• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Optier presentation for open analytics event
 

Optier presentation for open analytics event

on

  • 3,636 views

 

Statistics

Views

Total Views
3,636
Views on SlideShare
595
Embed Views
3,041

Actions

Likes
0
Downloads
1
Comments
0

37 Embeds 3,041

http://todobi.blogspot.com.es 1193
http://todobi.blogspot.com 931
http://todobi.blogspot.com.ar 226
http://www.ikanow.com 224
http://todobi.blogspot.mx 152
http://cloud.feedly.com 79
http://www.todobi.blogspot.com 54
http://todobi.blogspot.com.br 38
http://todobi.blogspot.de 18
http://feeds.feedburner.com 17
http://todobi.blogspot.co.nz 16
http://192.254.196.224 15
http://todobi.blogspot.co.uk 9
http://todobi.blogspot.fr 8
http://newsblur.com 7
http://todobi.blogspot.in 6
http://www.todobi.blogspot.com.es 5
http://todobi.blogspot.ca 5
http://todobi.blogspot.jp 4
http://todobi.blogspot.pt 4
http://todobi.blogspot.be 4
http://todobi.blogspot.it 3
http://feedreader.com 3
http://www.directrss.co.il 2
http://todobi.blogspot.ie 2
http://webcache.googleusercontent.com 2
http://todobi.blogspot.co.at 2
http://todobi.blogspot.com.au 2
http://todobi.blogspot.dk 2
http://dev.newsblur.com 1
http://prlog.ru 1
http://todobi.blogspot.ch 1
http://131.253.14.66 1
http://translate.googleusercontent.com 1
http://todobi.blogspot.nl 1
http://todobi.blogspot.tw 1
http://www.google.com.au 1
More...

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • 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?
  • 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.

Optier presentation for open analytics event Optier presentation for open analytics event Presentation Transcript

  • TRUTH. SIMPLICITY. SCALE.
  • YOU MUST FUNDAMENTALLYCHANGE THE PROCESSTO ACHIEVE MASSIVE RESULTS+ ≠INCREMENTAL IMPROVEMENTONLY WORKS SO FAR…
  • THE PROCESS OF ANALYZING DATAIS INEFFICIENT AND CAN BE FUNDAMENTALLYOVERHAULED
  • ACCENTURE: SERVING THE NON-STOP CUSTOMERSource: Accenture, October 2012ACCENTURE’S NON-STOP CUSTOMER EXPERIENCE MODELREDEFINES CUSTOMER INTERACTION• Digital technologies aredriving this change• Customers no longer entera channel but arecontinuously in the channel• Transactional, dynamic, experimental• UNPREDICTABLEAnalytics are Getting More Complex
  • • The data is first translated using a tool likeInformatica and then stored in a Data Warehouse.• The contextual relationship is NOT defined, andthe transactions are NOT established.• Financial reporting is stable & predictable.• Does not require access to real time data.• This process works well.Sophisticated data and modelingtools are used to createmodels, infer context and createenhanced data sets.The Data Warehouse storesmassive amounts of differentdata – but it’s not storingcontextual, transactional data.DATATOOLS (ETL)FINANCEMARKETINGMobileApp DatabaseE-CommerceApp DatabaseCall CenterApp DatabaseRetail BranchApp DatabaseDATAWAREHOUSEDATA &MODELINGTOOLSDATAWAREHOUSEOPSTODAY’S ANALYTICS PROCESS (TXNs & CONTEXT -AFTER)ENTERPRISEAPPLICATIONDATAENHANCEDDATA SETS
  • The Marketing team wants to analyze data thatflows through the applications, but is not storedanywhere.3Marketing wants to analyze data that is alreadycaptured by the application, but is not stored inthe data warehouse.2Marketing wants to analyze data that is notbeing stored in the enhanced data set, but isbeing stored in the data warehouse.1DATATOOLS (ETL)FINANCEMARKETINGMobileApp DatabaseE-CommerceApp DatabaseCall CenterApp DatabaseRetail BranchApp DatabaseDATAWAREHOUSEDATA &MODELINGTOOLSOPSTODAY’S ANALYTICS PROCESS (TXNs & CONTEXT -AFTER)ENTERPRISEAPPLICATIONDATAENHANCEDDATA SETS
  • WHY IS THE TRADITIONAL ANALYTICS PROCESSFLAWED?THESE PROJECTS COST 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
  • THIS PROCESS IS RIPEFOR A FUNDAMENTAL OVERHAULBECAUSE OF THE WAY APPLICATIONSSTORE DATA+ ≠
  • REAL-TIME TRANSACTIONAL ANALYTICS - WITHOPTIERENTERPRISEAPPLICATIONDATADATATOOLS (ETL)MobileApp DatabaseE-CommerceApp DatabaseCall CenterApp DatabaseRetail BranchApp DatabaseDATAWAREHOUSEDATA &MODELINGTOOLSENHANCEDDATA SETSFINANCEMARKETINGOPS
  • User TransactionWeb Server AuthenticationApplication ServerMessage Bus, ESBMiddleware ServerData BaseMainframeThe end-user initiates a transaction, such as checkingtheir bank balance.User TransactionEach transaction is uniquely tagged so usefultransactional data can be collected as it flowsthrough your architecture.Web Server AuthenticationApplication ServerMessage Bus, ESBMiddleware ServerData BaseData is collected at each step of the transaction. Thisgranular approach enables us to pinpoint and resolveproblems quickly and predict potential problems.MainframeActive ContextTrackingEach piece of data is put into context to deliver usefulreal-time analytics. This unique and powerful conceptis at the heart of OpTier’s technology.3rd Party Web Services3rd Party Web ServicesData is collected at each step of the transaction.OpTierReal-time businesstransactional datasetOPTIER’S PATENTED TECHNOLOGY COLLECTSDATA WHILE TRANSACTIONS RUN, WITHOUTCHANGING APPLICATIONSCASSANDRADATABASEWE DO THIS MILLIONS OF TIMES A DAY FOR THE WORLD’S BIGGEST COMPANIES
  • Marketing wants to analyze datanot saved by applications.3Marketing wants to analyze data that applicationsprocess but not saved in Cassandra.2REAL-TIME TRANSACTIONAL ANALYTICS - WITHOPTIERENTERPRISEAPPLICATIONDATAMobileApp DatabaseE-CommerceApp DatabaseCall CenterApp DatabaseRetail BranchApp DatabaseDATAWAREHOUSEDATATOOLS (ETL)CASSANDRADATABASEMarketing wants to analyze data that’s notbeing stored in the enhanced data set but is inthe data warehouse.1CASSANDRADATABASEENHANCEDDATA SETSFINANCEMARKETINGOPSDATA &MODELINGTOOLSOpTier1. Capture Transactions & Create contextual data in near-real time using proven technology.2. Decrease the reliance on ETL tools.3. Leverage power & economics of Cassandra.OpTier has created a code-free drag and droptool that empowers Business Analysts to Activelyengage in analytics and visualization – withouttime-consuming & expensive IT Projects.
  • CREATES 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 DaysREAL-TIME TRANSACTIONAL ANALYTICS - WITHOPTIER
  • REAL-TIME TRANSACTIONAL ANALYTICS:WHY IS THIS IMPORTANT?1 Supports routine changes & net-new business requests quickly - without IT involvement.2 Deliver complex analytics – in days or weeks (not years). Reduces “Big-Bang” Project risk.3 Saves huge amounts of money. Easier to start now and get results sooner.
  • TRUTH. SIMPLICITY. SCALE.