SlideShare a Scribd company logo
1 of 22
Make Better Decisions with Your Data


Dan English            Aaron Lowe           Alan Wernke
Principal Consultant   Senior Consultant    Practice Director, Enterprise Data Services
dane@magenic.com       aaronl@magenic.com
Who are we? – Dan and Aaron
                                                      Aaron Lowe                           Alan Wernke
            Dan English
                                            http://vendoran.spaces.live.com/
    http://denglishbi.spaces.live.com                                          •   Practice Director, Enterprise
                                                                                   Data Services
                                        •     10+ years experience in SQL
•   Developing with Microsoft                                                  •   18+ years experience with data
                                              Server development,
    technologies for over 10 years                                                 services
                                              administration and design
•   Over 5 years experience with                                               •   10 years at Microsoft
                                        •     Experience in advanced
    Data Warehousing and Business                                              •   30 years in Information
                                              administration, which includes
    Intelligence                                                                   Technology
                                              performance optimization,
•   Experienced in ETL and
                                              backup and recovery, migration
    Analysis Services development,
                                              strategies and replication, as
    requirements gathering and data
                                              well as security and auditing
    modeling
                                              techniques.
•   Microsoft Certified IT
                                        •     Microsoft Certified IT
    Professional (MCITP) and
                                              Professional (MCITP) and
    Microsoft Certified Technology
                                              Microsoft Certified Technology
    Specialist (MCTS)
                                              Specialist (MCTS)
                                        •     Masters degree in Information
                                              Systems Management
Who are we? – Magenic
 Founded in 1995, Magenic is a technical consulting firm
    focused exclusively on Microsoft technologies and has
    designed and delivered more than 500 Microsoft-based
    applications
   Headquartered in Minneapolis, with offices in Chicago,
    Boston, Atlanta and San Francisco
   2005 Microsoft Partner of the Year, Custom
    Development Solutions – Technical Innovation
   2007 Microsoft Partner of the Year Finalist, Data
    Management
   Microsoft Gold Certified Partner and National Systems
    Integrator
   40 Enterprise Data Services (EDS) consultants
Today‟s Agenda
•   What is Business Intelligence (BI)?
•   What are Spreadmarts and Data Marts?
•   What is a Business Intelligence Platform?
•   Where do I go from here?
•   Questions?
What is Business Intelligence (BI)?

The Gartner Group coined the term Business Intelligence in
the mid-1990s and defined it as follows:

“An interactive process for exploring and analyzing structured
and domain-specific information to discern trends or patterns,
thereby deriving insights and drawing conclusions. The
business intelligence process includes communicating
findings and effecting change.”


                                  (Source: A glossary on the web site www.gartner.com)
BI Maturity Model – where are you at?




  STRUCTURE:   Mgmt Reports   Spreadsheets    Data Marts   Data Warehouses   Enterprise DW     BI Services


                System        Individual     Department        Division       Enterprise     Inter-Enterprise
  SCOPE:




                                                            By Wayne Eckerson, Director of Research, TDWI
Spreadmart BI – Infant (2nd) Stage
          Are the users                                                                  What happens when
                                   Did they extract all     How long does it
          extracting and                                                                 the person responsible
                                   of the necessary         take to extract
          reporting on the                                                               for the report goes on
                                   data to allow            the data and how
          right data?                                                                    vacation or is sick or
                                   management to ask        clean is it once it
                                                                                         leaves the company?
                                   further questions?       is extracted?




                               MS Access              MS Excel             MS PowerPoint         Business Users



                                           Do they have enough
                                                                          What logic is
Source Data                                data collected to
                                                                          being applied and
                                           perform yearly
              Is all of the data
                                                                          is this common
                                           comparisons or
              available in the
                                                                          logic within the
                                           trends over time?
              source system?
                                                                          organization?
Datamart BI – Child (3rd) Stage




                         OLAP Engine
              Datamart




Source Data                            Business Users
Spreadmart vs. Datamart BI
Spreadmart                                       Datamart

                  • High end-user control
                                                            • Shared/consistent view of data
                  • Easy to generate
                                                            • Centralized logic
                  • Can be pieced
 Pros                                                       • Highly interactive (slice-and-
                    together
                                                  Pros        dice)
                  • Highly customizable for
                                                            • Secured
                    the intended audience
                                                            • Very Flexible
                  • Low cost solution
                                                            • Extremely Fast response time




             •   Inconsistent view of the data
             •                                                •
                 No centralized logic                             Takes time to generate
 Cons        •                                                •
                 Typically no security applied                    Less end-user control
                                                  Cons
             •                                                •
                 Silos of data throughout                         Costs more to develop
                 organization                                 •   Could potentially introduce
                                                                  new tools (training)
Spreadmart to Datamart Case Study

Spreadmart
 • Excel file report system
 • Lots of embedded business logic and conditional formatting
 • Generated over 1500+ files (most contained multiple reports) with macro
 • Process took approximately 30 hours to run
 • Initial Excel file was created and tested over a 6 month time period
 • If there were any data issues or report creation errors process had to be re-run
 • Not easy to implement additional change requests


Datamart
 • Star schema database engine designed
 • Analysis Service database created with centralized logic
 • Reporting Service reports created and data driven subscription setup
 • Generated same reports in approximately 30 minutes
 • Entire database along with reports was created and tested in 2 month time frame
 • Database and reporting structure extremely flexible to change requests
To BI or Not to BI?

