Learn how to: Construct a BI and analytical environment that provides the critical functionality that enables your customers to provide timely answers, supporting modern agile business Leverage agile delivery concepts to deliver value in days rather than in months Build a support organization that enables your users to create increased value from your company’s information assets

1. Agile BI: How to Deliver More
Value Faster
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2. About Perficient
Perficient is a leading information technology consulting firm serving clients
throughout North America.
We help clients implement business-driven technology solutions that integrate
business processes, improve worker productivity, increase customer loyalty and
create a more agile enterprise to better respond to new business opportunities.
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3. Perficient Profile
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Founded in 1997
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Public, NASDAQ: PRFT
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2012 revenue $327 million
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Major market locations throughout North America
• Atlanta, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Dallas, Denver,
Detroit, Fairfax, Houston, Indianapolis, Los Angeles, Minneapolis, New York City, Northern
California, Philadelphia, Southern California, St. Louis, Toronto and Washington, D.C.
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Global delivery centers in China, Europe and India
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~2,000 colleagues
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Dedicated solution practices
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~85% repeat business rate
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Alliance partnerships with major technology vendors
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Multiple vendor/industry technology and growth awards
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4. Our Solutions Expertise
Business Solutions
Technology Solutions
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Business Intelligence
Business Process Management
Customer Experience and CRM
Enterprise Performance Management
Enterprise Resource Planning
Experience Design (XD)
Management Consulting
Business Integration/SOA
Cloud Services
Commerce
Content Management
Custom Application Development
Education
Information Management
Mobile Platforms
Platform Integration
Portal & Social
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5. Our Speaker
Bill Busch
Sr. Solutions Architect, Enterprise Information Solutions, Perficient
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Leads Perficient's enterprise data practice
Specializes in business-enabling BI solutions that enable the agile
enterprise
Responsible for executive data strategy, roadmap development, and
the delivery of high-impact solutions that enable organizations to
leverage enterprise data
Bill has over 15 years of experience in executive leadership, business
intelligence, data warehousing, data governance, master data
management, information/data architecture, and analytics
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6. Objectives
• Reviewing challenges with BI as usual
• Defining Agile BI
• Agile BI attributes
• Wrap-up
• Question and answer
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7. Challenges with BI As Usual
• Systems tend to be hard to
change
o Significant pre-planning
o Investment in change is high
o Design and build processes are
complex
• Business users are reliant on IT
• IT resources are limited, but
expectations are growing
o
o
o
o
o
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More data sources
Bigger data
More complex data
Increased data velocity
More business units to service
Quicker time-to-value
o Add new data to the BI system
o New drill paths
o Creating content (think
dashboards and reports)
o Publishing content usually
requires IT interaction
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8. What is Agile Business Intelligence?
IT Perspective
The utilization of agile
SDLC processes to
deliver BI content to
business users
Business
Perspective
The ability to leverage
information to make better
decisions at the speed of
business
“Nothing is more agile than a business user creating their own report.”
Claudia Imhoff
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9. Agile BI System Attributes
Easily changed
Usable and extensible
Agile
Business
Intelligence
Systems
Jointly
governed
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10. Agile BI System Attributes
Easily changed
Usable and extensible
Agile
Business
Intelligence
Systems
Jointly
governed
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11. Easily Changed Systems
• Layered architecture
• “Early” access to data
• Architecture to support realities of new
breed of business-enabled tools
o Data discovery and analytical tools
• Minimize ETL and modeling in early
iterations
• Architecture aligned delivery process
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12. Typical Layered Agile BI Architecture
Metadata
Data Discovery/
Visualization
Advanced Analytics
BI/OLAP/Reporting
/ Dashboards
Performance
Management
Data Access Services
Product
Location
Source
Systems
Customer
………
Master Data
Table
1
Table
2
ERP
Table
1
Table
2
.
.
.
Table
n
.
.
.
Table
n
Text, Files
Down
Stream Data
Feeds
Files/
Unstructured
Data
Unstructured
Data
Data Pool
Extraction &
Loading
Raw Data
Standardized
Data
Data Integration
(Views, ETL,
Stored Proc)
Data Warehouse
(Views Where
Possible)
Data Mart
(Views)
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13. Data Pool Considerations
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Primary access to minimally processed data
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Modeling is not really required at this point, however, business
metadata collection is required.
