optier presentation for open analytics
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OANYC SummitTRANSCRIPT
PowerPoint Presentation
TRUTH. SIMPLICITY. SCALE.1YOU MUST FUNDAMENTALLYCHANGE THE PROCESSTO ACHIEVE MASSIVE RESULTS
+INCREMENTAL IMPROVEMENTONLY WORKS SO FAR2THE PROCESS OF ANALYZING DATAIS INEFFICIENT AND CAN BE FUNDAMENTALLY OVERHAULEDACCENTURE: SERVING THE NON-STOP CUSTOMERSource: Accenture, October 2012ACCENTURES NON-STOP CUSTOMER EXPERIENCE MODEL REDEFINES CUSTOMER INTERACTIONDigital technologies are driving this changeCustomers no longer enter a channel but are continuously in the channelTransactional, dynamic, experimentalUNPREDICTABLE
Analytics are Getting More ComplexThe traditional demand funnel - that describes a linear and generally predictable customer path to buying - has lost its relevance. Its 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.
4The data is first translated using a tool like Informatica and then stored in a Data Warehouse.
The contextual relationship is NOT defined, and the transactions are NOT established.
Financial reporting is stable & predictable.Does not require access to real time data.This process works well.
Sophisticated data and modeling tools are used to create models, infer context and create enhanced data sets.
The Data Warehouse stores massive amounts of different data but its not storing contextual, transactional data.
DATATOOLS (ETL)
FINANCE
MARKETING
MobileApp Database
E-CommerceApp Database
Call CenterApp Database
Retail BranchApp DatabaseDATAWAREHOUSE
DATA &MODELINGTOOLS
DATAWAREHOUSE
OPS
TODAYS ANALYTICS PROCESS (TXNs & CONTEXT - AFTER)ENTERPRISEAPPLICATIONDATAENHANCEDDATA SETSData 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?5The Marketing team wants to analyze data that flows through the applications, but is not stored anywhere. 3Marketing wants to analyze data that is already captured by the application, but is not stored in the data warehouse.
2Marketing wants to analyze data that is not being stored in the enhanced data set, but is being stored in the data warehouse. 1
DATATOOLS (ETL)
FINANCE
MARKETING
MobileApp Database
E-CommerceApp Database
Call CenterApp Database
Retail BranchApp DatabaseDATAWAREHOUSE
DATA &MODELINGTOOLS
OPS
TODAYS ANALYTICS PROCESS (TXNs & CONTEXT - AFTER)ENTERPRISEAPPLICATIONDATAENHANCEDDATA SETSData 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?6WHY IS THE TRADITIONAL ANALYTICS PROCESS FLAWED?THESE PROJECTS COST SO MUCH TIME & MONEY WE OFTEN JUST GIVE UPProblemTime To FixData not in enhanced data set5 DaysData not in data warehouse1 3 MonthsData not in application database3 12 Months3217THIS PROCESS IS RIPEFOR A FUNDAMENTAL OVERHAULBECAUSE OF THE WAY APPLICATIONS STORE DATA
+8REAL-TIME TRANSACTIONAL ANALYTICS - WITH OPTIERENTERPRISEAPPLICATIONDATA
DATATOOLS (ETL)
MobileApp Database
E-CommerceApp Database
Call CenterApp Database
Retail BranchApp DatabaseDATAWAREHOUSE
DATA &MODELINGTOOLS
ENHANCEDDATA SETS
FINANCE
MARKETING
OPSUser Transaction
Web ServerAuthenticationApplication ServerMessage Bus, ESBMiddleware ServerData BaseMainframe
The end-user initiates a transaction, such as checking their bank balance.User TransactionEach transaction is uniquely tagged so useful transactional data can be collected as it flows through your architecture.Web ServerAuthenticationApplication ServerMessage Bus, ESBMiddleware ServerData BaseData is collected at each step of the transaction. This granular approach enables us to pinpoint and resolve problems quickly and predict potential problems.MainframeActive Context TrackingEach piece of data is put into context to deliver useful real-time analytics. This unique and powerful concept is at the heart of OpTiers technology. 3rd Party Web Services3rd Party Web Services
Data is collected at each step of the transaction.OpTier Real-time business transactional dataset
OPTIERS PATENTED TECHNOLOGY COLLECTS DATA WHILE TRANSACTIONS RUN, WITHOUT CHANGING APPLICATIONSCASSANDRADATABASE
WE DO THIS MILLIONS OF TIMES A DAY FOR THE WORLDS BIGGEST COMPANIES10Marketing wants to analyze datanot saved by applications.3Marketing wants to analyze data that applications process but not saved in Cassandra.2REAL-TIME TRANSACTIONAL ANALYTICS - WITH OPTIERENTERPRISEAPPLICATIONDATA
MobileApp Database
E-CommerceApp Database
Call CenterApp Database
Retail BranchApp DatabaseDATAWAREHOUSE
The Data Warehouse stores massive amounts of different data but its not storing contextual, transactional data.Marketing wants to analyze data that is already captured by the application, but is not stored in the data warehouse.
Several IT teams are involved. Application modifications are required. The data model has to change. 2The Marketing team wants to analyze data that flows through the applications, but is not stored anywhere.
For example, the real-time transaction data that flows through the non stop customer model. 3
DATATOOLS (ETL)CASSANDRADATABASE
Marketing wants to analyze data thats not being stored in the enhanced data set but is in the data warehouse.1CASSANDRADATABASE
ENHANCEDDATA SETS
FINANCE
MARKETING
OPS
DATA &MODELINGTOOLS
OpTier
Capture Transactions & Create contextual data in near-real time using proven technology.Decrease the reliance on ETL tools.Leverage power & economics of Cassandra.OpTier has created a code-free drag and drop tool that empowers Business Analysts to Actively engage in analytics and visualization without time-consuming & expensive IT Projects. CREATES MASSIVE VALUEProblemTime To FixData not in enhanced data set5 DaysData not in data warehouse1 3 MonthsData not in application database3 12 Months321____1 Hour______1 - 2 Days_______1 - 2 DaysREAL-TIME TRANSACTIONAL ANALYTICS - WITH OPTIERThe traditional demand funnel - that describes a linear and generally predictable customer path to buying - has lost its relevance. Its 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.
12REAL-TIME TRANSACTIONAL ANALYTICS:WHY IS THIS IMPORTANT?
1Supports routine changes & net-new business requests quickly - without IT involvement.2Deliver complex analytics in days or weeks (not years). Reduces Big-Bang Project risk. 3Saves huge amounts of money. Easier to start now and get results sooner.TRUTH. SIMPLICITY. SCALE.14