See how Microsoft Power BI and Azure Analysis Services are influencing the BI and analytics market. Journey through data structures and fundamentals for setting up your next dashboard initiative. Interested in learning more? Click ccganalytics.com/resources for more or call (813) 265-3239.

1. Afternoons with Azure Series
Microsoft Power BI and Azure Analysis Services

2. Intro to CCG Azure Subscriptions
Overview of Power BI
Overview of Azure Analysis
Services
Power BI Workshop
Q & A

3. Microsoft Power BI
Martin Rivera, BI Architect

4. Overview of Power BI
Power BI Desktop
Data Sources
Visualizations
Interactive Reports

5. Overview of Power BI

6. Microsoft in the BI and Analytics Market
Leaders Leaders are vendors that demonstrate a solid understanding of the
product capabilities and commitment to customer success that buyers
demand in the current market.
Have a robust roadmap for solidifying its position as a future market
leader, thus protecting the investment of today's buyers.
Challengers Challengers are well-positioned to succeed in the market. However, they
may be limited to specific use cases, technical environments or
application domains.
Visionaries Visionaries have a strong and unique vision for delivering a modern
analytics and BI platform. However, they may have gaps relating to
broader functionality, customer experiences, operations, and sales
execution.
Niche Players Niche Players do well in a specific segment of the analytics and BI market
— such as cloud BI, customer-facing analytics, agile reporting and
dashboarding, embeddability or big data analytics — or have a limited
capability to out-innovate or outperform other vendors.
Microsoft has been leader for 11 years

7. Mi
What is Power BI?
Power BI is a suite of business analytics tools to analyze
data and share insights. Monitor your business and get
answers quickly with rich dashboards available on
every device.
Microsoft
BI Stack

8. What is Power BI Report Server
Power BI Report Server (PBIRS), is a
Microsoft solution deployed on premise
for creating, publishing, and managing
reports, then delivering them to the right
users in different ways.
For end users of Power BI Report Server,
the front door is a modern web portal
you can view in any web browser.
*Content gets developed and published using
the Power BI Desktop Tool.
Invoices
Time
Vendor
State
Customer

9. What’s the Difference?
Power BI (Service)
• Hosted in the (Azure) cloud
• SaaS (Software as a Service)
• Integration with Azure stack
• Rapid evolution (~monthly)
• Cutting edge features (ex: Cortana)
Power BI Report Server
• Hosted on premise
• Rely on legacy SSRS architecture
• Integration with Microsoft tools
• More controlled rollouts
• Features backlogged at times
Both aim to provide developers and
end-users with a similar experience.

10. Report Power BI Dashboard
A Power BI report displays one or more visualizations that
represent different findings and insights from a specific
dataset.
Could be a single page, or multiple pages.
All visualizations displayed are part of the same report.
A Power BI dashboard is a single page, often called a canvas, that
uses visualizations to tell a story.
The visualizations you see on the dashboard are called tiles and
are pinned to the dashboard from existing reports.
Typically, a PBI dashboard will contain tiles from various reports.
What’s the Difference?

11. Power BI Desktop

12. Power BI Desktop
• Intuitive report Authoring
• Data Preparation and Data
Modeling
• Drag-and-drop to place content
exactly where you want it
• Discovery of data patterns in one
unified view through rich and
interactive visualizations
NOTE: There are separate versions of Power BI
Desktop for Power BI Service and Power BI Report
Service

13. Power BI Desktop
Publish
Report Server

14. Power BI Desktop
Clean and Transform Your Data
Query Editor
• 1 query per table/worksheet
• Transform existing columns
• Add new columns
• Combine multiple queries
• Merge
• Append

15. Power BI Desktop
Clean and Transform Your Data
Data Type Specific Filters
Replace/Fill Values

16. Power BI Desktop
Modeling
• The Semantic Model
• Friendly names
• Business rules /
definitions
• Creating custom columns
& measures
• Formatting columns and
measures for reporting
• E.g. currency, number of
decimals, short/long date

17. Power BI Desktop
• Can be configured Between any
two tables, even from different
sources
• Columns must have the same data
type
• Column names don’t have to be
the same
• Supports 1 to 1, 1 to Many, and
Many to 1 relationships
• Many-to many relationship are
not supported: use a bridge table
Relationships between Entities

18. Power Query “M” Language
• Similar to MDX
• Often used with
multidimensional models
• Mechanism for manipulating
data prior to load
• Can be a powerful tool and
extend capabilities available
from UI
https://msdn.microsoft.com/en-us/library/mt211003.aspx
Power Query “M” Language Reference

19. Data Analysis Expressions (DAX)
• Calculated Columns
– Calculated at load time
– Evaluated for each row
– Stored in the model!
• Calculated Measures
– Calculated at (report) run time
– Evaluated with context (filters)
– Implicit: Created by Power BI
– Explicit: Created by you
• Calculated Tables
– Lookups
– Date Table
– Constants
• DAX is a library of functions and operators that can be used
after you’ve loaded your dataset
• Conceptually similar to Excel formulas, but different in how
it may process inputs
• Concepts are straightforward, but not easy
– Don’t expect to learn DAX in 2 hours
• Functional Language
– Full code in nested functions
– Evaluated from inner to outer
• Do not write everything on one line
Over 200 Functions:
• Text Functions
• Statistical Functions
• Math and Trig Functions
• Date and Time
• Information Functions
• Filter Functions

