Microsoft SQL Server 2014 - Designing BI Solutions: Data Models

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

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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

Expertise Level
Expert