SlideShare a Scribd company logo
1 of 23
Download to read offline
Ensuring Mobile BI Success



        August 18, 2011




 The only secure mobile BI solution
Webinar Notes


                 Attendees Muted
                    Upon Entry



                Please send questions
                   using the online
                       interface
Featured Speakers


      Stefan Schmitz
      Vice President of Products




      Wei-Chin Cheng
      Senior Consultant
Agenda

   • Trends in Mobile BI

   • Characteristics of Mobile BI

   • Mobile BI Best Practices

   • Security Considerations

   • Birst Mobile BI Demo
History of information delivery to mobile devices




                                                 Purpose-built
                                      Mobile     mobile BI apps
                                    client app

                      Data access
                      via browser

            Static
          data push
Mobile Wave – Fastest in IT History




“Over 80% of Fortune 100 companies have already begun deploying iPads in the
work place, or are in the process of ramping up their iPad support”

- Peter Oppenheimer, CFO Apple, January 2011
Shift in Usage Patterns Thanks to Tablets
Trends in Mobile BI

• Mobilization of business analytics is unstoppable
   – 9.25 million Apple iPads sold in the Q2 2011
   – Tablet sales estimated to reach 100 million by 2012
   – Gartner estimates that by 2013 a third of BI functionality
     will be consumed via mobile devices

• Mobile BI will drive wider adoption of BI
   – Only 8% of the people in most organizations are using
     mobile BI
   – Using mobile devices, BI becomes a more integral part of
     work processes away from the desk
   – Tablets like the iPad that are “always-on” and provide a
     gesture-based UI make BI more accessible and easier to
     consume
Drivers for Mobile BI Adoption




                                 Confidential   8/18/2011   9
User-Perceived Benefits of Mobile BI




         COPYRIGHT 2010 DRESNER ADVISORY SERVICES, LLC
User-Perceived Drawbacks of Mobile BI




         COPYRIGHT 2010 DRESNER ADVISORY SERVICES, LLC
Profile of Typical Mobile BI User

 • Not an information producer
    – Data analyst
    – Report Writer

 • Rather an information collaborator
    – Project lead, manager, specialist


 • Definitely an information consumer
    – Sales, marketing
    – Executives
    – IT
Mobile BI Best Practices
1. Avoid dashboard proliferation and rework
   ‒   Plan for author-once, distribute-everywhere dashboards

2. Design to a smaller form factor
   ‒   Most important chart/table at the top left
   ‒   Limit charts & tables to 4
   ‒   Avoid legends if possible
   ‒   Size fonts appropriately

3. Design for on-the-go usage
   ‒   Intuitive drill paths to more detail
   ‒   Limit to essential prompts
   ‒   Encourage collaboration

4. Focus on operational data
   ‒   Avoid data requiring deep analysis
   ‒   “here and now” metrics
Tablets vs. Smart Phones




   • Greater interactivity        • Alert driven
   • Perform drill down, filter   • Interaction based on
     data, data exploration         finding reports
   • Longer view times            • No data exploration
Browser-Based vs. Native BI App

 Capability               Browser-Based   Native App
 Performance

 Cross platform support

 Interactivity

 Offline Mode

 Geo Location

 Maintenance

 Security
Browser-Based vs. Native BI App
Mobile BI Security Considerations
1. Device Security
   – Utilize the handset/device security features
     to protect the data
   – Remote data management

2. Transmission Security
   – Cryptographic shared key systems
   – Secure socket layers

3. Authentication & Authorization
   – Control access rights to information
   – Provisions and policies
Solutions Provided by Mobile BI Vendors
• Solution 1 – Data & rendering on mobile device
   – Devices can be hacked
   – Mobile devices are not powerful enough
     for complex analytics

• Solution 2 – Data & rendering on server
   – Lacks interactivity, unfamiliar UI
   – Slow response times

• Solution 3 – Data on server, rendering on device
   – Use a VPN, which can be hacked
   – Or open up firewall and …
Are you prepared to open your firewall?




                              Firewall
                                                             Data
                      https




              • Do you have intrusion detection?
              • Do you have security monitoring?
              • Are you SAS 70 Type II certified?