Reasons to BI
 • Integrate data from multiple source systems
 • Create centralized „single version‟ of the truth
 • Centralized business logic and calculations
 • Gain insight into unknown and disparate areas of the organization
 • Maintain competitive edge
 • Provide additional services to customers



Reasons to Not BI
 • Do not have the time and resources
 • Do not have any competition
 • Not interested in evaluating your organization
BI Platform – what is it?
“Gartner defines BI platforms as those that enable
  users to build applications that help organizations
  learn and understand their business. It divides
  these capabilities into the functions of integration,
  information delivery, and analysis.”
                    InformationWeek, Microsoft Gets Gartner's Business Intelligence Top Ranking,
                    Mary Hayes Weier, February 5, 2008
Magic Quadrant for BI Platforms, 2008
Microsoft strengths:
• Pricing
• Tight integration with MS Office
• PerformancePoint Server
• SQL Server
• Extremely large Microsoft
   Developer community
• Attractive to those already on
   Microsoft platform




                                     Source: Gartner (January 2008)
                                     Gartner RAS Core Research Note G00154227
Microsoft BI Tool Offerings
                                   DELIVERY

                                SharePoint Server

                                           Analytic
                                Excel                 Scorecards   Plans
        Reports   Dashboards
                                            Views
                               Workbooks

       END USER TOOLS & PERFORMANCE MANAGEMENT APPS
                  Excel                     PerformancePointServer

                                BI PLATFORM
             SQL Server                            SQL Server
          Reporting Services                     Analysis Services
                               SQL Server DBMS

                     SQL Server Integration Services
SharePoint Business Intelligence
 • Excel Services
 • Dashboards
 • Key Performance Indicators (KPI‟s)
 • Filter Web Parts
 • Report Center/Report Library (Integrate Reporting Services)
PerformancePoint Offering




           Performance Management Cycle
PerformancePoint Server
PerformancePoint Server
Source Information
Business Intelligence Definition – http://www.perceptualedge.com/blog/?p=31

BI Maturity Model – http://www.dmreview.com/issues/20041101/1012391-1.html or
http://www.tdwi.org/publications/display.aspx?ID=7199

BI Platform Definition –
http://www.informationweek.com/news/windows/microsoft_news/showArticle.jhtml?articleID=
206104502

Magic Quadrant –
http://mediaproducts.gartner.com/reprints/microsoft/vol7/article3/article3.html
Resources
 Microsoft BI Site
 http://www.microsoft.com/bi/

 SharePoint BI Features Introduction
 http://office.microsoft.com/en-us/sharepointserver/HA100872181033.aspx

 PerformancePoint Home Site
 http://www.microsoft.com/business/performancepoint/default.aspx

 PerformancePoint Developer Portal
 http://msdn.microsoft.com/en-us/office/bb660518.aspx

 Channel9 MSDN BI Screencasts
 http://channel9.msdn.com/Showforum.aspx?forumid=38&tagid=277

 SQL Server 2008 Home Site
 http://www.microsoft.com/sqlserver/2008/en/us/default.aspx

 Microsoft Virtual Labs (TechNet and MSDN)
 http://www.microsoft.com/events/vlabs/default.mspx

 Magenic Blogs
 http://blog.magenic.com/blogs
How Do We Get Started?
  Complimentary Strategy Session
     Up to 4 hours
     Deliverable:
         Customized BI Recommendations
  Business Intelligence Benefit Assessment
     5 days
     Deliverables
         Initial proof-of-concept development custom to your
           company‟s unique reporting needs
         High level BI architecture
         Mentoring & Knowledge Transfer
  Email info@magenic.com for more information
Contact Information – Thank You!

    Contact us to find out how your business can benefit
    from a complimentary strategy session with one of our
    consultants and look into one of our BI quickstart
    engagements.

    Dan - http://denglishbi.spaces.live.com
    Aaron - http://vendoran.spaces.live.com
    Magenic - info@magenic.com

More Related Content

What's hot

NRF BigIdeas_Big Data in Retail_AN16
NRF BigIdeas_Big Data in Retail_AN16NRF BigIdeas_Big Data in Retail_AN16
NRF BigIdeas_Big Data in Retail_AN16Bill Lombardi
 
6 STEPS TO CREATE A SUCCESSFUL BUSINESS INTELLIGENCE STRATEGY
6 STEPS TO CREATE A SUCCESSFUL BUSINESS INTELLIGENCE STRATEGY6 STEPS TO CREATE A SUCCESSFUL BUSINESS INTELLIGENCE STRATEGY
6 STEPS TO CREATE A SUCCESSFUL BUSINESS INTELLIGENCE STRATEGYGeorge Beaton
 