Encourage power users to leverage the data utilizing a
meta-data centric data discovery tool
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o
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Excellent source of requirements
Helps prioritize what is truly important to the business
Define standard decision trees for common architectural
decisions (Think cookie cutter)
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Focus minimizing the analysis required for moving move of data to
data pool
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Storage options, Like compression, partitioning, maintaining raw data
o
Hadoop FS vs. Traditional DB
TOT_HRS RT_D_H EXT_CST
288
225
64800
440
165
72600
480
195
93600
480
145
69600
TOT_HRS RT_D_H EXT_CST
288
225
64800
440
165
72600
480
195
93600
480
145
69600
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14. Iterate on Data Management
 Certify data, establish
complete meta data
including full source to
target lineage
 Enhance data in Data Pool
by standardizing values to
common business values
& master data
 Model new data
 Move data as is to Data
Pool
 Inventory data, establish
known business rules and
lineage to immediate source
 Publish data for business
content creator/ power users
in DD tools
 Incremental updates (no
more than daily)
 Move to more frequent
updates
 Enhance data with
business rules for data
substitution and adequacy
 Integrate like facts
 Publish integrated model
 Leverage enterprise
reporting and dashboards
(IT developed)
 Publish data in DD tools
 Implement robust data
governance
 Develop first aggregates
 Start initial data
stewardship
 Establish ownership at
department level
Iteration 1
Iteration 2
Iteration 3
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15. Example Build-Out
Mobile Access
Data Discovery
Data Access Views
Table 1
Table 2
Social Data
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ERP
Table n
Operational
File System
Unstructured
Data
Source
Systems
Extraction &
Loading
Data Pool
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16. Example Build-Out
Portal and Mobile Access
Data Discovery
Data Access Views
Customer
Sales Hierarchy
Calendar
Geography
Product
Common Tables
Table 1
Table 2
Social Data
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.
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Master Data Hub
ERP
Table n
Operational
File System
Unstructured
Data
Source
Systems
Extraction &
Loading
Data Pool
Integration
Layer (Stored
Proc and Views)
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17. Example Build-Out
Portal and Mobile Access
Data Discovery
| Analytical Tools
|
Traditional BI
Data Access Views
Customer
Sales Hierarchy
Calendar
Geography
Product
Common Tables
Table 1
Table 2
Social Data
.
.
.
Master Data Hub
ERP
Table n
Operational
File System
Data Warehouse/
Data Marts
Unstructured
Data
Source
Systems
Extraction &
Loading
Data Pool
Integration
Layer (Stored
Proc and Views)
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18. Agile BI System Attributes
Usable and extensible
Easily changed
Agile
Business
Intelligence
Systems
Jointly
governed
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19. Usable and Extensible Systems
Business Enablement Provided by Non-Traditional BI Tools
Repeat as Necessary
Quantify The
Problem
Determine/
Modify
Strategy
Find & Locate
Information
Source &
Prepare
Information
Construct &
Perform
Analysis
Format /
Interpret
Analysis
Determine
Monitoring
Strategy
Find & Locate
Information
Source &
Prepare
Information
Create and
Publish BI
Content
Determine
Ongoing Need
& Value
Share
Conclusions
Traditional BI
IT Creates
Enterprise BI
Content
Traditional BI
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20. Traditional BI and Data Discovery
Traditional
Business
Intelligence
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Data
Discovery
Drives Need for
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Proven Answers to
Known Questions
High-Value Reporting
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Fast Answers To
New Questions
Early/Short-term
Reporting
Specifies new KPIs and BI
Content for
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21. Agile BI System Attributes
Easily changed
Usable and extensible
Agile
Business
Intelligence
Systems
Jointly
governed
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22. Governing the Agile BI Environment
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Both IT and Business Users are Providing Value in
an Agile BI Environment
o Must share governance
o Must share responsibility
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Develop two-tier support system – Content creators
must support end-users
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Data Quality is a business decision – define options
and let business choose their investment level
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SDLC’s need to be tailored to enable BI systems to
deliver value quickly
o Push as much into BAU processes
o Factory type delivery for data
o Agile processes for BI content
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Establish a BI/Analytics COE focused on driving
adoption/usage and data access
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Develop a BI scorecard of what is important to the
business
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23. Wrapping Up
• Well managed BI environments
that enable business agility, just
do not happen!
• They require an overall strategic
approach that coordinates people
process, and technology.
• Develop your BI strategy with the
overall vision to enable Agile BI
• Remain business focused let the
business choose what they want
to fund
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24. Questions?
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25. Daily unique insights
on content
management, user
experience, portals
and other enterprise
information technology
solutions across a
variety of industries.
Perficient.com/SocialMedia
Facebook.com/Perficient
Twitter.com/Perficient
http://blogs.perficient.com/bus
inessintelligence/
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26. Thank you for your time
and attention today.
Please visit us at Perficient.com