Course Details

Previous Page


Microsoft SQL Server 2014 - Designing BI Solutions: Data Models


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number



Overview/Description
SQL Server Analysis Services enable the storage and analysis of data using data models that employ the Business Intelligence Semantic Model, BISM framework. Using a data model allows value to be added to the data being presented to the business users by using key performance indicators and aggregating the appropriate data. In this course, you will explore how to design multidimensional and tabular data models and how to create the different elements to make meaningful data for the business user reports. This course is one of a series in the Skillsoft learning path that helps individuals prepare for the Designing Business Intelligence Solutions with Microsoft SQL Server exam (70-467).

Target Audience
Database and business intelligence administrators and developers who are responsible for designing a BI infrastructure, IT professionals interested learning how to design BI infrastructures and how they're related to data systems, and individuals interested in taking the Designing Business Intelligence Solutions with Microsoft SQL Server exam (70-467)

Prerequisites
None

Expected Duration (hours)
2.8

Lesson Objectives

Microsoft SQL Server 2014 - Designing BI Solutions: Data Models

  • start the course
  • describe the two types of BISM data models and how they can be used to create a unified Analysis Services platform
  • describe the considerations for choosing an analytical data model for an SSAS solution
  • choose between a star and snowflake schema for a multidimensional data model
  • identify how to design a relational model for a Data Mart
  • determine the appropriate Proactive Caching method within SSAS for different scenarios
  • describe how to plan for a multidimensional cube
  • design data sources for analytical models, including the types of data source and the considerations
  • create data sources and data source views, including relationships, for analytical models
  • use the cube wizard to create a cube for a multidimensional model
  • configure measures, including identifying the aggregation method
  • define measure groups
  • design and configure dimensions in a multidimensional model
  • design and configure relationships between tables
  • design and create aggregations to improve cube performance
  • design and configure cubes for drill-through
  • design indexes, index views, and order by statement for SSAS processing
  • import tables and configure relationships and measures for a tabular model
  • design and configure attributes and dimensions for a tabular model
  • choose the appropriate partitioning strategy for a cube
  • design aggregations strategies for separate partitions
  • create partitions for a cube, including specifying the aggregations and storage
  • configure binding options for partitions
  • configure data compression options on fact table partitions
  • design and configure write back for a cube
  • design data models and SSAS solutions in a given scenario
  • Course Number:
    md_dbis_a03_it_enus