5 Essential Practices for the Data Driven Organization
5 Essential Practices for the Data Driven Organization5 Essential Practices for the Data Driven Organization
5 Essential Practices for the Data Driven OrganizationVivastream
 
Business Analytics
Business Analytics Business Analytics
Business Analytics Infosys
 
I Npd Mfei 5 10
I Npd Mfei 5 10I Npd Mfei 5 10
I Npd Mfei 5 10kbmcgourty
 
A treatise on SAP CRM information reporting
A treatise on SAP CRM information reportingA treatise on SAP CRM information reporting
A treatise on SAP CRM information reportingVijay Raj
 
Marcoccio10 22
Marcoccio10 22Marcoccio10 22
Marcoccio10 22jaikms kms
 
5 Essential Practices for the Data Driven Organization
5 Essential Practices for the Data Driven Organization5 Essential Practices for the Data Driven Organization
5 Essential Practices for the Data Driven OrganizationVivastream
 
Competitive Intelligence & Big Data
Competitive Intelligence & Big DataCompetitive Intelligence & Big Data
Competitive Intelligence & Big DataCID GmbH
 
Be Digital or Die - Big Data in Financial Services
Be Digital or Die - Big Data in Financial ServicesBe Digital or Die - Big Data in Financial Services
Be Digital or Die - Big Data in Financial ServicesFintricity
 
Customer analytics. Turn big data into big value
Customer analytics. Turn big data into big valueCustomer analytics. Turn big data into big value
Customer analytics. Turn big data into big valueJosep Arroyo
 
Business Process Re-Engineering Case Study
Business Process Re-Engineering Case StudyBusiness Process Re-Engineering Case Study
Business Process Re-Engineering Case StudyKanchana Weerasinghe
 
Customer analytics software - Quiterian
Customer analytics software - QuiterianCustomer analytics software - Quiterian
Customer analytics software - QuiterianJosep Arroyo
 
When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...
When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...
When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...Birst
 
BUSINESS INTELLIGENCE OVERVIEW & APPLICATIONS
BUSINESS INTELLIGENCE OVERVIEW & APPLICATIONSBUSINESS INTELLIGENCE OVERVIEW & APPLICATIONS
BUSINESS INTELLIGENCE OVERVIEW & APPLICATIONSGeorge Krasadakis
 

What's hot (20)

Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
 
NRF BigIdeas_Big Data in Retail_AN16
NRF BigIdeas_Big Data in Retail_AN16NRF BigIdeas_Big Data in Retail_AN16
NRF BigIdeas_Big Data in Retail_AN16
 
6 STEPS TO CREATE A SUCCESSFUL BUSINESS INTELLIGENCE STRATEGY
6 STEPS TO CREATE A SUCCESSFUL BUSINESS INTELLIGENCE STRATEGY6 STEPS TO CREATE A SUCCESSFUL BUSINESS INTELLIGENCE STRATEGY
6 STEPS TO CREATE A SUCCESSFUL BUSINESS INTELLIGENCE STRATEGY
 
A9 schubert
A9 schubertA9 schubert
A9 schubert
 
5 Essential Practices for the Data Driven Organization
5 Essential Practices for the Data Driven Organization5 Essential Practices for the Data Driven Organization
5 Essential Practices for the Data Driven Organization
 
Business Analytics
Business Analytics Business Analytics
Business Analytics
 
I Npd Mfei 5 10
I Npd Mfei 5 10I Npd Mfei 5 10
I Npd Mfei 5 10
 
Tally 1 K E Y
Tally 1 K E YTally 1 K E Y
Tally 1 K E Y
 
Dat analytics all verticals
Dat analytics all verticalsDat analytics all verticals
Dat analytics all verticals
 
A treatise on SAP CRM information reporting
A treatise on SAP CRM information reportingA treatise on SAP CRM information reporting
A treatise on SAP CRM information reporting
 
Marcoccio10 22
Marcoccio10 22Marcoccio10 22
Marcoccio10 22
 
5 Essential Practices for the Data Driven Organization
5 Essential Practices for the Data Driven Organization5 Essential Practices for the Data Driven Organization
5 Essential Practices for the Data Driven Organization
 
Competitive Intelligence & Big Data
Competitive Intelligence & Big DataCompetitive Intelligence & Big Data
Competitive Intelligence & Big Data
 
Be Digital or Die - Big Data in Financial Services
Be Digital or Die - Big Data in Financial ServicesBe Digital or Die - Big Data in Financial Services
Be Digital or Die - Big Data in Financial Services
 
Customer analytics. Turn big data into big value
Customer analytics. Turn big data into big valueCustomer analytics. Turn big data into big value
Customer analytics. Turn big data into big value
 
Business Process Re-Engineering Case Study
Business Process Re-Engineering Case StudyBusiness Process Re-Engineering Case Study
Business Process Re-Engineering Case Study
 
Customer analytics software - Quiterian
Customer analytics software - QuiterianCustomer analytics software - Quiterian
Customer analytics software - Quiterian
 
When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...
When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...
When Salesforce Isn’t Enough: Using Birst to Accelerate Your Business and Und...
 
