Presented by: Rik Tamm-­‐Daniels, VP Technology, Attivio TIBCO Spotfire and Teradata: First to Insight, First to Action; Warehousing, Analytics and Visualizations for the High Tech Industry Conference July 22, 2013 The Four Seasons Hotel Palo Alto, CA

2. The
Unsung
Hero
of
Big
Data
in
Manufacturing:
Unstructured
Content
Rik
Tamm-­‐Daniels,
VP
Technology
TwiBer:
@riktammdaniels

3. Proprietary
Big
Data
Big
Data
encompasses
geEng
insight
and
making
smarter
decisions
from
any
informaFon
that
is
not
easily
tapped
using
tradiFonal
BI
and
AnalyFcs
technology
stacks.
Source:
'Big
Data'
Is
Only
the
Beginning
of
Extreme
Informa7on
Management,
April
7,
2011,
Gartner
Group

4. Proprietary
Big
Data
Structured
Data
Unstructured
Data
Unstructured
Data
Unstructured
Content
Beyond
Structured
vs.
Unstructured
<xyz>
</xyz>
1-­‐2-­‐2013
abc/bed/fnd
87
998
1-­‐2-­‐2013
abc/bed/fnd
87
998
1-­‐2-­‐2013
abc/bed/fnd
87
998
1-­‐2-­‐2013
abc/bed/fnd
87
998
57°
64°
71°
120°
Understanding
the
nature
of
data
and
how
to
get
insight
from
it
is
fundamental
to
succeeding
with
Big
Data

5. Proprietary
Unstructured
Data
• Brings
the
promise
of
inferring
customer
intent,
idenFfying
paBerns
of
behavior
and
predicFng
future
acFons
• But
gaining
this
insight
requires
large
amounts
of
raw
data,
much
of
which
is
noise,
to
get
what
amounts
to
indirect
insight
1000
rows
of
impression
logs
to
get
1
click-­‐thru;
6
months
of
click
data
to
be
able
to
develop
staFsFcally
meaningful
user
segments

6. Proprietary
Unstructured
Content
• Consider
this
CRM
case:
Customer:
Joe
Customer
jcust@acmemail.com
Product:
Mobile
Phone
X1000
Summary:
BaBery
is
dying
aber
only
1
hour
of
use
Date:
3-­‐1-­‐2013
01:35:00
Comments:
I
just
bought
the
new
X1000
because
I
saw
it
had
fantasFc
reviews
online,
but
aber
only
one
week,
the
baBery
dies
aber
just
an
hour
of
use.
This
is
completely
unacceptable
and
I’ve
been
unable
to
get
help
from
ACME
mobile
where
I
bought
the
phone.
They
keep
telling
me
that
depending
on
the
apps
I’m
running,
this
might
be
expected.
I’m
only
running
the
basic
pre-­‐installed
apps!
Also,
I’ve
noFced
that
the
screen
is
always
super
bright
and
starts
to
hurt
my
eyes
aber
20
minutes
of
use.
I
would
really
appreciate
it
if
you
could
send
me
a
new
phone
or
tell
me
how
to
fix
mine.

7. Proprietary
What
does
this
single
CRM
case
tell
us?
Customer:
Joe
Customer
jcust@acmemail.com
Product:
Mobile
Phone
X1000
Summary:
BaBery
is
dying
aber
only
1
hour
of
use
Date:
3-­‐1-­‐2013
01:35:00
Comments:
I
just
bought
the
new
X1000
because
I
saw
it
had
fantasFc
reviews
online,
but
aber
only
one
week
of
use,
the
baBery
dies
aber
just
an
hour.
This
is
completely
unacceptable
and
I’ve
been
unable
to
get
help
from
ACME
mobile
where
I
bought
the
phone.
They
keep
telling
me
that
depending
on
the
apps
I’m
running,
this
might
be
expected.
I’m
only
running
the
basic
pre-­‐installed
apps!
This
is
completely
unacceptable
from
a
retailer
selling
your
products.
Also,
I’ve
noFced
that
the
screen
is
always
super
bright
and
starts
to
hurt
my
eyes
aber
20
minutes
of
use.
I
would
really
appreciate
it
if
you
could
send
me
a
new
phone
or
tell
me
how
to
fix
mine.
Customer
email
Customer
name
PosiFve
SenFment
NegaFve
SenFment
Retail
Outlet
PotenFal
Liability
Key
concept
Industry
term

