Mastering SQL Server Query Languages - T-SQL, MDX, DAX & DMX
What you'll learn
- Download curated reference material spanning thousands of pages
- Download 1000+ ready-to-use queries developed in the course
- Learn how to query SQL Server databases, SSAS databases, and Data Mining models using T-SQL, MDX & DAX, and DMX respectively.
- Install SQL Server 2016 Database Engine, SQL Server Analysis Services in Multi-dimensional and Tabular mode, and SQL Server Management Studio
- Learn fundamentals of SQL Server, SQL Server Analysis Services and Data Mining
Requirements
- No prior working knowledge of SQL Server, SSAS, Data Mining, T-SQL, MDX, DAX or DMX is required.
- A Windows machine (Win 7 or higher) preferably with 4 GB RAM or higher
- SQL Server 2016 or higher Installable setup (even trial version will do). Installation is covered in the course.
- Added Advantage: Conceptual knowledge of SQL Server, SSAS and Data Mining will help to learn the query languages faster. Fundamentals are covered in the course.
Description
Top 4 Reasons to take this course:
1) You can learn T-SQL, MDX, DAX and DMX from scratch as well as ask questions directly to a Published Author, Microsoft MVP, and a Senior Technology Architect with more than 14 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 query development experience - You can learn four query languages - T-SQL, MDX, DAX and DMX, in such detail that you can apply for a job of SQL Developer / SSAS Developer / Data Mining Developer. Also you get to compare the querying techniques in 4 different query languages side by side using examples from a single course, taught by a single instructor on the same sample data.
3) More than 1000+ queries are explained in the course on OLTP, OLAP and Data Mining Models.
4) Downloadable Course Content:
- 15+ curated reference guides from MSDN which provides exhaustive theory, syntax, examples and reference links for SQL Server, Data Mining, T-SQL, MDX, DAX, and DMX.
- 1000+ Ready-to-use T-SQL, MDX, DAX and DMX Queries
- Links to 1 Sample OLTP Database, 1 Sample Data Warehouse, 1 OLAP Database with sample data and data mining models.
Course Description
SQL Server and SSAS Query Languages - T-SQL, MDX, DAX and DMX is a course in which a student having no experience in database query development would be trained step by step to a level where the student is confident to independently work in a high-performing database development project.
Course includes job-oriented practical hands-on queries with explanation and analysis, and theoretical coverage of key concepts. This is a fast track course to learn practical query development on 4 query languages using the latest version of SQL Server - 2016. No prior experience of working with any query language is required. Even installation of SQL Server, SSAS and Sample Data is covered in the course.
The course is structured in the following categories: Fundamentals, T-SQL, MDX, DAX and DMX. All the query languages have a common coverage that explains Selection, Joins, Grouping, Filtering, Sorting, Navigation, Calculations on the corresponding data models.
Who this course is for:
- This course is for students seeking to learn transactional and analytical query languages should
- This course is for professionals seeking to learn SQL Server database query development
- This course is for anyone seeking a SQL / Analytical / Data Mining Developer job / role
Instructor
![Siddharth Mehta](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.3 Instructor Rating
- 7,956 Reviews
- 64,825 Students
- 10 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