 Birst is the only secure mobile BI solution providing SAS 70 Type II
About Birst
 Birst offers a comprehensive end-to-end BI suite with reporting, dash
 boarding, OLAP, ETL and data warehousing via SaaS
     –   Founded 2004 by former Siebel Analytics executives
     –   120+ Customers, 50,000+ users, 10+ TB under management
     –   Revenues tripled in 2010
     –   Top-tier VC funding by Sequoia Capital and Hummer Winblad

 Business Analytics for:
     –   Front Office: Executives, Sales, Marketing, Operations
     –   Back Office: Finance, Supply Chain, Human Resources




    “One of Ten IT Companies To Watch In 2011” – The Bloor Group
    “… customers chose Birst for 3 reasons; 1) ease of use, 2) implementation cost/efforts and 3) TCO” - Gartner

                                                                                    Confidential   8/18/2011   20
Logical and Physical Data Integration,
  Flexible End-user Access – In ONE Package
Existing Business Intelligence
End-user Tools                                                                                      Ad Hoc
                                                           Dashboards/
                                                                                                                                                 Mobile
                                                           Reporting                                Analysis


                                                                                           Multi-dimensional Analysis (OLAP)
                                                         Analytics
                                                         and
                                                         Logical Data                             Universal Semantic Layer
                                                         Integration
                                                                                Mongo Cache: Massive Scale Cloud-based Caching




                                                                                                                                                            MDX Realtime Query
                                                                                                                            SQL Realtime Query
 Datamart-in-a-Box
                                Extract          Transform           Load
                                                                                       Mart/Warehouse
 Physical Data                                         BEL
                                   Birst                               Birst
                                                 Transformation
                                 Connect                            Datamart
 Integration                                         Engine
                                                                     Engine*




                                                                                                                                                          Cube
                                                                                                                       Relational                     (e.g. MSAS,
                                                                                                                       Database                         SAP BW,
                                                                  Source 1
                                                              (DB, File, XML)
                                                                                 …           Source N
                                                                                            (DB, File, XML)
                                                                                                                      (MSSQL, Oracle,
                                                                                                                       DB2, Teradata,
                                                                                                                    Sybase, Vertica, ...)
                                                                                                                                                       Hyperion)

                                         SAP R/3
             Cloud Sources                                                                                                                           On Premise Data
   End-user (browser/device)               Cloud              On-premise (within the firewall)                Optional either On-premise or Cloud
               * Birst’s patent-pending datamart generation engine dynamically generates and manages a fully conformed star schema data warehouse EITHER in
               the cloud or in anon-premise relational database (i.e. no data need be resident in the cloud). Additions/modifications are automatically handled.
Demo of Birst Mobile BI
Learn More
• Test drive Birst today
   – Register at Birst.com, under
     Sign Up
• Join us for a live demo of
  Birst for additional detail
   – Every Tuesday at 10:00 am pt
   – Register at Birst.com
• Contact us
   – Email: info@birst.com
   – Phone: (866) 940-1496

More Related Content

What's hot

Agile BI : meeting the best of both worlds from departmental and enterprise BI
Agile BI : meeting the best of both worlds from departmental and enterprise BIAgile BI : meeting the best of both worlds from departmental and enterprise BI
Agile BI : meeting the best of both worlds from departmental and enterprise BIJean-Michel Franco
 
Building a business intelligence architecture fit for the 21st century by Jon...
Building a business intelligence architecture fit for the 21st century by Jon...Building a business intelligence architecture fit for the 21st century by Jon...
Building a business intelligence architecture fit for the 21st century by Jon...Mark Tapley
 
Mobile Business Intelligence Best Practices
Mobile Business Intelligence Best PracticesMobile Business Intelligence Best Practices
Mobile Business Intelligence Best PracticesYellowfin
 
Wall Street Technology
Wall Street TechnologyWall Street Technology
Wall Street TechnologyBharat Gera
 
Investigative Analytics- What's in a Data Scientists Toolbox
Investigative Analytics- What's in a Data Scientists ToolboxInvestigative Analytics- What's in a Data Scientists Toolbox
Investigative Analytics- What's in a Data Scientists ToolboxData Science London
 
ScaleBase Webinar: Methods and Challenges to Scale Out a MySQL Database
ScaleBase Webinar: Methods and Challenges to Scale Out a MySQL DatabaseScaleBase Webinar: Methods and Challenges to Scale Out a MySQL Database
ScaleBase Webinar: Methods and Challenges to Scale Out a MySQL DatabaseScaleBase
 
Demystifying the Path to a JBoss Intelligent, Integrated Enterprise
Demystifying the Path to a JBoss Intelligent, Integrated EnterpriseDemystifying the Path to a JBoss Intelligent, Integrated Enterprise
Demystifying the Path to a JBoss Intelligent, Integrated EnterpriseEric D. Schabell
 
