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Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
Transaction Based Big Data Analytics
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Transaction Based Big Data Analytics

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Today's data analytics is fundamentally flawed. OpTier's transaction-based approach to data analytics is changing everything.

Today's data analytics is fundamentally flawed. OpTier's transaction-based approach to data analytics is changing everything.

Published in: Business, Technology
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  • The traditional demand funnel - that describes a linear and generally predictable customer path to buying - has lost its relevance. It’s too slow, too static and too generic to be used as the foundation for marketing, sales and service strategies.Now, while buyers still go through the same stages of awareness, consideration, evaluation, purchase and use, they no longer enter a channel but, instead, are continuously in the channel.Nonstop customers today are frequently re-evaluating their decisions, and the alternatives.
  • Data stored in the application data bases lack the context and uniformity to enable analytics to quickly make use of it.Data is the bricks and context is the cement that holds the data together. Context is defined as the relationship between different data elements that answers who, what, where, when and why?
  • The traditional demand funnel - that describes a linear and generally predictable customer path to buying - has lost its relevance. It’s too slow, too static and too generic to be used as the foundation for marketing, sales and service strategies.Now, while buyers still go through the same stages of awareness, consideration, evaluation, purchase and use, they no longer enter a channel but, instead, are continuously in the channel.Nonstop customers today are frequently re-evaluating their decisions, and the alternatives.
  • The traditional demand funnel - that describes a linear and generally predictable customer path to buying - has lost its relevance. It’s too slow, too static and too generic to be used as the foundation for marketing, sales and service strategies.Now, while buyers still go through the same stages of awareness, consideration, evaluation, purchase and use, they no longer enter a channel but, instead, are continuously in the channel.Nonstop customers today are frequently re-evaluating their decisions, and the alternatives.
  • Transcript

    • 1. TRANSACTION-BASED DATA ANALYTICS
    • 2. YOU MUST FUNDAMENTALLYCHANGE THE DATA ANALYTICS PROCESSTO ACHIEVE UNPRECEDENTED RESULTSTHE PROCESS OF ANALYZING DATAIS INEFFICIENT AND CAN BE FUNDAMENTALLY OVERHAULED
    • 3. ACCENTURE: SERVING THE NON-STOP CUSTOMERSource: Accenture, October 2012ACCENTURE’S NON-STOP CUSTOMER EXPERIENCE MODEL REDEFINESCUSTOMER INTERACTION• Digital technologies are driving thischange• Customers no longer enter a channelbut are continuously in the channel• Transactional, dynamic, experimental• UNPREDICTABLEAnalytics is Getting Increasingly More Complex
    • 4. TODAY’S ANALYTICS PROCESS (PRE OPTIER)ENTERPRISEAPPLICATIONDATADATATOOLS (ETL)ENHANCEDDATA SETSFINANCEMARKETINGMobileApp DatabaseE-CommerceApp DatabaseCall CenterApp DatabaseRetail BranchApp DatabaseDATAWAREHOUSEMODELING& BI STEPOPSExpensive, time-consuming, inefficient
    • 5. WHY IS THIS TRADITIONAL ANALYTICS PROCESS FLAWED?IT COSTS SO MUCH TIME & MONEYWE OFTEN JUST GIVE UPProblem Time To FixData not in enhanced data set 5 DaysData not in data warehouse 1 – 3 MonthsData not in application database 3 – 12 Months321
    • 6. THE DATA ANALYTICS PROCESS IS RIPEFOR A FUNDAMENTAL OVERHAULBECAUSE OF THE WAY APPLICATIONS STORE DATA
    • 7. TOMORROW’S ANALYTICS PROCESS (WITH OPTIER)ENTERPRISEAPPLICATIONDATAMobileApp DatabaseE-CommerceApp DatabaseCall CenterApp DatabaseRetail BranchApp DatabaseCASSANDRADATABASEENHANCEDDATA SETSFINANCEMARKETINGOPSOpTierScalable, intuitive, responsive
    • 8. TOMORROW’S ANALYTICS PROCESS WITH OPTIERCREATES MASSIVE VALUEProblem Time To FixData not in enhanced data set 5 DaysData not in data warehouse 1 – 3 MonthsData not in application database 3 – 12 Months321 ____1 Hour______1 - 2 Days_______1 - 2 Days
    • 9. WHY IS THIS IMPORTANT?1 IT can supports routine changes in business requests quickly.2 Analytics that address complex issues like “non-stop” customercompleted in days or weeks not years.3 Saves huge amounts of money.
    • 10. OUT OF 128,000,000..THE ONLY COMPANYWITH THE SOLUTION THATCHANGES THE PROCESS

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