20. Data Sources

21. Types of Data Sources

22. Data Connectivity Mode
This is handled in Data Source Settings in Power BI Desktop. The report consumer or content
manager does not have the option to control/override this.
Import Imports data into the generated PBIX file. This results in faster performance,
but is a “snapshot” of data as of a point in time*.
*You can schedule a periodic refresh.
DirectQuery Connects to the data source “live” at each report execution. This means data is
in real-time, but can result in slower performance of report executions and
interactions.
You cannot mix both data
connectivity modes in the same
report
You cannot change the data
connectivity modes of a report
once selected

23. Visualizations

24. • Power BI is all about visualizations
• Tell the right story
• Highlight unforeseen nuances
• Easy to consume
• Intuitive, and actionable
Visualize Data for Maximum Impact

25. Default Visualizations
1. Stacked Bar Chart
2. Stacked Column chart
3. Clustered Bar Chart
4. Clustered Column Chart
5. 100% Stacked Bar Chart
6. 100% Stacked Column chart
7. Line Chart
8. Area Chart
9. Stacked Area Chart
10. Line and Stacked Column Chart
11. Line and Clustered Column Chart
12. Ribbon Chart
13. Waterfall Chart
14. Scatter Chart
15. Pie Chart
16. Donut Chart
17. Tree Map
18. Map
19. Filled Map
20. Funnel
21. Gauge
22. Card
23. Multi-Row Card
24. KPI
25. Slicer
26. Table
27. Matrix
28. R Script Visual

26. Custom Visuals

27. Custom Visuals
• Available from Microsoft Apps site
• They are Open Source
• Users contribute, MSFT publishes
• They are someone else’s idea of what looks good
• May provide limited properties/controls
• Can also be obtained directly from other publishers
• No guarantee they will work!
• May not be supported across versions
• Reside within the specific PBIX file
Example:
Body Part
Analysis

28. Interactive Reports

29. Interactive Analysis
Year Selected
State
Selected
All visualizations interact with
one another.
Some visualizations are filtered,
while others are highlighted
Only visualizations within the
same page interact with one
another.
Interactions can be controlled
within Power BI Desktop

30. Drilling
Power BI allows for drilling down and up hierarchies to explore data at different levels of
a pre-defined hierarchy
• Great use case for exploring time based hierarchies
Date columns have built-in Time Intelligence, to generate hierarches
Also, you have the ability to setup drill through filters on a report page, to focus the data
in that child page, based on the selection in the parent page
Drill through can be setup between pages w/in the same report
Year
Quarter
Month
Day

31. Drill Down vs. Drill Through

32. Intro to Azure Analysis Services

33. SSAS Fundamentals
– Multidimensional Models
– Tabular Models
Azure Analysis Services
– Features
– Compatibilities with On
Premises SSAS
– Deployment
Why Azure?

34. SSAS Fundamentals

35. The Model, regardless of type, will be the Semantic Layer for the
analytics user
SSAS Model Types
Multidimensional Model
Tabular Model

36. Online Analytical Processing (Traditional OLAP)
Cubes consist of dimensions and measures
Create cubes with SSDT, manage with SSDT and SSMS
Default Mode (MOLAP) stores imported data on disk (Requires large volume of disk space)
Performance is increased by pre-calculating and pre-loading aggregations
Query data via SSMS, MS Excel (most common), SSRS, Power BI and other BI Tools
SSAS MDM is most commonly queried using MDX (Multidimensional eXpressions)
SSAS server must be configured in Multidimensional Mode, a separate instance will be needed for
Tabular Models
SSAS Multidimensional Model

37. Multidimensional Model Features
Aggregations
Calculated Measures
Drill Through
Drill Down
Hierarchies
KPI’s
Many-to-many relationships
Partitions
Perspectives
Row and Object Level Security

38. Multidimensional Data Sources
Any on premises data source
– Oracle
– IBM
– SAP
– Teradata
– Microsoft (Access, SQL Server, Excel, etc.)
– Any data source with OLEDB (OLAP sources not supported)

39. Multidimensional
Cube Structure
Yellow – Fact Table
Blue – Dimension Table

40. Sample Dimension Usage

41. MDM Sample Calculation (used in aggregations)

42. Partitions and Perspectives
• Perspectives (Logical views for organization
for end users) For example: Subject Area
• Partitions (Slices or chunks of data
optimized for loading data)

43. While query performance of cubes is very fast for large datasets, Loading time can be very long.
The cube is unavailable while loading. Dimensions and aggregations will need to be recalculated
every time the cube is processed.
• Partitions allow for horizontal slices of data to be loaded (By Year, Geography, Customer, etc.)
• Incremental partitions can be used to load the most recent data (more often), with historical
partitions loaded less often.
Partitions