Expert Webinar Series: SharePoint Governance - Managing Content Sprawl
Expert Webinar Series:  SharePoint Governance - Managing Content SprawlExpert Webinar Series:  SharePoint Governance - Managing Content Sprawl
Expert Webinar Series: SharePoint Governance - Managing Content Sprawlmartingarland
 
BW Multi-Dimensional Model
BW Multi-Dimensional ModelBW Multi-Dimensional Model
BW Multi-Dimensional Modelyujesh
 
An Enterprise Perspective on Cloud Innovation
An Enterprise Perspective on Cloud InnovationAn Enterprise Perspective on Cloud Innovation
An Enterprise Perspective on Cloud InnovationOpen Data Center Alliance
 
Database Architecture Proposal
Database Architecture ProposalDatabase Architecture Proposal
Database Architecture ProposalDATANYWARE.com
 
Introduccion a SQL Server Master Data Services
Introduccion a SQL Server Master Data ServicesIntroduccion a SQL Server Master Data Services
Introduccion a SQL Server Master Data ServicesEduardo Castro
 
Make Your Business More Flexible with Scalable Business Process Management So...
Make Your Business More Flexible with Scalable Business Process Management So...Make Your Business More Flexible with Scalable Business Process Management So...
Make Your Business More Flexible with Scalable Business Process Management So...Perficient, Inc.
 
Ibm cognos mobile now with android support
Ibm cognos mobile now with android supportIbm cognos mobile now with android support
Ibm cognos mobile now with android supportFriedel Jonker
 
Identity Insights: Social, Local and Mobile Identity
Identity Insights: Social, Local and Mobile IdentityIdentity Insights: Social, Local and Mobile Identity
Identity Insights: Social, Local and Mobile IdentityJon Bultmeyer
 
Sap sap so h 2013
Sap sap so h 2013Sap sap so h 2013
Sap sap so h 2013deepersnet
 
sones company presentation
sones company presentationsones company presentation
sones company presentationsones GmbH
 

What's hot (20)

Agile BI : meeting the best of both worlds from departmental and enterprise BI
Agile BI : meeting the best of both worlds from departmental and enterprise BIAgile BI : meeting the best of both worlds from departmental and enterprise BI
Agile BI : meeting the best of both worlds from departmental and enterprise BI
 
Building a business intelligence architecture fit for the 21st century by Jon...
Building a business intelligence architecture fit for the 21st century by Jon...Building a business intelligence architecture fit for the 21st century by Jon...
Building a business intelligence architecture fit for the 21st century by Jon...
 
Mobile Business Intelligence Best Practices
Mobile Business Intelligence Best PracticesMobile Business Intelligence Best Practices
Mobile Business Intelligence Best Practices
 
Wall Street Technology
Wall Street TechnologyWall Street Technology
Wall Street Technology
 
Investigative Analytics- What's in a Data Scientists Toolbox
Investigative Analytics- What's in a Data Scientists ToolboxInvestigative Analytics- What's in a Data Scientists Toolbox
Investigative Analytics- What's in a Data Scientists Toolbox
 
ScaleBase Webinar: Methods and Challenges to Scale Out a MySQL Database
ScaleBase Webinar: Methods and Challenges to Scale Out a MySQL DatabaseScaleBase Webinar: Methods and Challenges to Scale Out a MySQL Database
ScaleBase Webinar: Methods and Challenges to Scale Out a MySQL Database
 
NextInside Data exchanger
NextInside Data exchangerNextInside Data exchanger
NextInside Data exchanger
 
Why Mashups Matter
Why Mashups MatterWhy Mashups Matter
Why Mashups Matter
 
Demystifying the Path to a JBoss Intelligent, Integrated Enterprise
Demystifying the Path to a JBoss Intelligent, Integrated EnterpriseDemystifying the Path to a JBoss Intelligent, Integrated Enterprise
Demystifying the Path to a JBoss Intelligent, Integrated Enterprise
 
Expert Webinar Series: SharePoint Governance - Managing Content Sprawl
Expert Webinar Series:  SharePoint Governance - Managing Content SprawlExpert Webinar Series:  SharePoint Governance - Managing Content Sprawl
Expert Webinar Series: SharePoint Governance - Managing Content Sprawl
 
BW Multi-Dimensional Model
BW Multi-Dimensional ModelBW Multi-Dimensional Model
BW Multi-Dimensional Model
 
An Enterprise Perspective on Cloud Innovation
An Enterprise Perspective on Cloud InnovationAn Enterprise Perspective on Cloud Innovation
An Enterprise Perspective on Cloud Innovation
 
Database Architecture Proposal
Database Architecture ProposalDatabase Architecture Proposal
Database Architecture Proposal
 
Introduccion a SQL Server Master Data Services
Introduccion a SQL Server Master Data ServicesIntroduccion a SQL Server Master Data Services
Introduccion a SQL Server Master Data Services
 
Ihee Ppres0998
Ihee Ppres0998Ihee Ppres0998
Ihee Ppres0998
 
Make Your Business More Flexible with Scalable Business Process Management So...
Make Your Business More Flexible with Scalable Business Process Management So...Make Your Business More Flexible with Scalable Business Process Management So...
Make Your Business More Flexible with Scalable Business Process Management So...
 