BUSINESS INTELLIGENCE OVERVIEW & APPLICATIONS
BUSINESS INTELLIGENCE OVERVIEW & APPLICATIONSBUSINESS INTELLIGENCE OVERVIEW & APPLICATIONS
BUSINESS INTELLIGENCE OVERVIEW & APPLICATIONS
 
Competitive Intelligence
Competitive IntelligenceCompetitive Intelligence
Competitive Intelligence
 

Viewers also liked

201406 IASA: Analytics Maturity - Unlocking The Business Impact
201406 IASA: Analytics Maturity - Unlocking The Business Impact201406 IASA: Analytics Maturity - Unlocking The Business Impact
201406 IASA: Analytics Maturity - Unlocking The Business ImpactSteven Callahan
 
Competing on analytics
Competing on analyticsCompeting on analytics
Competing on analyticsGreg Seltzer
 
The CDO Agenda: Competing with Data - Strategy and Organization
The CDO Agenda: Competing with Data - Strategy and OrganizationThe CDO Agenda: Competing with Data - Strategy and Organization
The CDO Agenda: Competing with Data - Strategy and OrganizationDATAVERSITY
 
AIA SOX Conference May 2009 - CCM & Data Analytics
AIA SOX Conference May 2009 - CCM & Data AnalyticsAIA SOX Conference May 2009 - CCM & Data Analytics
AIA SOX Conference May 2009 - CCM & Data Analyticsprosenzw69
 
In-Database Predictive Analytics
In-Database Predictive AnalyticsIn-Database Predictive Analytics
In-Database Predictive AnalyticsJohn De Goes
 
Post-Free: Life After Free Monads
Post-Free: Life After Free MonadsPost-Free: Life After Free Monads
Post-Free: Life After Free MonadsJohn De Goes
 
Increasing Your Business Data and Analytics Maturity
Increasing Your Business Data and Analytics MaturityIncreasing Your Business Data and Analytics Maturity
Increasing Your Business Data and Analytics MaturityDATAVERSITY
 
How to Become a Thought Leader in Your Niche
How to Become a Thought Leader in Your NicheHow to Become a Thought Leader in Your Niche
How to Become a Thought Leader in Your NicheLeslie Samuel
 

Viewers also liked (9)

201406 IASA: Analytics Maturity - Unlocking The Business Impact
201406 IASA: Analytics Maturity - Unlocking The Business Impact201406 IASA: Analytics Maturity - Unlocking The Business Impact
201406 IASA: Analytics Maturity - Unlocking The Business Impact
 
Competing on analytics
Competing on analyticsCompeting on analytics
Competing on analytics
 
Competing on analytics
Competing on analyticsCompeting on analytics
Competing on analytics
 
The CDO Agenda: Competing with Data - Strategy and Organization
The CDO Agenda: Competing with Data - Strategy and OrganizationThe CDO Agenda: Competing with Data - Strategy and Organization
The CDO Agenda: Competing with Data - Strategy and Organization
 
AIA SOX Conference May 2009 - CCM & Data Analytics
AIA SOX Conference May 2009 - CCM & Data AnalyticsAIA SOX Conference May 2009 - CCM & Data Analytics
AIA SOX Conference May 2009 - CCM & Data Analytics
 
In-Database Predictive Analytics
In-Database Predictive AnalyticsIn-Database Predictive Analytics
In-Database Predictive Analytics
 
Post-Free: Life After Free Monads
Post-Free: Life After Free MonadsPost-Free: Life After Free Monads
Post-Free: Life After Free Monads
 
Increasing Your Business Data and Analytics Maturity
Increasing Your Business Data and Analytics MaturityIncreasing Your Business Data and Analytics Maturity
Increasing Your Business Data and Analytics Maturity
 
How to Become a Thought Leader in Your Niche
How to Become a Thought Leader in Your NicheHow to Become a Thought Leader in Your Niche
How to Become a Thought Leader in Your Niche
 

Similar to Make Better Decisions With Your Data 20080916

B13 Driving Business Intelligence
B13 Driving Business IntelligenceB13 Driving Business Intelligence
B13 Driving Business IntelligenceJohnRobson
 
B13 Driving Business Intelligence John Robson
B13 Driving Business Intelligence John RobsonB13 Driving Business Intelligence John Robson
B13 Driving Business Intelligence John RobsonProvoke Solutions
 
20100430 introduction to business objects data services
20100430 introduction to business objects data services20100430 introduction to business objects data services
20100430 introduction to business objects data servicesJunhyun Song
 
Spreadmart To Data Mart BISIG Presentation
Spreadmart To Data Mart BISIG PresentationSpreadmart To Data Mart BISIG Presentation
Spreadmart To Data Mart BISIG PresentationDan English
 
Intellinet Overview 2009
Intellinet Overview 2009Intellinet Overview 2009
Intellinet Overview 2009mclevenger
 
Corporate-training-for-msbi-course-in-mumbai
Corporate-training-for-msbi-course-in-mumbaiCorporate-training-for-msbi-course-in-mumbai
Corporate-training-for-msbi-course-in-mumbaiUnmesh Baile
 
