAS, MDX, DAX and Data Mining interview or Microsoft BI certification practice test questions. Every few weeks, new interview questions are added to the course.
  • Design, Model and Build SSAS database, data warehouse or data mart, and database objects like facts, dimensions, cubes, measures, perspectives, etc
  • Deploy SSAS solutions and learn SSAS administration tasks like backup and restore, processing dimensions and measures, building aggregations, etc
  • Develop MDX and DAX code with confidence
  • Develop SSRS Reports using MDX as query language and SSAS as data source
  • Debug issues and performance tune SSAS solutions for optimal performance
  • Learn about Microsoft Business Intelligence Architecture, and understand how SSAS fits in this architecture along with other tools like SSIS, SSRS, Master Data Services ( MDS ), Data Quality Services ( DQS ), Powerpivot, PowerView, SQL Server Database Engine, SSMS, SSDT and other tools.

Course content

13 sections • 78 lectures • 7h 54m total length

  • Preview11:56

  • Business Intelligence Solution Components Overview
    Preview07:49
  • Analyzing Dimensional Model
    14:26
  • Resources for downloading and analyzing sample Data Warehouse and OLTP database
    00:06
  • Business Intelligence Semantic Model Overview
    07:51
  • SSAS Overview
    14:17
  • Multidimensional Expressions Overview
    11:19
  • Comparison of SSAS Multidimensional, Tabular and Data Mining modes
    00:50
  • SQL Server 2016 Ebook Download Link and Glossary of SSAS Terminologies
    02:17
  • SSAS and Dimensional Modeling Interview Questions / Practice Test Exam Questions
    13 questions

  • Installing SQL Server and SSAS
    07:27
  • Configuring SSAS
    06:06
  • Resources and FAQ for SSAS Installation and Configuration
    01:43
  • SSAS Installation and Config Interview Questions / Practice Test Exam Questions
    6 questions

  • Attaching Data Warehouse
    04:15
  • Data Source and Data Source Views
    08:03
  • Developing Cube using Cube wizard
    04:53
  • Cube Design
    07:42
  • Dimension Design
    11:49
  • Hierarchy Design
    03:18
  • Preview08:05
  • Resources for Design and Development of SSAS Cube, Dimension, Measures
    00:07
  • SSAS Cube Development Interview Questions / Practice Test Exam Questions
    20 questions

  • Installing OLAP database
    05:26
  • Fundamentals of MDX Query
    10:33
  • Querying Object hiearchy - Dimensions, Attributes and Members
    09:52
  • Navigating and Sorting data
    11:36
  • Filtering Data
    11:35
  • Named Sets and Subcubes
    06:49
  • Calculated Measures and KPIs
    10:24
  • SSRS with MDX
    08:06
  • 50+ Ready-to-use MDX Queries
    02:20
  • Glossary of MDX Terms
    01:43
  • MDX Interview Questions / Practice Test Exam Questions
    28 questions

  • Processing Dimensions, Measurses and Cubes
    09:47
  • Backup and Restore
    04:15
  • Query Logging, Exception Logging and Flight Recorder
    07:19
  • Scripting and Synchronizing Databases
    03:43
  • SSAS Security
    08:26
  • Resources for SSAS Administration
    00:08
  • SSAS Administration Interview Questions / Practice Test Exam Questions
    16 questions

  • Fine tuning and Multi-lingual Support
    11:49
  • Aggregation Design
    11:17
  • Partitioning and Storage Modes
    11:57
  • Resources for SSAS Advance Techniques
    00:05
  • SSAS Aggregation Design Interview Questions / Practice Test Exam Questions
    11 questions

  • Query interception and analysis
    06:19
  • Usage based performance optimization
    05:17
  • Performance Counters
    05:53
  • Resources for SSAS Performance Tuning
    00:03
  • SSAS Performance Tuning Interview Questions / Practice Test Exam Questions
    7 questions