Ibm cognos mobile now with android support
Ibm cognos mobile now with android supportIbm cognos mobile now with android support
Ibm cognos mobile now with android support
 
Identity Insights: Social, Local and Mobile Identity
Identity Insights: Social, Local and Mobile IdentityIdentity Insights: Social, Local and Mobile Identity
Identity Insights: Social, Local and Mobile Identity
 
Sap sap so h 2013
Sap sap so h 2013Sap sap so h 2013
Sap sap so h 2013
 
sones company presentation
sones company presentationsones company presentation
sones company presentation
 

Similar to Ensuring Mobile BI Success

Martin Wildberger Presentation
Martin Wildberger PresentationMartin Wildberger Presentation
Martin Wildberger PresentationMauricio Godoy
 
SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)
SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)
SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)Will Gardella
 
제1회 Korea Community Day 발표자료 Bigdata
제1회 Korea Community Day 발표자료 Bigdata 제1회 Korea Community Day 발표자료 Bigdata
제1회 Korea Community Day 발표자료 Bigdata Gruter
 
Big Data Beyond Hadoop*: Research Directions for the Future
Big Data Beyond Hadoop*: Research Directions for the FutureBig Data Beyond Hadoop*: Research Directions for the Future
Big Data Beyond Hadoop*: Research Directions for the FutureOdinot Stanislas
 
Business Intelligence
Business Intelligence Business Intelligence
Business Intelligence arunvanlvanoor
 
Magic quadrant for data warehouse database management systems
Magic quadrant for data warehouse database management systems Magic quadrant for data warehouse database management systems
Magic quadrant for data warehouse database management systems divjeev
 
Protect Your Big Data with Intel<sup>®</sup> Xeon<sup>®</sup> Processors a..
Protect Your Big Data with Intel<sup>®</sup> Xeon<sup>®</sup> Processors a..Protect Your Big Data with Intel<sup>®</sup> Xeon<sup>®</sup> Processors a..
Protect Your Big Data with Intel<sup>®</sup> Xeon<sup>®</sup> Processors a..Odinot Stanislas
 
BI Forum 2010 - High Performance BI: The Future of BI
BI Forum 2010 - High Performance BI: The Future of BIBI Forum 2010 - High Performance BI: The Future of BI
BI Forum 2010 - High Performance BI: The Future of BIOKsystem
 
Big Data and Implications on Platform Architecture
Big Data and Implications on Platform ArchitectureBig Data and Implications on Platform Architecture
Big Data and Implications on Platform ArchitectureOdinot Stanislas
 
What is BI on Cloud
What is BI on CloudWhat is BI on Cloud
What is BI on Cloudtdwiindia
 
Innovations in Data Grid Technology with Oracle Coherence
Innovations in Data Grid Technology with Oracle CoherenceInnovations in Data Grid Technology with Oracle Coherence
Innovations in Data Grid Technology with Oracle CoherenceBob Rhubart
 
Dev mobile apps ent it final
Dev mobile apps ent   it finalDev mobile apps ent   it final
Dev mobile apps ent it finalHeinrich Seeger
 
Case Study: Synchroniztion Issues in Mobile Databases
Case Study: Synchroniztion Issues in Mobile DatabasesCase Study: Synchroniztion Issues in Mobile Databases
Case Study: Synchroniztion Issues in Mobile DatabasesG. Habib Uddin Khan
 
Case Study: Synchroniztion Issues in Mobile Databases
Case Study: Synchroniztion Issues in Mobile DatabasesCase Study: Synchroniztion Issues in Mobile Databases
Case Study: Synchroniztion Issues in Mobile DatabasesG. Habib Uddin Khan
 
Clextra tablet applications
Clextra tablet applicationsClextra tablet applications
Clextra tablet applicationsEdgevalue
 
10052012 luc vervenne synergetics van syntax portfolio naar semantische uitwi...
10052012 luc vervenne synergetics van syntax portfolio naar semantische uitwi...10052012 luc vervenne synergetics van syntax portfolio naar semantische uitwi...
10052012 luc vervenne synergetics van syntax portfolio naar semantische uitwi...Stichting ePortfolio Support
 