2009 Intellinet Overview
2009 Intellinet Overview2009 Intellinet Overview
2009 Intellinet OverviewMark Seeley
 
Predictive Analytics with IBM Cognos 10
Predictive Analytics with IBM Cognos 10Predictive Analytics with IBM Cognos 10
Predictive Analytics with IBM Cognos 10Senturus
 
Information på agendaen
Information på agendaenInformation på agendaen
Information på agendaenIBM Danmark
 
Bpm and-beyond-slide
Bpm and-beyond-slideBpm and-beyond-slide
Bpm and-beyond-slideAericon
 
RoMT - Part 2 Marketing Technology Webinar
RoMT - Part 2 Marketing Technology WebinarRoMT - Part 2 Marketing Technology Webinar
RoMT - Part 2 Marketing Technology WebinarSmart Insights
 
What is an information professional?
What is an information professional?What is an information professional?
What is an information professional?John Mancini
 
The Missing Link in Enterprise Data Governance - Automated Metadata Management
The Missing Link in Enterprise Data Governance - Automated Metadata ManagementThe Missing Link in Enterprise Data Governance - Automated Metadata Management
The Missing Link in Enterprise Data Governance - Automated Metadata ManagementDATAVERSITY
 
Module 3 Adapative Customer Experience Final
Module 3 Adapative Customer Experience FinalModule 3 Adapative Customer Experience Final
Module 3 Adapative Customer Experience FinalVivastream
 
Gregs BI Presentation
Gregs BI PresentationGregs BI Presentation
Gregs BI Presentationflyjock1
 
DAS Slides: Metadata Management From Technical Architecture & Business Techni...
DAS Slides: Metadata Management From Technical Architecture & Business Techni...DAS Slides: Metadata Management From Technical Architecture & Business Techni...
DAS Slides: Metadata Management From Technical Architecture & Business Techni...DATAVERSITY
 
Manthan biim services and solutions
Manthan   biim services  and solutionsManthan   biim services  and solutions
Manthan biim services and solutionsJaikumar Karuppannan
 

Similar to Make Better Decisions With Your Data 20080916 (20)

B13 Driving Business Intelligence
B13 Driving Business IntelligenceB13 Driving Business Intelligence
B13 Driving Business Intelligence
 
B13 Driving Business Intelligence John Robson
B13 Driving Business Intelligence John RobsonB13 Driving Business Intelligence John Robson
B13 Driving Business Intelligence John Robson
 
Enterprise Services Solutions
Enterprise Services SolutionsEnterprise Services Solutions
Enterprise Services Solutions
 
20100430 introduction to business objects data services
20100430 introduction to business objects data services20100430 introduction to business objects data services
20100430 introduction to business objects data services
 
Spreadmart To Data Mart BISIG Presentation
Spreadmart To Data Mart BISIG PresentationSpreadmart To Data Mart BISIG Presentation
Spreadmart To Data Mart BISIG Presentation
 
Intellinet Overview 2009
Intellinet Overview 2009Intellinet Overview 2009
Intellinet Overview 2009
 
Corporate-training-for-msbi-course-in-mumbai
Corporate-training-for-msbi-course-in-mumbaiCorporate-training-for-msbi-course-in-mumbai
Corporate-training-for-msbi-course-in-mumbai
 
2009 Intellinet Overview
2009 Intellinet Overview2009 Intellinet Overview
2009 Intellinet Overview
 
Predictive Analytics with IBM Cognos 10
Predictive Analytics with IBM Cognos 10Predictive Analytics with IBM Cognos 10
Predictive Analytics with IBM Cognos 10
 
Information på agendaen
Information på agendaenInformation på agendaen
Information på agendaen
 
Bpm and-beyond-slide
Bpm and-beyond-slideBpm and-beyond-slide
Bpm and-beyond-slide
 
RoMT - Part 2 Marketing Technology Webinar
RoMT - Part 2 Marketing Technology WebinarRoMT - Part 2 Marketing Technology Webinar
RoMT - Part 2 Marketing Technology Webinar
 
What is an information professional?
What is an information professional?What is an information professional?
What is an information professional?
 
The Missing Link in Enterprise Data Governance - Automated Metadata Management
The Missing Link in Enterprise Data Governance - Automated Metadata ManagementThe Missing Link in Enterprise Data Governance - Automated Metadata Management
The Missing Link in Enterprise Data Governance - Automated Metadata Management
 
Module 3 Adapative Customer Experience Final
Module 3 Adapative Customer Experience FinalModule 3 Adapative Customer Experience Final
Module 3 Adapative Customer Experience Final
 
Gregs BI Presentation
Gregs BI PresentationGregs BI Presentation
Gregs BI Presentation
 
About Micro
About MicroAbout Micro
About Micro
 
MAnish Kumar-G
MAnish Kumar-GMAnish Kumar-G
MAnish Kumar-G
 
DAS Slides: Metadata Management From Technical Architecture & Business Techni...
DAS Slides: Metadata Management From Technical Architecture & Business Techni...DAS Slides: Metadata Management From Technical Architecture & Business Techni...
DAS Slides: Metadata Management From Technical Architecture & Business Techni...
 
