SQL Server Analysis Services - SSAS, Data Mining & Analytics

Develop SSAS cubes from data warehouse on Multidimensional & Tabular modes with Dimensional & Data Mining Models
4.23 (1312 reviews)
Udemy
platform
English
language
Databases
category
instructor
SQL Server Analysis Services - SSAS, Data Mining & Analytics
8 411
students
8 hours
content
Mar 2019
last update
$59.99
regular price

What you will 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 Gallery

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Our Verdict

SQL Server Analysis Services - SSAS, Data Mining & Analytics is a solid course on Udemy that covers various aspects of SSAS. While there are areas for improvement such as audio quality and course organization, it still provides a wealth of practical information in a hands-on manner, including extensive downloadable content that can significantly enhance your learning experience. If you're looking to build foundational to intermediate knowledge in SQL Server Analysis Services and related tools, this course should be valuable for you.

What We Liked

  • Comprehensive coverage of SQL Server Analysis Services (SSAS) and related technologies, including Multidimensional & Tabular modes, MDX, DAX, and Data Mining
  • Practical approach with downloadable course content, interview questions, reference materials, and sample projects
  • Addresses SSAS administration tasks like backup, restore, processing dimensions and measures, building aggregations, and deployment
  • Real-world scenarios and examples to help learners better understand the concepts

Potential Drawbacks

  • Some lectures may be too high-level or not detailed enough for beginners; additional resources might be required for in-depth learning
  • Occasional issues with audio, video, and pronunciation clarity that can make understanding the content challenging
  • Minimal real-world use cases or case studies to showcase advanced SSAS applications
  • A few users find the course disorganized, which may negatively impact the learning experience for some
893856
udemy ID
01/07/2016
course created date
21/11/2019
course indexed date
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