Scaling MySQL: Catch 22 of Read Write Splitting
Scaling MySQL: Catch 22 of Read Write SplittingScaling MySQL: Catch 22 of Read Write Splitting
Scaling MySQL: Catch 22 of Read Write SplittingScaleBase
 

Similar to Ensuring Mobile BI Success (20)

Martin Wildberger Presentation
Martin Wildberger PresentationMartin Wildberger Presentation
Martin Wildberger Presentation
 
SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)
SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)
SAP HANA and Apache Hadoop for Big Data Management (SF Scalable Systems Meetup)
 
제1회 Korea Community Day 발표자료 Bigdata
제1회 Korea Community Day 발표자료 Bigdata 제1회 Korea Community Day 발표자료 Bigdata
제1회 Korea Community Day 발표자료 Bigdata
 
Big Data Beyond Hadoop*: Research Directions for the Future
Big Data Beyond Hadoop*: Research Directions for the FutureBig Data Beyond Hadoop*: Research Directions for the Future
Big Data Beyond Hadoop*: Research Directions for the Future
 
Business Intelligence
Business Intelligence Business Intelligence
Business Intelligence
 
Secure Big Data Analytics - Hadoop & Intel
Secure Big Data Analytics - Hadoop & IntelSecure Big Data Analytics - Hadoop & Intel
Secure Big Data Analytics - Hadoop & Intel
 
SAP EIM
SAP EIM SAP EIM
SAP EIM
 
Magic quadrant for data warehouse database management systems
Magic quadrant for data warehouse database management systems Magic quadrant for data warehouse database management systems
Magic quadrant for data warehouse database management systems
 
Protect Your Big Data with Intel<sup>®</sup> Xeon<sup>®</sup> Processors a..
Protect Your Big Data with Intel<sup>®</sup> Xeon<sup>®</sup> Processors a..Protect Your Big Data with Intel<sup>®</sup> Xeon<sup>®</sup> Processors a..
Protect Your Big Data with Intel<sup>®</sup> Xeon<sup>®</sup> Processors a..
 
BI Forum 2010 - High Performance BI: The Future of BI
BI Forum 2010 - High Performance BI: The Future of BIBI Forum 2010 - High Performance BI: The Future of BI
BI Forum 2010 - High Performance BI: The Future of BI
 
Big Data and Implications on Platform Architecture
Big Data and Implications on Platform ArchitectureBig Data and Implications on Platform Architecture
Big Data and Implications on Platform Architecture
 
What is BI on Cloud
What is BI on CloudWhat is BI on Cloud
What is BI on Cloud
 
Innovations in Data Grid Technology with Oracle Coherence
Innovations in Data Grid Technology with Oracle CoherenceInnovations in Data Grid Technology with Oracle Coherence
Innovations in Data Grid Technology with Oracle Coherence
 
Dev mobile apps ent it final
Dev mobile apps ent   it finalDev mobile apps ent   it final
Dev mobile apps ent it final
 
Slideshare ga
Slideshare gaSlideshare ga
Slideshare ga
 
Case Study: Synchroniztion Issues in Mobile Databases
Case Study: Synchroniztion Issues in Mobile DatabasesCase Study: Synchroniztion Issues in Mobile Databases
Case Study: Synchroniztion Issues in Mobile Databases
 
Case Study: Synchroniztion Issues in Mobile Databases
Case Study: Synchroniztion Issues in Mobile DatabasesCase Study: Synchroniztion Issues in Mobile Databases
Case Study: Synchroniztion Issues in Mobile Databases
 
Clextra tablet applications
Clextra tablet applicationsClextra tablet applications
Clextra tablet applications
 
10052012 luc vervenne synergetics van syntax portfolio naar semantische uitwi...
10052012 luc vervenne synergetics van syntax portfolio naar semantische uitwi...10052012 luc vervenne synergetics van syntax portfolio naar semantische uitwi...
10052012 luc vervenne synergetics van syntax portfolio naar semantische uitwi...
 