Manthan biim services and solutions
Manthan   biim services  and solutionsManthan   biim services  and solutions
Manthan biim services and solutions
 

More from Dan English

Power BI / AAS Data Model Optimization 101 v2
Power BI / AAS Data Model Optimization 101 v2Power BI / AAS Data Model Optimization 101 v2
Power BI / AAS Data Model Optimization 101 v2Dan English
 
Power BI / AAS Model Optimization
Power BI / AAS Model OptimizationPower BI / AAS Model Optimization
Power BI / AAS Model OptimizationDan English
 
Power BI: Dashboard in an Hour Walk-Through
Power BI: Dashboard in an Hour Walk-ThroughPower BI: Dashboard in an Hour Walk-Through
Power BI: Dashboard in an Hour Walk-ThroughDan English
 
Getting the new year started with Microsoft Power BI!
Getting the new year started with Microsoft Power BI!Getting the new year started with Microsoft Power BI!
Getting the new year started with Microsoft Power BI!Dan English
 
Self-Service BI with SQL Server 2012
Self-Service BI with SQL Server 2012Self-Service BI with SQL Server 2012
Self-Service BI with SQL Server 2012Dan English
 
Inside PerformancePoint
Inside PerformancePointInside PerformancePoint
Inside PerformancePointDan English
 
Intro to BI Semantic Model & Self-Service Reporting with Power View
Intro to BI Semantic Model & Self-Service Reporting with Power ViewIntro to BI Semantic Model & Self-Service Reporting with Power View
Intro to BI Semantic Model & Self-Service Reporting with Power ViewDan English
 
What's New with BI in SQL Server Denali (SQL11)
What's New with BI in SQL Server Denali (SQL11)What's New with BI in SQL Server Denali (SQL11)
What's New with BI in SQL Server Denali (SQL11)Dan English
 
Leveraging PowerPivot
Leveraging PowerPivotLeveraging PowerPivot
Leveraging PowerPivotDan English
 
Leveraging Microsoft BI Toolset to Monitor Performance
Leveraging Microsoft BI Toolset to Monitor PerformanceLeveraging Microsoft BI Toolset to Monitor Performance
Leveraging Microsoft BI Toolset to Monitor PerformanceDan English
 
SSAS Design & Incremental Processing - PASSMN May 2010
SSAS Design & Incremental Processing - PASSMN May 2010SSAS Design & Incremental Processing - PASSMN May 2010
SSAS Design & Incremental Processing - PASSMN May 2010Dan English
 
Leveraging MS BI Toolset to Monitor Performance - TechFuse 2010
Leveraging MS BI Toolset to Monitor Performance - TechFuse 2010Leveraging MS BI Toolset to Monitor Performance - TechFuse 2010
Leveraging MS BI Toolset to Monitor Performance - TechFuse 2010Dan English
 
PASSMN Summit 2009 Upgrade to SSAS 2008
PASSMN Summit 2009 Upgrade to SSAS 2008PASSMN Summit 2009 Upgrade to SSAS 2008
PASSMN Summit 2009 Upgrade to SSAS 2008Dan English
 
SQL Server Integration Services – Enterprise Manageability
SQL Server Integration Services – Enterprise ManageabilitySQL Server Integration Services – Enterprise Manageability
SQL Server Integration Services – Enterprise ManageabilityDan English
 
Driving BI with SQL Server 2008
Driving BI with SQL Server 2008Driving BI with SQL Server 2008
Driving BI with SQL Server 2008Dan English
 
SQL Server 2008 New Features
SQL Server 2008 New FeaturesSQL Server 2008 New Features
SQL Server 2008 New FeaturesDan English
 

More from Dan English (16)

Power BI / AAS Data Model Optimization 101 v2
Power BI / AAS Data Model Optimization 101 v2Power BI / AAS Data Model Optimization 101 v2
Power BI / AAS Data Model Optimization 101 v2
 
Power BI / AAS Model Optimization
Power BI / AAS Model OptimizationPower BI / AAS Model Optimization
Power BI / AAS Model Optimization
 
Power BI: Dashboard in an Hour Walk-Through
Power BI: Dashboard in an Hour Walk-ThroughPower BI: Dashboard in an Hour Walk-Through
Power BI: Dashboard in an Hour Walk-Through
 
Getting the new year started with Microsoft Power BI!
Getting the new year started with Microsoft Power BI!Getting the new year started with Microsoft Power BI!
Getting the new year started with Microsoft Power BI!
 
