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Time to Fly - Why Predictive Analytics is Going Mainstream


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The Briefing Room with Robin Bloor and Perceivant
Live Webcast on Nov. 20, 2012

When companies predict the future effectively, they almost always win. But barriers abound for corporate departments and mid-sized organizations that have limited capital, IT staff, or both. They often lack the resources to employ powerful predictive analytics, and instead can only rely on basic reporting capabilities. That situation is now changing, thanks to several market forces, such as software innovation, maturing methodologies, as well as competition from open-source offerings.

Check out this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor, who will explain why predictive analytics is finally going mainstream, and what that means for companies looking to grow. He will be briefed by Brian Rowe of Perceivant, who will tout his company’s SaaS-based analytics platform, which was designed to streamline the workflow required to get significant lift from predictive algorithms. He'll also discuss the packaged services designed to help business users get up and running with the key procedures for building and managing predictive models.

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Time to Fly - Why Predictive Analytics is Going Mainstream

  1. 1. The Briefing Room
  2. 2. Welcome Host: Eric Kavanagh eric.kavanagh@bloorgroup.comTwitter Tag: #briefr The Briefing Room
  3. 3. Mission !   Reveal the essential characteristics of enterprise software, good and bad !   Provide a forum for detailed analysis of today s innovative technologies !   Give vendors a chance to explain their product to savvy analysts !   Allow audience members to pose serious questions... and get answers!Twitter Tag: #briefr The Briefing Room
  4. 4. November: Cloud December: Innovators January: Big Data February: AnalyticsTwitter Tag: #briefr The Briefing Room
  5. 5. Cloud !   Cloud computing has come a long way and can now offer an array of hosted services: software (SaaS), platform (PaaS), infrastructure (IaaS), as well as other services and resources (storage, security, API desktop, etc.). !   Cloud services can be deployed as public, private, or as a hybrid according to needs. !   Using the Cloud means companies can invest less in hardware resources, which can close the gap between large and mid-sized organizations.Twitter Tag: #briefr The Briefing Room
  6. 6. Analyst: Robin Bloor  Robin Bloor is Chief Analyst at The Bloor Group robin.bloor@bloorgroup.comTwitter Tag: #briefr The Briefing Room
  7. 7. Perceivant ! Perceivant offers a SaaS-based Big Data analytics platform. !   The Platform delivers real-time access to disparate data sources and allows customers to leverage high performance analytics on terabytes of data. ! Perceivant designed its platform for scalability and ease of use, requiring no servers, software licenses or consultants. ! Perceivant lets customers begin with a low-risk, short term license which can be extended after adoption.Twitter Tag: #briefr The Briefing Room
  8. 8. Brian Rowe Brian Rowe is CEO at Perceivant. He has been an entrepreneur for the last 10 years and started developing Internet based applications in 1990. He has been Project Manager for various programs with annual budgets between $10m-$20m. As Director of e- Business at Cummins Engine Company, Brian started six online businesses and won CIO Magazines 50 Best Intranets Award during his tenure. Brian had P&L responsibility at to develop a Distributed Storefront online retail offering. He was the COO and co-founder of Redtrain, a Software Service consultancy. Brian was also a founder of Last Piece Software where he acted as President until the company was acquired by iGoDigital. With a background that bridges both business and technology, he enjoys the fast paced and dynamic startup environment, where these skills can be used effectively. He has a B.S. in Financial Planning and an MBA from Purdue University.Twitter Tag: #briefr The Briefing Room
  9. 9. Decisions Driven by Insight
  10. 10. Background● Founded in 2012 based on experience working with data at iGoDigital● Leveraging nearly a decade of big data and analysis experience acquired while scaling the recommendations business at iGoDigital for some of the biggest names in online retail● Some of the issues iGoDigital had to solve became desirable to offer as a stand alone tools
  11. 11. How we got here● We had 5 TB of data to analyze● Receiving data in all different formats from many sources● Data had to be prepared for analysis - Joined, flattened, cleansed● Machine learning algorithms had to run● Additional needs to manually analyze and report on data● Cash constrained as a startup
  12. 12. Searching for a solution● So many vendors, so little time● Lots of vendors had partial solutions● Total cost to own and operate the solutions were far outside our budget 250K/year and up.● So we started building.... ○ Our goal was the fastest path to ROI ○ Hadoop, Hive, ElasticSearch, MongoDB....● Started to find out that other people had our same challenges
