3. THE PROCESS OF ANALYZING DATA
IS INEFFICIENT AND CAN BE FUNDAMENTALLY
OVERHAULED
4. ACCENTURE: SERVING THE NON-STOP CUSTOMER
Source: Accenture, October 2012
ACCENTURE’S NON-STOP CUSTOMER EXPERIENCE MODEL
REDEFINES CUSTOMER INTERACTION
• Digital technologies are
driving this change
• Customers no longer enter
a channel but are
continuously in the channel
• Transactional, dynamic, ex
perimental
• UNPREDICTABLE
Analytics are Getting More Complex
5. • The 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 it’s not storing
contextual, transactional data.
DATA
TOOLS (ETL)
FINANCE
MARKETING
Mobile
App Database
E-Commerce
App Database
Call Center
App Database
Retail Branch
App Database
DATA
WAREHOUSE
DATA &
MODELING
TOOLS
DATA
WAREHOUSE
OPS
TODAY’S ANALYTICS PROCESS (TXNs & CONTEXT -
AFTER)
ENTERPRISE
APPLICATION
DATA
ENHANCED
DATA SETS
6. The Marketing team wants to analyze data that
flows through the applications, but is not stored
anywhere.
3
Marketing wants to analyze data that is already
captured by the application, but is not stored in
the data warehouse.
2
Marketing wants to analyze data that is not
being stored in the enhanced data set, but is
being stored in the data warehouse.
1
DATA
TOOLS (ETL)
FINANCE
MARKETING
Mobile
App Database
E-Commerce
App Database
Call Center
App Database
Retail Branch
App Database
DATA
WAREHOUSE
DATA &
MODELING
TOOLS
OPS
TODAY’S ANALYTICS PROCESS (TXNs & CONTEXT -
AFTER)
ENTERPRISE
APPLICATION
DATA
ENHANCED
DATA SETS
7. WHY IS THE TRADITIONAL ANALYTICS PROCESS
FLAWED?
THESE PROJECTS COST SO MUCH TIME &
MONEY
WE OFTEN JUST GIVE UP
Problem Time To Fix
Data not in enhanced data set 5 Days
Data not in data warehouse 1 – 3 Months
Data not in application database 3 – 12 Months3
2
1
8. THIS PROCESS IS RIPE
FOR A FUNDAMENTAL OVERHAUL
BECAUSE OF THE WAY APPLICATIONS
STORE DATA
+ ≠
9. REAL-TIME TRANSACTIONAL ANALYTICS - WITH
OPTIER
ENTERPRISE
APPLICATION
DATA
DATA
TOOLS (ETL)
Mobile
App Database
E-Commerce
App Database
Call Center
App Database
Retail Branch
App Database
DATA
WAREHOUSE
DATA &
MODELING
TOOLS
ENHANCED
DATA SETS
FINANCE
MARKETING
OPS
10. User Transaction
Web Server Authentication
Application Server
Message Bus, ESB
Middleware Server
Data Base
Mainframe
The end-user initiates a transaction, such as checking
their bank balance.
User Transaction
Each transaction is uniquely tagged so useful
transactional data can be collected as it flows
through your architecture.
Web Server Authentication
Application Server
Message Bus, ESB
Middleware Server
Data Base
Data is collected at each step of the transaction. This
granular approach enables us to pinpoint and resolve
problems quickly and predict potential problems.
Mainframe
Active Context
Tracking
Each piece of data is put into context to deliver useful
real-time analytics. This unique and powerful concept
is at the heart of OpTier’s technology.
3rd Party Web Services3rd Party Web Services
Data is collected at each step of the transaction.
OpTier
Real-time business
transactional dataset
OPTIER’S PATENTED TECHNOLOGY COLLECTS
DATA WHILE TRANSACTIONS RUN, WITHOUT
CHANGING APPLICATIONS
CASSANDRA
DATABASE
WE DO THIS MILLIONS OF TIMES A DAY FOR THE WORLD’S BIGGEST COMPANIES
11. Marketing wants to analyze data
not saved by applications.
3
Marketing wants to analyze data that applications
process but not saved in Cassandra.
2
REAL-TIME TRANSACTIONAL ANALYTICS - WITH
OPTIER
ENTERPRISE
APPLICATION
DATA
Mobile
App Database
E-Commerce
App Database
Call Center
App Database
Retail Branch
App Database
DATA
WAREHOUSE
DATA
TOOLS (ETL)
CASSANDRA
DATABASE
Marketing wants to analyze data that’s not
being stored in the enhanced data set but is in
the data warehouse.
1
CASSANDRA
DATABASE
ENHANCED
DATA SETS
FINANCE
MARKETING
OPS
DATA &
MODELING
TOOLS
OpTier
1. 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 drop
tool that empowers Business Analysts to Actively
engage in analytics and visualization – without
time-consuming & expensive IT Projects.
12. CREATES MASSIVE VALUE
Problem Time To Fix
Data not in enhanced data set 5 Days
Data not in data warehouse 1 – 3 Months
Data not in application database 3 – 12 Months3
2
1 ____
1 Hour
______
1 - 2 Days
_______
1 - 2 Days
REAL-TIME TRANSACTIONAL ANALYTICS - WITH
OPTIER
13. 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.
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.