8. Proprietary
What’s
the
business
value
of
this
CRM
case?
• When
a
help
desk
user
gets
assigned
this
case,
their
view
could
be:
Customer:
Joe
Customer
Email
Address:
jcust@acmemail.com
Summary:
…
Case:
I
just
bought
the
new
X1000
because
I
saw
it
had
fantasFc
reviews
online,
but
aber
only
one
week
of
use,
the
baBery
dies
aber
just
an
hour
of
use.
This
is
completely
unacceptable
and
I’ve
been
unable
to
get
help
from
ACME
mobile
where
I
bought
the
phone.
They
keep
telling
me
that
depending
on
the
apps
I’m
running,
this
might
be
expected.
I’m
only
running
the
basic
pre-­‐installed
apps!
Also,
I’ve
noFced
that
the
screen
is
always
super
bright
and
starts
to
hurt
my
eyes
aber
20
minutes
of
use.
I
would
really
appreciate
it
if
you
could
send
me
a
new
phone
or
tell
me
how
to
fix
mine.
Related
CRM
cases:
Screen
and
baBery
issue
…
Screen
too
bright
….
Issue
trend
line
for
screen
and
baBery
issues
for
the
X1000

9. Proprietary
What
could
the
value
of
a
lot
of
CRM
cases
be?
LifeFme
Customer
Value
%
NegaFve
Customer
Service
InteracFons
ACME
Mobile
PhoneX
CoolPhones
Joe’s
Phones
BigBell
MallMobile
Percent
nega.ve
/
posi.ve
per
retailer
BaBery
dies
Apps
I’m
running
Screen
Super
Bright

10. Proprietary
Unstructured
Content
in
Customer
Experience
Management
Every
item
from
every
one
of
these
channels
is
your
customer
telling
you
directly
what
they
like,
what
they
don’t
like,
where
they
would
like
to
see
you
take
your
products,
etc…

11. Proprietary
Unstructured
Content
is
Everywhere!
CRM
case
notes
Email
Surveys
Warranty
claims
Product
manuals
Maintenance
reports
Online
reviews
Social
Media

12. Unlocking
Unstructured
Content

13. Proprietary
Unlocking
Unstructured
Content
• Fundamental:
Structure
the
Unstructured
• For
Unstructured
Content
this
is
done
through
Text
AnalyFcs:
– SenFment
Analysis
– ClassificaFon
– EnFty
ExtracFon
– Key
Concept
Analysis
– Taxonomies
and
Ontologies
New
Dimensions/New
Insights
Key
Concept
Analysis
EnFty
ExtracFon
SenFment
Analysis

14. Proprietary
Enterprise
Text
AnalyFcs
Spectrum
Taxonomies/
Ontologies
Gazeteer/
Dic.onary-­‐
Driven
En.ty
Extrac.on
Pa@ern
Based
En.ty
Extrac.on
Machine-­‐
Learning:
Sen.ment
&
Classifica.on
Sta.s.cal
En.ty
Extrac.on
Language
Model-­‐Based
Keyphrase
Analysis
Directed
Discovery

15. Proprietary
Enterprise
Text
AnalyFcs
in
PracFce
• IteraFon,
iteraFon,
iteraFon
–
the
faster
you
can
iterate,
the
greater
the
ROI
Text
Analy.cs
are
Itera.ve

16. Proprietary
Enterprise
Text
AnalyFcs
Best
PracFces
• Domain-­‐specific
analyFcs
• Extensible/flexible
frameworks
• Directed
and
Discovery
text
analyFcs
• Agile
data
environments
– Text
analyFc
data
can
produce
high-­‐degrees
of
cardinality
– Metadata
will
be
variable
by
“row”/“object”