  13. 13. A lot of work to do● Data Preparation - Clean & Flatten● Visualize & Analyze● Make a hypothesis, What to predict● Analysis● Implement result● Back Test● Integrate into business process● Operate it with scaling compute resources● Measure it
  14. 14. Big Data issues for businesses● McKinsey expects that 60% of big data projects will face a gap in talent by 2018● People with experience in Hadoop, Hive, Pig, ElasticSearch, NoSQL, MongoDB, R, SAS, etc.● Data preparation time typically takes 40-50% of an analytics project (ETL/Cleaning)● TDWI study says data prep is taking longer in 2011 than it was in 2009● Internal data growing 40% annually (IDC estimate), social data explosion
  15. 15. Breakthrough Insights● Target predicts fairly well if a shopper is pregnant based on buying habits and markets to her upcoming purchasing needs● Combining credit scores with channel data to better price loans increasing channel profitability● Insights like these can have a big impact on your business and profitability● You have already made sizeable investments in your data, get value from it!
  16. 16. How Perceivant Can Help● Launch within 30 days● Achieve 50% savings compared to purchase package solutions● BI Suite of tools - Reporting, OLAP, charting● Data manipulation - ETL, Cleansing● Partner with you on predictive engagements● Access data anywhere you have the internet● No need to worry about scaling● Easy to integrate back into your existing systems and process
  17. 17. Overview
  18. 18. Predictive Analytics● Predictive Analytics is not "one size fits all"● These are services engagements● We help determine the right combination of human expertise and machine learning tools● We deliver and implement the predictive formula● We measure the on-going results● This approach identifies hidden patterns in your data that will not be found with traditional approaches
  19. 19. Case Study● Educational institution spending about 500K/year on current BI tools and infrastructure, not including people● Limited capabilities, slow, no predictive capabilities● RFP produced projects starting at $1M from well known vendors● Our solution loaded data in 2 weeks ○ BI tools out of the box satisfied many reporting needs ○ Real-time query capabilities previously not possible ○ Conversion of remaining existing reports ○ Creation of new reports including predictive reports ○ Creation of history from ongoing point in time data ○ Reduced cost by 50% from the current solution
  20. 20. Invest in ROI, not R&D● The fastest path to ROI on the market today ○ Less than 30 days on-boarding process ○ Monthly starting at $2,000 ○ Leverage sizeable investments already made in your data
  21. 21. Perceptions & Questions Analyst: Robin BloorTwitter Tag: #briefr The Briefing Room
  22. 22. A NEWUNIVERSEOF BI? The Bloor Group
  23. 23. Open Source, The Cloud and BI (1) •  Open Source and The Cloud walk hand in hand •  Together they undermine the traditional DBMS business model in some areas •  Hadoop and Hadoop++ can happily be deployed in the cloud •  Hadoop has become the staging place for data and an ETL engine •  The cloud is a natural prototyping environment - a low risk and possibly permanent location for BI apps The Bloor Group
  24. 24. Open Source, The Cloud and BI (2)•  The public cloud is growing at >100% p.a.•  The private cloud is a gateway drug to the public cloud – and vice versa•  The cloud devalues many software brands (you can only brand applications now)•  Open source is beginning to dominate BI cloud deployments by virtue of cost•  For BI users, the Cloud + Open Source is –  Good enough or better –  A leap-frog opportunity The Bloor Group
  25. 25. BI CategoriesHindsight: Regular reporting/operational BI Oversight: Dashboards, OLAP, BPM, etc.Insight: Data mining, statistical analysis (trends and relationships)Foresight: Predictive analytics The Bloor Group
  26. 26. The New BI Universe (?) The Bloor Group
  27. 27. !  Roughly how much of the software that Perceivant deploys is home-grown in terms of distinct components, i.e., what do you add to the solution?!  Which other data stores/DBMSs do you use, aside from Hadoop? Any favorites?!  Is there any aspect of BI that you don’t or wont cater for (CEP, data governance, MDM, etc.)?!  What kind of predictive capabilities do you provide? Are these standard or bespoke? The Bloor Group
  28. 28. !  Aside from the customer base is there any aspect of your software stack that could not be implemented at higher scale (e.g., for large companies)?!  How do you define requirements?!  How many of your customers take the data scientist consultancy?!  Roughly how many of your customers eventually choose to specialize the solution? The Bloor Group
  29. 29. Twitter Tag: #briefr The Briefing Room
  30. 30. Upcoming Topics This month: Cloud December: Innovators January: Big Data 2013 Editorial Calendar www.insideanalysis.comTwitter Tag: #briefr The Briefing Room
  31. 31. Thank You for Your AttentionImage credits: Tag: #briefr The Briefing Room