Development and implementation of SQL Server data models (MDX, OLAP)

The course is primarily intended for business intelligence professionals, BI designers and developers who will be responsible for implementing, managing and supporting data warehouses, business intelligence solutions and implementing multidimensional data modelling.

• Introduction to business intelligence (BI) systems and data modelling: business intelligence concepts, components, trends, BI solutions, Microsoft BI platforms.
• Multidimensional database management: overview, basic concepts, multidimensional database architecture and features; overview of SQL Server 2016 Analysis Services; multidimensional data analysis features; concept and creation of data sources and data source views; concept of cubes, creating and modifying cubes; overview of cube security.
• Working with cubes and dimensions: configuring dimensions; defining attribute hierarchies; sorting and grouping attributes; implementing dimensions in cubes.
• Implementing measures in a cube: basic concepts; working with measures and measure groups, configuring measures; dimension usage and defining relationships; configuring measure group containers.
• Multidimensional expressions (MDX): basic concepts; using MDX syntax; adding calculations to a cube; querying a cube using MDX; creating calculated members.
• Cube functionality customisation: overview and application of key performance indicators (KPIs); concepts and use of operations, perspectives, translations.
• Implementing a tabular data model using Analysis Services: overview, concepts, characteristics; building and using a tabular data model in an enterprise BI solution.
• Introduction to Data Analysis Expression: overview, purpose, syntax of DAX language; creating calculated columns; creating measures; using Time Intelligence; creating dynamic measures.
• Predictive analytics using data mining technologies: overview of data mining, objectives, concepts, tools, implementation; use of Excel Data Mining Add-in; overview of data mining models; building custom data mining models and solutions; validation and application of data mining models.

Windows 8/10 or Windows Server 2012/2016 operator basics, previous SQL Server basics, query and implementation knowledge and experience. Completion of or knowledge of 20461 or 20761 courses required. As the course materials are in English, basic English language skills at document reading level are required. The lecture will be given in Hungarian.