Scaling MySQL: Catch 22 of Read Write Splitting
Scaling MySQL: Catch 22 of Read Write SplittingScaling MySQL: Catch 22 of Read Write Splitting
Scaling MySQL: Catch 22 of Read Write Splitting
 

More from Birst

Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Da...
Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Da...Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Da...
Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Da...Birst
 
The Truth About Cross-Channel Attribution... and Why it Does Not Have to be ...
The Truth About Cross-Channel Attribution...  and Why it Does Not Have to be ...The Truth About Cross-Channel Attribution...  and Why it Does Not Have to be ...
The Truth About Cross-Channel Attribution... and Why it Does Not Have to be ...Birst
 
The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...
The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...
The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...Birst
 
Birst 5X: Turn Information Consumers into Information Producers – Connected o...
Birst 5X: Turn Information Consumers into Information Producers – Connected o...Birst 5X: Turn Information Consumers into Information Producers – Connected o...
Birst 5X: Turn Information Consumers into Information Producers – Connected o...Birst
 
The five essential steps to building a data product
The five essential steps to building a data productThe five essential steps to building a data product
The five essential steps to building a data productBirst
 
Sales analytics webinar
Sales analytics webinarSales analytics webinar
Sales analytics webinarBirst
 
Embedded Analytics for the ISV: Supercharging Applications with BI
Embedded Analytics for the ISV: Supercharging Applications with BIEmbedded Analytics for the ISV: Supercharging Applications with BI
Embedded Analytics for the ISV: Supercharging Applications with BIBirst
 
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
 
How Best-in-Class Sales Leaders Create Better Forecasts and Increase Revenue
How Best-in-Class Sales Leaders Create Better Forecasts and Increase RevenueHow Best-in-Class Sales Leaders Create Better Forecasts and Increase Revenue
How Best-in-Class Sales Leaders Create Better Forecasts and Increase RevenueBirst
 
The Analytic Trifecta: Abstraction, the Cloud, and Visualization
The Analytic Trifecta: Abstraction, the Cloud, and VisualizationThe Analytic Trifecta: Abstraction, the Cloud, and Visualization
The Analytic Trifecta: Abstraction, the Cloud, and VisualizationBirst
 
Birst for SAP HANA
Birst for SAP HANABirst for SAP HANA
Birst for SAP HANABirst
 
Boost Your Analytics Acumen: Learn Where BI is Headed from the Wisdom of the ...
Boost Your Analytics Acumen: Learn Where BI is Headed from the Wisdom of the ...Boost Your Analytics Acumen: Learn Where BI is Headed from the Wisdom of the ...
Boost Your Analytics Acumen: Learn Where BI is Headed from the Wisdom of the ...Birst
 
Webinar: Get Embedded Marketing Analytics in your CRM
Webinar: Get Embedded Marketing Analytics in your CRMWebinar: Get Embedded Marketing Analytics in your CRM
Webinar: Get Embedded Marketing Analytics in your CRMBirst
 
Data Discovery vs BI Webinar
Data Discovery vs BI WebinarData Discovery vs BI Webinar
Data Discovery vs BI WebinarBirst
 
Why SaaS BI
Why SaaS BIWhy SaaS BI
Why SaaS BIBirst
 

More from Birst (15)

Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Da...
Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Da...Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Da...
Birst Webinar Slides: "Build vs. Buy - Making the Right Choice for a Great Da...
 
The Truth About Cross-Channel Attribution... and Why it Does Not Have to be ...
The Truth About Cross-Channel Attribution...  and Why it Does Not Have to be ...The Truth About Cross-Channel Attribution...  and Why it Does Not Have to be ...
The Truth About Cross-Channel Attribution... and Why it Does Not Have to be ...
 
The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...
The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...
The Art and Science of Sales Forecasting: A Webinar for Sales Managers and Co...
 
Birst 5X: Turn Information Consumers into Information Producers – Connected o...
Birst 5X: Turn Information Consumers into Information Producers – Connected o...Birst 5X: Turn Information Consumers into Information Producers – Connected o...
Birst 5X: Turn Information Consumers into Information Producers – Connected o...
 
The five essential steps to building a data product
The five essential steps to building a data productThe five essential steps to building a data product
The five essential steps to building a data product
 
Sales analytics webinar
Sales analytics webinarSales analytics webinar
Sales analytics webinar
 
Embedded Analytics for the ISV: Supercharging Applications with BI
Embedded Analytics for the ISV: Supercharging Applications with BIEmbedded Analytics for the ISV: Supercharging Applications with BI
Embedded Analytics for the ISV: Supercharging Applications with BI
 
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...
 