  • Applications of Data Mining
    06:05
  • Problem Definition for Data Mining with SSAS
    04:14
  • Data Preparation for Data Mining with SSAS
    02:11
  • Data Exploration for Data Mining with SSAS
    03:29
  • Building and Training Models for Data Mining with SSAS
    04:06
  • Validating model for Data Mining with SSAS
    04:26
  • Deploying models for Data Mining with SSAS
    03:03
  • Data Mining Algorithms
    08:42
  • Resources for Data Mining Algorithms in SQL Server 2016 and SSAS
    00:12
  • Data Mining Interview Questions / Practice Test Exam Questions
    11 questions

  • Building a Relational Data Mining Model and Data Mining Structure
    12:53
  • Analyzing and Testing a Relational Data Mining Model
    14:17
  • Applying a Data Mining Model for Prediction
    04:14
  • Reusing a Data Mining Structure
    06:33
  • Building an OLAP Data Mining Model
    09:43
  • Analyzing Cube with Data Mining Dimension
    07:39
  • Developing Data Mining Reports using Microsoft Office
    06:36
  • Resources for SSAS Data Mining Model Development
    00:08
  • Data Mining Interview Questions / Practice Test Exam Questions
    14 questions

Requirements

  • No prior knowledge of SSAS, MDX, Dimensional modeling or Data Mining is required.
  • Basic working knowledge of SQL Server like working with tables, views, stored procedures etc is required.

Description

Top 4 Reasons to take this course:

1) You can learn SSAS, Data Mining and Analytics from scratch as well as ask questions directly to a Published Author, Microsoft MVP, and a Senior Technology Architect with more than 15 years of experience who actively practices Business Intelligence, Data Mining and Analytics in real-world client projects internationally.

2) In a single course, without any prior analytics experience - You can learn three query languages used for analytics - MDX, DAX and DMX. Along with this you learn SSAS in such detail that you can apply for a job of SSAS Developer / Admin / Architect, and also prepare yourself for Microsoft certification 70-768.

3) You get to train yourself for any SSAS, MDX, DAX, and Data Mining interview with more than 150+ interview questions. If you still have any questions, you can ask those questions to me. 

4) Downloadable Course Content:

  • FREE SQL Server 2016 EBook Link

  • 150+ Interview Questions

  • 100+ curated reference material links

  • 70+ Ready-to-use MDX / DAX Queries

  • Links to 1 Sample OLTP Database and 1 Sample Data Warehouse with sample data - schema diagrams - documentation - dimensional modeling workbook 

  • Links to 1 Sample Multidimensional OLAP Database + 1 Sample Tabular OLAP Database containing fully functional cube with sample data 

  • Full project developed in the course.


Course Description

SQL Server Analysis Services, Data Mining and Analytics is a  course in which a student having no experience in data science and analytics would be trained step by step from basics to advanced data science topics like data mining. The intention of this course is to empower students with the knowledge of OLAP, Analytics and Data Mining, which can potentially yield salaries of $85 - $150k based only on your experience of SSAS, MDX, DAX and Data Mining.

Course includes job-oriented practical hands-on exercises, theoretical coverage of key concepts, interview questions, practice test questions for certifications and more. This course covers all the topics for developers, administrators as well as aspiring data scientists. New Interview questions are added to the course every few weeks. Anyone pursuing this course would be able to clearly understand about Microsoft Business Intelligence Architecture, and understand how SSAS and Data Mining fits in this architecture along with other tools like SSIS, SSRS, Master Data Services ( MDS ), Data Quality Services ( DQS ), Powerpivot, PowerView, SQL Server Database Engine, SSMS, SSDT and other tools.

SQL Server Analysis Services, Data Mining and MDX is a fast track course to learn practical SSAS ( SQL Server Analysis Services ), Data Mining and MDX code development using the latest version of SQL Server - 2016. No prior experience of working with SSAS / Data Mining or MDX is required. 

The course is structured in the following categories: Fundamentals, Design, Development, MDX Code development, Administration, Performance Tuning, Data Mining Basics and Data Mining Development, Tabular SSAS Installation and Configuration, and Tabular SSAS Design and Development as well as DAX programming.

