agile bi: how to deliver more value in less time
Post on 18-Nov-2014
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Agile BI: How to Deliver More Value Faster
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.
About Perficient
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• Founded in 1997
• Public, NASDAQ: PRFT
• 2012 revenue $327 million
• 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.
• Global delivery centers in China, Europe and India
• ~2,000 colleagues
• Dedicated solution practices
• ~85% repeat business rate
• Alliance partnerships with major technology vendors
• Multiple vendor/industry technology and growth awards
Perficient Profile
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Business Solutions• Business Intelligence• Business Process Management• Customer Experience and CRM• Enterprise Performance Management• Enterprise Resource Planning• Experience Design (XD)• Management Consulting
Technology Solutions• Business Integration/SOA• Cloud Services• Commerce• Content Management• Custom Application Development• Education• Information Management• Mobile Platforms• Platform Integration• Portal & Social
Our Solutions Expertise
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Our Speaker
Bill BuschSr. Solutions Architect, Enterprise Information Solutions, Perficient
• 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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Objectives
• Reviewing challenges with BI as usual
• Defining Agile BI
• Agile BI attributes
• Wrap-up
• Question and answer
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Challenges with BI As Usual
• Systems tend to be hard to changeo Significant pre-planningo Investment in change is higho Design and build processes are
complex
• Business users are reliant on ITo Add new data to the BI systemo New drill pathso Creating content (think
dashboards and reports)o Publishing content usually
requires IT interaction
• IT resources are limited, but expectations are growingo More data sourceso Bigger data o More complex datao Increased data velocityo More business units to serviceo Quicker time-to-value
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What is Agile Business Intelligence?
IT PerspectiveThe 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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Agile Business
Intelligence Systems
Usable and extensibleEasily changed
Jointly governed
Agile BI System Attributes
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Agile Business
Intelligence Systems
Usable and extensibleEasily changed
Jointly governed
Agile BI System Attributes
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Easily Changed Systems
• Layered architecture
• “Early” access to data
• Architecture to support realities of new breed of business-enabled toolso Data discovery and analytical tools
• Minimize ETL and modeling in early iterations
• Architecture aligned delivery process
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Data Discovery/ VisualizationMetadata Advanced Analytics BI/OLAP/Reporting
/ Dashboards
Typical Layered Agile BI Architecture
ERP
Source Systems
.
.
.
Table 2
Table n
Data Integration
(Views, ETL, Stored Proc)
Extraction & Loading
Raw Data Data Mart(Views)
Data Warehouse(Views Where
Possible)
Performance Management
Down Stream Data Feeds
StandardizedData
Table 1
.
.
.
Table 2
Table n
Portal and Mobile Access
Master Data
Product Customer
Location ………
Data Access Services
Text, Files
Unstructured Data
Data Pool
Table 1
Files/ Unstructured
Data
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• Primary access to minimally processed datao 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 toolo Excellent source of requirementso Helps prioritize what is truly important to the business
• Define standard decision trees for common architectural decisions (Think cookie cutter)o Focus minimizing the analysis required for moving move of data to
data poolo Storage options, Like compression, partitioning, maintaining raw datao Hadoop FS vs. Traditional DB
Data Pool Considerations
TOT_HRS RT_D_H EXT_CST288 225 64800440 165 72600480 195 93600480 145 69600
TOT_HRS RT_D_H EXT_CST288 225 64800440 165 72600480 195 93600480 145 69600
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Iterate on Data Management
Iteration 1 Iteration 2 Iteration 3
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)
Establish ownership at department level
Enhance data in Data Pool by standardizing values to common business values & master data
Model new data
Move to more frequent updates
Enhance data with business rules for data substitution and adequacy
Develop first aggregates
Start initial data stewardship
Certify data, establish complete meta data including full source to target lineage
Integrate like facts
Publish integrated model
Leverage enterprise reporting and dashboards (IT developed)
Publish data in DD tools
Implement robust data governance
Increasing Value
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Example Build-Out
Data Discovery
Table 1
.
.
.
Table 2
Table n
Data Pool
Mobile Access
Data Access Views
Social Data
Operational
ERP
Extraction & Loading
Source Systems
Unstructured Data
File System
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Example Build-Out
Data Discovery
Table 1
.
.
.
Table 2
Table n
Data Pool
Portal and Mobile Access
Customer
Calendar
Product
Geography
Sales Hierarchy
Common Tables
Data Access Views
Master Data Hub
Social Data
Operational
ERP
Extraction & Loading
Source Systems
Unstructured Data
File System
Integration Layer (Stored
Proc and Views)
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Example Build-Out
Data Discovery | Analytical Tools | Traditional BI
Table 1
.
.
.
Table 2
Table n
Data Pool
Data Warehouse/ Data Marts
Portal and Mobile Access
Customer
Calendar
Product
Geography
Sales Hierarchy
Common Tables
Data Access Views
Master Data Hub
Social Data
Operational
ERP
Extraction & Loading
Source Systems
Unstructured Data
File System
Integration Layer (Stored
Proc and Views)
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Agile Business
Intelligence Systems
Usable and extensibleEasily changed
Jointly governed
Agile BI System Attributes
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Usable and Extensible Systems
Quantify The Problem
Determine/ Modify
Strategy
Find & Locate Information
Source & Prepare
Information
Construct & PerformAnalysis
Format / Interpret Analysis
Share Conclusions
Repeat as Necessary
Traditional BI
Determine Monitoring Strategy
Find & Locate Information
Source & Prepare
Information
Create and Publish BI Content
Determine Ongoing Need
& Value
IT Creates Enterprise BI
Content
Business Enablement Provided by Non-Traditional BI Tools
Traditional BI
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Drives Need for
Traditional BusinessIntelligence
• Proven Answers to Known Questions
• High-Value Reporting
DataDiscovery
• Fast Answers ToNew Questions
• Early/Short-term Reporting
Specifies new KPIs and BI Content for
Traditional BI and Data Discovery
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Agile Business
Intelligence Systems
Usable and extensibleEasily changed
Jointly governed
Agile BI System Attributes
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Governing the Agile BI Environment
• Both IT and Business Users are Providing Value in an Agile BI Environmento Must share governanceo Must share responsibility
• Develop two-tier support system – Content creators must support end-users
• Data Quality is a business decision – define options and let business choose their investment level
• SDLC’s need to be tailored to enable BI systems to deliver value quicklyo Push as much into BAU processeso Factory type delivery for datao Agile processes for BI content
• Establish a BI/Analytics COE focused on driving adoption/usage and data access
• Develop a BI scorecard of what is important to the business
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• 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
Wrapping Up
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Questions?
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Perficient.com/SocialMediaFacebook.com/Perficient
Twitter.com/Perficienthttp://blogs.perficient.com/
businessintelligence/
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Thank you for your timeand attention today.
Please visit us at Perficient.com
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