Self-Service BI with SQL Server 2012
Self-Service BI with SQL Server 2012Self-Service BI with SQL Server 2012
Self-Service BI with SQL Server 2012
 
Inside PerformancePoint
Inside PerformancePointInside PerformancePoint
Inside PerformancePoint
 
Intro to BI Semantic Model & Self-Service Reporting with Power View
Intro to BI Semantic Model & Self-Service Reporting with Power ViewIntro to BI Semantic Model & Self-Service Reporting with Power View
Intro to BI Semantic Model & Self-Service Reporting with Power View
 
What's New with BI in SQL Server Denali (SQL11)
What's New with BI in SQL Server Denali (SQL11)What's New with BI in SQL Server Denali (SQL11)
What's New with BI in SQL Server Denali (SQL11)
 
Leveraging PowerPivot
Leveraging PowerPivotLeveraging PowerPivot
Leveraging PowerPivot
 
Leveraging Microsoft BI Toolset to Monitor Performance
Leveraging Microsoft BI Toolset to Monitor PerformanceLeveraging Microsoft BI Toolset to Monitor Performance
Leveraging Microsoft BI Toolset to Monitor Performance
 
SSAS Design & Incremental Processing - PASSMN May 2010
SSAS Design & Incremental Processing - PASSMN May 2010SSAS Design & Incremental Processing - PASSMN May 2010
SSAS Design & Incremental Processing - PASSMN May 2010
 
Leveraging MS BI Toolset to Monitor Performance - TechFuse 2010
Leveraging MS BI Toolset to Monitor Performance - TechFuse 2010Leveraging MS BI Toolset to Monitor Performance - TechFuse 2010
Leveraging MS BI Toolset to Monitor Performance - TechFuse 2010
 
PASSMN Summit 2009 Upgrade to SSAS 2008
PASSMN Summit 2009 Upgrade to SSAS 2008PASSMN Summit 2009 Upgrade to SSAS 2008
PASSMN Summit 2009 Upgrade to SSAS 2008
 
SQL Server Integration Services – Enterprise Manageability
SQL Server Integration Services – Enterprise ManageabilitySQL Server Integration Services – Enterprise Manageability
SQL Server Integration Services – Enterprise Manageability
 
Driving BI with SQL Server 2008
Driving BI with SQL Server 2008Driving BI with SQL Server 2008
Driving BI with SQL Server 2008
 
SQL Server 2008 New Features
SQL Server 2008 New FeaturesSQL Server 2008 New Features
SQL Server 2008 New Features
 

Recently uploaded

[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?XfilesPro
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...HostedbyConfluent
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersThousandEyes
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 

Recently uploaded (20)

[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping Elbows
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 