Who this course is for:

  • Open minded professionals seeking to give a competitive edge to their carrer in the field of data and analytics should definitely consider in enrolling for this course
  • This course is for those who want to start a career in the analytics space by learning a niche skill
  • If you are planning to appear for a SSAS job interview or MS BI Certification, this course is for you
  • Students planning to take 70-768 microsoft certification should enroll in this course as the course covers almost entire topics of the exam.
  • Data mining professionals are very rare and having even a basic or intermediate training on Data Mining is a huge plus. Students who wants to add a plus on their resume should take this course.
  • MDX developers are one of the most sought after professionals in the analytics data space. This course is for those who are ready to invest their time in a complex skill to differentiate themselves from the crowd.
  • This course is specially designed for those working or who want to work in the role of MS BI Architect, MDX Developer, SSAS Administrator, SSAS Architect, SSAS Developer, Data Modeler, MS BI Developer, SSAS Performance Engineering Specialist and others
  • SSAS Tabular and DAX is the newest trend in the self-service Analytics using SSAS. Students interested in this part of the BI should enroll in this course

Featured review

Craig A. Simmons
Craig A. Simmons
5 courses
3 reviews
Rating: 5.0 out of 5a year ago
Thank you for a really good informative course. I learned so much from it. I signed up for this course with the premise that there was a Completion Certificate at the conclusion. Is there a place that I am not looking to find my Certificate? Thank you again.

Instructor

Siddharth Mehta
Enterprise Cloud Architect, Published Author, Cloud Geek
Siddharth Mehta
  • 4.3 Instructor Rating
  • 5,659 Reviews
  • 47,690 Students
  • 11 Courses

Udemy's Top 10% of most engaging instructors

My name is Siddharth Mehta. I have career experience of more than 15 years in the IT Industry and am presently working as Enterprise Cloud Architect. I am published author on many online and print-media publications. I have taught thousands of students on Udemy and have number of courses on Data and Analytics. 

Would you consider learning from just any hobbyist who knows programming or someone who just teaches programming without practically using it in the real world, or someone who has experience of using the technology in real world on multi-million dollar large-scale projects globally ? I will teach you everything I know about the subject, from my years of practical experience in the field of BI, Data, Analytics, Cloud and Data Science.

If you are interested in learning more about me, below are some of my career highlights:

I have career experience of more than 15+ years and am presently working in New York Metro region as Enterprise Architect for a life-sciences proprietary multi-tenant product technology portfolio, managing an ecosystem of ISVs and tenants. Below are some of my career highlights:


-|- International experience of working across geographies (US, UK, Singapore) for multi-national clients in Banking, Logistics, Government, Media Entertainment, Products, Life Sciences and other domains

-|- Lead architecture of multi-million dollar portfolios containing apps in Cloud, web, mobile, BI, Analytics, Data warehousing, Reporting, Collaboration, CMS, NoSQL and other categories.

-|- Official inventor of a patented application

-|- Published author/reviewer of whitepapers for Microsoft MSDN Library, Manning publication, Packt publication and others.

-|- Certifications: AWS Certified Solution Architect, TOGAF 9, CITA-F, HCAHD and more


In my present role, I remain responsible for Estimations like AO, IO, SI, IC & Security, Architecture Design, Technology Stack selection, Infra design, 3rd party products evaluation and procurement, and Performance engineering. Hands-On Technology experience of below tech:


-|- OS: Win, Linux

-|- Cloud: GCP, Azure, AWS

-|- Databases: Neo4j, AWS Neptune, Redis, Memcached, MongoDB, Cassandra, HBase, SQL Server, MariaDB, Postgres, Aurora, MySQL, SSAS, AWS Redshift, Google BigQuery, Azure Data Lake, AWS RDS, DynamoDB, Athena, AWS Elasticache

-|- Big Data: Google DataProc, AWS EMR, Kafka, Spark, Hive, Oozie

-|- Search: AWS Elasticsearch

-|- Web: Node.JS, Angular, jQuery, REST APIs, React

-|- ESB/ETL: AWS Lambda, Step Functions, AWS Kinesis, AWS Glue, Mulesoft, SSIS, AWS Data pipeline

-|- Data Science: R , Python, GGPlot 2, Numpy, Seaborn, Pandas, Skikit-learn, Spark ML, Data Mining, Regression & Classification algorithms

-|- Reports / Dashboards : Tableau, Qlikview, SSRS, AWS Quicksight, D3

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