How Best-in-Class Sales Leaders Create Better Forecasts and Increase Revenue
How Best-in-Class Sales Leaders Create Better Forecasts and Increase RevenueHow Best-in-Class Sales Leaders Create Better Forecasts and Increase Revenue
How Best-in-Class Sales Leaders Create Better Forecasts and Increase Revenue
 
The Analytic Trifecta: Abstraction, the Cloud, and Visualization
The Analytic Trifecta: Abstraction, the Cloud, and VisualizationThe Analytic Trifecta: Abstraction, the Cloud, and Visualization
The Analytic Trifecta: Abstraction, the Cloud, and Visualization
 
Birst for SAP HANA
Birst for SAP HANABirst for SAP HANA
Birst for SAP HANA
 
Boost Your Analytics Acumen: Learn Where BI is Headed from the Wisdom of the ...
Boost Your Analytics Acumen: Learn Where BI is Headed from the Wisdom of the ...Boost Your Analytics Acumen: Learn Where BI is Headed from the Wisdom of the ...
Boost Your Analytics Acumen: Learn Where BI is Headed from the Wisdom of the ...
 
Webinar: Get Embedded Marketing Analytics in your CRM
Webinar: Get Embedded Marketing Analytics in your CRMWebinar: Get Embedded Marketing Analytics in your CRM
Webinar: Get Embedded Marketing Analytics in your CRM
 
Data Discovery vs BI Webinar
Data Discovery vs BI WebinarData Discovery vs BI Webinar
Data Discovery vs BI Webinar
 
Why SaaS BI
Why SaaS BIWhy SaaS BI
Why SaaS BI
 

Recently uploaded

AI in Action: Real World Use Cases by Anitaraj
AI in Action: Real World Use Cases by AnitarajAI in Action: Real World Use Cases by Anitaraj
AI in Action: Real World Use Cases by AnitarajAnitaRaj43
 
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)Samir Dash
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesrafiqahmad00786416
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Zilliz
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...apidays
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
JohnPollard-hybrid-app-RailsConf2024.pptx
JohnPollard-hybrid-app-RailsConf2024.pptxJohnPollard-hybrid-app-RailsConf2024.pptx
JohnPollard-hybrid-app-RailsConf2024.pptxJohnPollard37
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistandanishmna97
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century educationjfdjdjcjdnsjd
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdfSandro Moreira
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Jeffrey Haguewood
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusZilliz
 
Introduction to use of FHIR Documents in ABDM
Introduction to use of FHIR Documents in ABDMIntroduction to use of FHIR Documents in ABDM
Introduction to use of FHIR Documents in ABDMKumar Satyam
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Victor Rentea
 
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelMcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelDeepika Singh
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native ApplicationsWSO2
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 

Recently uploaded (20)

AI in Action: Real World Use Cases by Anitaraj
AI in Action: Real World Use Cases by AnitarajAI in Action: Real World Use Cases by Anitaraj
AI in Action: Real World Use Cases by Anitaraj
 
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
JohnPollard-hybrid-app-RailsConf2024.pptx
JohnPollard-hybrid-app-RailsConf2024.pptxJohnPollard-hybrid-app-RailsConf2024.pptx
JohnPollard-hybrid-app-RailsConf2024.pptx
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Introduction to use of FHIR Documents in ABDM
Introduction to use of FHIR Documents in ABDMIntroduction to use of FHIR Documents in ABDM
Introduction to use of FHIR Documents in ABDM
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelMcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 