Make Better Decisions With Your Data 20080916

  • 1. Make Better Decisions with Your Data Dan English Aaron Lowe Alan Wernke Principal Consultant Senior Consultant Practice Director, Enterprise Data Services dane@magenic.com aaronl@magenic.com
  • 2. Who are we? – Dan and Aaron Aaron Lowe Alan Wernke Dan English http://vendoran.spaces.live.com/ http://denglishbi.spaces.live.com • Practice Director, Enterprise Data Services • 10+ years experience in SQL • Developing with Microsoft • 18+ years experience with data Server development, technologies for over 10 years services administration and design • Over 5 years experience with • 10 years at Microsoft • Experience in advanced Data Warehousing and Business • 30 years in Information administration, which includes Intelligence Technology performance optimization, • Experienced in ETL and backup and recovery, migration Analysis Services development, strategies and replication, as requirements gathering and data well as security and auditing modeling techniques. • Microsoft Certified IT • Microsoft Certified IT Professional (MCITP) and Professional (MCITP) and Microsoft Certified Technology Microsoft Certified Technology Specialist (MCTS) Specialist (MCTS) • Masters degree in Information Systems Management
  • 3. Who are we? – Magenic  Founded in 1995, Magenic is a technical consulting firm focused exclusively on Microsoft technologies and has designed and delivered more than 500 Microsoft-based applications  Headquartered in Minneapolis, with offices in Chicago, Boston, Atlanta and San Francisco  2005 Microsoft Partner of the Year, Custom Development Solutions – Technical Innovation  2007 Microsoft Partner of the Year Finalist, Data Management  Microsoft Gold Certified Partner and National Systems Integrator  40 Enterprise Data Services (EDS) consultants
  • 4. Today‟s Agenda • What is Business Intelligence (BI)? • What are Spreadmarts and Data Marts? • What is a Business Intelligence Platform? • Where do I go from here? • Questions?
  • 5. What is Business Intelligence (BI)? The Gartner Group coined the term Business Intelligence in the mid-1990s and defined it as follows: “An interactive process for exploring and analyzing structured and domain-specific information to discern trends or patterns, thereby deriving insights and drawing conclusions. The business intelligence process includes communicating findings and effecting change.” (Source: A glossary on the web site www.gartner.com)
  • 6. BI Maturity Model – where are you at? STRUCTURE: Mgmt Reports Spreadsheets Data Marts Data Warehouses Enterprise DW BI Services System Individual Department Division Enterprise Inter-Enterprise SCOPE: By Wayne Eckerson, Director of Research, TDWI
  • 7. Spreadmart BI – Infant (2nd) Stage Are the users What happens when Did they extract all How long does it extracting and the person responsible of the necessary take to extract reporting on the for the report goes on data to allow the data and how right data? vacation or is sick or management to ask clean is it once it leaves the company? further questions? is extracted? MS Access MS Excel MS PowerPoint Business Users Do they have enough What logic is Source Data data collected to being applied and perform yearly Is all of the data is this common comparisons or available in the logic within the trends over time? source system? organization?
  • 8. Datamart BI – Child (3rd) Stage OLAP Engine Datamart Source Data Business Users
  • 9. Spreadmart vs. Datamart BI Spreadmart Datamart • High end-user control • Shared/consistent view of data • Easy to generate • Centralized logic • Can be pieced Pros • Highly interactive (slice-and- together Pros dice) • Highly customizable for • Secured the intended audience • Very Flexible • Low cost solution • Extremely Fast response time • Inconsistent view of the data • • No centralized logic Takes time to generate Cons • • Typically no security applied Less end-user control Cons • • Silos of data throughout Costs more to develop organization • Could potentially introduce new tools (training)
  • 10. Spreadmart to Datamart Case Study Spreadmart • Excel file report system • Lots of embedded business logic and conditional formatting • Generated over 1500+ files (most contained multiple reports) with macro • Process took approximately 30 hours to run • Initial Excel file was created and tested over a 6 month time period • If there were any data issues or report creation errors process had to be re-run • Not easy to implement additional change requests Datamart • Star schema database engine designed • Analysis Service database created with centralized logic • Reporting Service reports created and data driven subscription setup • Generated same reports in approximately 30 minutes • Entire database along with reports was created and tested in 2 month time frame • Database and reporting structure extremely flexible to change requests
  • 11. To BI or Not to BI? Reasons to BI • Integrate data from multiple source systems • Create centralized „single version‟ of the truth • Centralized business logic and calculations • Gain insight into unknown and disparate areas of the organization • Maintain competitive edge • Provide additional services to customers Reasons to Not BI • Do not have the time and resources • Do not have any competition • Not interested in evaluating your organization
  • 12. BI Platform – what is it? “Gartner defines BI platforms as those that enable users to build applications that help organizations learn and understand their business. It divides these capabilities into the functions of integration, information delivery, and analysis.” InformationWeek, Microsoft Gets Gartner's Business Intelligence Top Ranking, Mary Hayes Weier, February 5, 2008
  • 13. Magic Quadrant for BI Platforms, 2008 Microsoft strengths: • Pricing • Tight integration with MS Office • PerformancePoint Server • SQL Server • Extremely large Microsoft Developer community • Attractive to those already on Microsoft platform Source: Gartner (January 2008) Gartner RAS Core Research Note G00154227
  • 14. Microsoft BI Tool Offerings DELIVERY SharePoint Server Analytic Excel Scorecards Plans Reports Dashboards Views Workbooks END USER TOOLS & PERFORMANCE MANAGEMENT APPS Excel PerformancePointServer BI PLATFORM SQL Server SQL Server Reporting Services Analysis Services SQL Server DBMS SQL Server Integration Services
  • 15. SharePoint Business Intelligence • Excel Services • Dashboards • Key Performance Indicators (KPI‟s) • Filter Web Parts • Report Center/Report Library (Integrate Reporting Services)
  • 16. PerformancePoint Offering Performance Management Cycle
  • 19. Source Information Business Intelligence Definition – http://www.perceptualedge.com/blog/?p=31 BI Maturity Model – http://www.dmreview.com/issues/20041101/1012391-1.html or http://www.tdwi.org/publications/display.aspx?ID=7199 BI Platform Definition – http://www.informationweek.com/news/windows/microsoft_news/showArticle.jhtml?articleID= 206104502 Magic Quadrant – http://mediaproducts.gartner.com/reprints/microsoft/vol7/article3/article3.html
  • 20. Resources Microsoft BI Site http://www.microsoft.com/bi/ SharePoint BI Features Introduction http://office.microsoft.com/en-us/sharepointserver/HA100872181033.aspx PerformancePoint Home Site http://www.microsoft.com/business/performancepoint/default.aspx PerformancePoint Developer Portal http://msdn.microsoft.com/en-us/office/bb660518.aspx Channel9 MSDN BI Screencasts http://channel9.msdn.com/Showforum.aspx?forumid=38&tagid=277 SQL Server 2008 Home Site http://www.microsoft.com/sqlserver/2008/en/us/default.aspx Microsoft Virtual Labs (TechNet and MSDN) http://www.microsoft.com/events/vlabs/default.mspx Magenic Blogs http://blog.magenic.com/blogs
  • 21. How Do We Get Started?  Complimentary Strategy Session  Up to 4 hours  Deliverable:  Customized BI Recommendations  Business Intelligence Benefit Assessment  5 days  Deliverables  Initial proof-of-concept development custom to your company‟s unique reporting needs  High level BI architecture  Mentoring & Knowledge Transfer  Email info@magenic.com for more information
  • 22. Contact Information – Thank You! Contact us to find out how your business can benefit from a complimentary strategy session with one of our consultants and look into one of our BI quickstart engagements. Dan - http://denglishbi.spaces.live.com Aaron - http://vendoran.spaces.live.com Magenic - info@magenic.com