44. Perspectives provide horizontal
slices (views) of the data in the
cube
Cubes CANNOT be secured at the
Perspective level
Perspectives

45. Performance enhanced by predefined aggregations
The development to production cycle is longer than most solutions
Multidimensional data structures are rigid. Must be loaded as facts and dimensions. Flattened
summary views not supported for loading
Default storage is MOLAP. Direct Query is available (ROLAP), but does not utilize pre-calculated and
loaded aggregations
Many companies use a hybrid approach (HOLAP). Larger facts using MOLAP, smaller facts using
ROLAP.
Not included in Azure Analysis Services
SSAS Multidimensional Model Takeaways

46. Overview
SSAS Tabular Model
A Tabular Model is a relational, columnar, multi-
threaded SSAS database that utilizes the xVelocity
(Vertipaq) compression technology in the following
modes:
• In Memory (Default)
• Direct Query

47. Design
Design, Manage, Explore
Manage Explore

48. Metadata
The Tabular Model utilizes the relationships inherited
from its data sources, where applicable.

49. Data Compression
Multidimensional models – 3x compression
Tabular models – 10x compression

50. Feature In Memory Direct Query MDM
Calculated Column Yes No No
Calculated Measure Yes Yes Yes
Calculated Table Yes No No
Hierarchies Yes Yes Yes, more flexibility
KPI’s Yes Yes Yes
Partitions Yes Yes Yes
Perspectives Yes Yes Yes
MDM type Aggregations No No Yes
Multiple data sources Yes No Yes
Row Level Security Yes (Row Filter) Only from database Yes
Data Modification Language
(DML)
DAX, MDX DAX MDX, DMX
SSAS Tabular Model Features

51. https://docs.microsoft.com/en-us/sql/analysis-services/comparing-tabular-and-multidimensional-solutions-ssas
Feature Comparison (Complete List)

52. Data Source In Memory Direct Query
Multiple Yes No
Relational DB Yes Yes
MDM Cube Yes No
Spreadsheet Yes No
Text Yes No
Data Feeds Yes No
Azure SQL Database Yes Yes
Many-to-many relationships Requires Bi-directional Cross filter
and DAX
Requires Bi-directional Cross filter
and DAX
Tabular Model Data Sources

53. Best performance/compression
Partitions load in parallel
Data limited by installed memory, also no single
column in a table can have more than 2 billion
distinct values.
Full DAX capabilities
DAX Time Intelligence
DAX or MDX
Multiple data sources
Tabular In Memory vs Direct Query
Direct Query
Only stores metadata (with exception of sample
partitions)
Does not consume memory for storage
Useful for instances without large memory, no data
size limitation
Does not support DAX calculated columns or tables
Calculated measures are supported
DAX, but not Time Intelligence
Single data source (Process other data sources
through SQL Server)
Inherits Windows AD RLS (may require Kerberos)
In Memory

54. SSAS Tabular Model Relational View

55. SSAS Tabular Model Data View with Measures

56. SSAS Tabular KPI’s
Simple interface
1. Base Measure
2. Target (Measure or literal
value)
3. Target ranges
4. Icon style

57. Azure Analysis Services

58. Coverage Specs
Model(s) Tabular Model >= 1200 Compatibility
Design Tool SSDT, Web Designer (Preview) SSMS to manage
Deployment SSDT
Data Sources Same as SSAS Tabular and more Local sources require on
premises data gateway
Features Fully compatible with SSAS Tabular
Modes In Memory, Direct Query
Azure Analysis Services – Overview

59. Azure data source In-memory Direct Query
Azure SQL Database Yes Yes
Azure SQL Data Warehouse Yes Yes
Azure Blob Storage Yes No
Azure Table Storage Yes No
Azure Cosmos DB Yes No
Azure Data Lake Store Yes No
Azure HDInsight HDFS Yes No
Azure HDInsight Spark (Beta) Yes No
Azure Analysis Services - Cloud Data Sources (1400 Compatibility)

60. 1. Login to Azure Portal to copy destination server
name
2. In SSDT (Solution Explorer), right-click the Project
> Properties
3. Under Deployment paste server name
4. In Solution Explorer, right-click Properties, then
select Deploy (You may be prompted to sign into
Azure)
Steps to Deploy On-prem SSAS Tabular to Azure Analysis Services

61. Task Tool
Manage SSMS
Design SSDT, Web Designer
Explore Excel, Power BI Desktop, SSRS?, Any
supported BI Tool
Interacting with Azure Analysis Services

62. Why Azure?

63. Better with Azure
Azure Integration
Azure Active Directory
Azure Data Factory
Azure Automation and Functions
Rapid Development/Deployment
Create server in minutes
Model data in SSDT or Web Designer
Import model from PBIX file
Scalable
Tier based support (price based on needs)
Use query pools to replicate models to improve
client performance
Use geographical Azure regions to minimize
latency. Deploy in multiple regions for high
availability
Built on SSAS Foundation
Familiar tools (SSMS, SSDT)
Compatible with SSAS Tabular (>=1200)
TMSL compatible (Scripting Language)
Existing data sources + cloud

64. Power BI Workshop

66. THANK YOU!