Ensuring Mobile BI Success

  • 1. Ensuring Mobile BI Success August 18, 2011 The only secure mobile BI solution
  • 2. Webinar Notes Attendees Muted Upon Entry Please send questions using the online interface
  • 3. Featured Speakers Stefan Schmitz Vice President of Products Wei-Chin Cheng Senior Consultant
  • 4. Agenda • Trends in Mobile BI • Characteristics of Mobile BI • Mobile BI Best Practices • Security Considerations • Birst Mobile BI Demo
  • 5. History of information delivery to mobile devices Purpose-built Mobile mobile BI apps client app Data access via browser Static data push
  • 6. Mobile Wave – Fastest in IT History “Over 80% of Fortune 100 companies have already begun deploying iPads in the work place, or are in the process of ramping up their iPad support” - Peter Oppenheimer, CFO Apple, January 2011
  • 7. Shift in Usage Patterns Thanks to Tablets
  • 8. Trends in Mobile BI • Mobilization of business analytics is unstoppable – 9.25 million Apple iPads sold in the Q2 2011 – Tablet sales estimated to reach 100 million by 2012 – Gartner estimates that by 2013 a third of BI functionality will be consumed via mobile devices • Mobile BI will drive wider adoption of BI – Only 8% of the people in most organizations are using mobile BI – Using mobile devices, BI becomes a more integral part of work processes away from the desk – Tablets like the iPad that are “always-on” and provide a gesture-based UI make BI more accessible and easier to consume
  • 9. Drivers for Mobile BI Adoption Confidential 8/18/2011 9
  • 10. User-Perceived Benefits of Mobile BI COPYRIGHT 2010 DRESNER ADVISORY SERVICES, LLC
  • 11. User-Perceived Drawbacks of Mobile BI COPYRIGHT 2010 DRESNER ADVISORY SERVICES, LLC
  • 12. Profile of Typical Mobile BI User • Not an information producer – Data analyst – Report Writer • Rather an information collaborator – Project lead, manager, specialist • Definitely an information consumer – Sales, marketing – Executives – IT
  • 13. Mobile BI Best Practices 1. Avoid dashboard proliferation and rework ‒ Plan for author-once, distribute-everywhere dashboards 2. Design to a smaller form factor ‒ Most important chart/table at the top left ‒ Limit charts & tables to 4 ‒ Avoid legends if possible ‒ Size fonts appropriately 3. Design for on-the-go usage ‒ Intuitive drill paths to more detail ‒ Limit to essential prompts ‒ Encourage collaboration 4. Focus on operational data ‒ Avoid data requiring deep analysis ‒ “here and now” metrics
  • 14. Tablets vs. Smart Phones • Greater interactivity • Alert driven • Perform drill down, filter • Interaction based on data, data exploration finding reports • Longer view times • No data exploration
  • 15. Browser-Based vs. Native BI App Capability Browser-Based Native App Performance Cross platform support Interactivity Offline Mode Geo Location Maintenance Security
  • 17. Mobile BI Security Considerations 1. Device Security – Utilize the handset/device security features to protect the data – Remote data management 2. Transmission Security – Cryptographic shared key systems – Secure socket layers 3. Authentication & Authorization – Control access rights to information – Provisions and policies
  • 18. Solutions Provided by Mobile BI Vendors • Solution 1 – Data & rendering on mobile device – Devices can be hacked – Mobile devices are not powerful enough for complex analytics • Solution 2 – Data & rendering on server – Lacks interactivity, unfamiliar UI – Slow response times • Solution 3 – Data on server, rendering on device – Use a VPN, which can be hacked – Or open up firewall and …
  • 19. Are you prepared to open your firewall? Firewall Data https • Do you have intrusion detection? • Do you have security monitoring? • Are you SAS 70 Type II certified? Birst is the only secure mobile BI solution providing SAS 70 Type II
  • 20. About Birst Birst offers a comprehensive end-to-end BI suite with reporting, dash boarding, OLAP, ETL and data warehousing via SaaS – Founded 2004 by former Siebel Analytics executives – 120+ Customers, 50,000+ users, 10+ TB under management – Revenues tripled in 2010 – Top-tier VC funding by Sequoia Capital and Hummer Winblad Business Analytics for: – Front Office: Executives, Sales, Marketing, Operations – Back Office: Finance, Supply Chain, Human Resources “One of Ten IT Companies To Watch In 2011” – The Bloor Group “… customers chose Birst for 3 reasons; 1) ease of use, 2) implementation cost/efforts and 3) TCO” - Gartner Confidential 8/18/2011 20
  • 21. Logical and Physical Data Integration, Flexible End-user Access – In ONE Package Existing Business Intelligence End-user Tools Ad Hoc Dashboards/ Mobile Reporting Analysis Multi-dimensional Analysis (OLAP) Analytics and Logical Data Universal Semantic Layer Integration Mongo Cache: Massive Scale Cloud-based Caching MDX Realtime Query SQL Realtime Query Datamart-in-a-Box Extract Transform Load Mart/Warehouse Physical Data BEL Birst Birst Transformation Connect Datamart Integration Engine Engine* Cube Relational (e.g. MSAS, Database SAP BW, Source 1 (DB, File, XML) … Source N (DB, File, XML) (MSSQL, Oracle, DB2, Teradata, Sybase, Vertica, ...) Hyperion) SAP R/3 Cloud Sources On Premise Data End-user (browser/device) Cloud On-premise (within the firewall) Optional either On-premise or Cloud * Birst’s patent-pending datamart generation engine dynamically generates and manages a fully conformed star schema data warehouse EITHER in the cloud or in anon-premise relational database (i.e. no data need be resident in the cloud). Additions/modifications are automatically handled.
  • 22. Demo of Birst Mobile BI
  • 23. Learn More • Test drive Birst today – Register at Birst.com, under Sign Up • Join us for a live demo of Birst for additional detail – Every Tuesday at 10:00 am pt – Register at Birst.com • Contact us – Email: info@birst.com – Phone: (866) 940-1496