17. The
Big
Picture

18. Proprietary
Big
Data
Maturity
Model
Level
0:
Current
State
Level
1:
Single
source
of
Big
Data
Analyzed
Level
2:
MulFple
types
of
Big
Data
sources
Analyzed
Level
3:
Unified
Big
Data
Architecture
Looking
at
a
single
source
of
Big
Data:
unstructured
data
or
unstructured
content
Looking
at
mulFple
sources
of
Big
Data:
unstructured
data
and
unstructured
content
Single
point
of
access
for
all
Big
Data
access
and
analysis
with
variety
of
access
modes
to
support
variety
of
business
cases
Structured
data
analysis:
EDW
+
BI
18

19. Proprietary
• Unified
informaFon
access
plauorms
provide
single
point
of
access
to
informaFon
from
mulFple
sources,
integraFng
and
finding
relaFonships
across
sources
– Efficiently
combines
features
of
database,
business
intelligence
and
search
technologies
in
a
single
architecture
in
real-­‐Fme
Unified
InformaFon
Access
Unified
Informa.on
Access
Note:
IDC
June
2012.
Unified
Informa.on
Access
&
Analysis
Content
Analy.cs
Databases
Search
and
Discovery
Decision
Management
Business
Intelligence
Data
Warehouses
Unified
Informa.on
Access
&
Analysis
• Serves
as
foundaFon
for
new
informaFon
management
and
access
stack
for
the
enterprise
• May
replace
data
warehouses
if
applicaFons
require
quick
ad
hoc
access
to
collecFons
of
heterogeneous
informaFon
• Will
eventually
replace
the
tradiFonal
enterprise
search
engine
Key
Disrup.ve
Elements

20. Customer
Experience
Management
for
Complex
Device
Manufacturers

21. Proprietary
Case
Study
Global
Manufacturer
• Create new BI platform to proactively manage customer engine
fleets at new level of breadth and depth of detail beyond just
data trends
• Greatly improve efficiency, customer satisfaction and repeat
business
• Analyze Everything platform for complete agile BI: integrates,
correlates and presents data and content, with no advance data
modeling required:
• Engine sensor data, generated in “Big Data” volumes
• Service status data, quality metrics, CRM and other databases
• Customer case management notes
• Engine maintenance system notes by service technicians
• Supports BI tools with native SQL support & ODBC/JDBC
connectivity
• BI pilot completed in just 5 weeks – “a new standard for BI time to market”
• Managers analyze and discover new correlations between changes in
engine KPIs, sensor data, recurring key phrases from service notes & more
• New insights into root causes behind service issues – not just the numbers
• “No data left behind…Time from ‘data to decision’ drastically reduced”
ProblemWhyAIE?Results

22. Proprietary
SEARCH API SQL over ODBC/JDBC
QUERY/RESPONSE WORKFLOWS
INGESTION WORKFLOWS
CONTENT API
TIBCO Spotfire
DATA & CONTENT CONNECTORS
UNIVERSAL INDEX
EDW
Customer
Service Email CRM
OperaFonal
Events
Device
Generated
Data
Complex Event
Processing Engine Maintenance
Reports
Textual
data
is
enriched
with
text
analyFcs
(senFment,
keyphrases,
enFty
extracFon)
CUSTOMERS
DEVICES
OWNED
EMAILS
CRM
CASES
OPERATIONAL
EVENTS
KPIs
Dashboards
using
TIBCO
Spouire
contain
a
mix
of
in-­‐
memory
tables
loaded
from
AIE
with
on-­‐demand
detail
drill
down
Logical
Tables
from
the
BI
tool
perspecFve,
AIE
does
not
store
data
in
physical
tables

23. TIBCO
Spouire
and
AEvio
AIE

24. Proprietary
Benefits
of
combining
AEvio
and
TIBCO
Spouire
VisualizaFon
of
unstructured
content
and
data
that
does
not
currently
exist
in
the
BI
stack,
providing
criFcal
business
process
and
analysis
context
Rich
Text
AnalyFcs
to
gain
insight
from
unstructured
content
that
can
be
visualized
in
Spouire
Full-­‐text
search
within
Spouire
Dashboards
-­‐
providing
a
complete
Data
Discovery
experience
Agile,
complete,
UIA
technology
stack

25. Proprietary
Spotfire Server
Extracted
or
On-­‐Demand
via
JDBC
AIE
and
TIBCO
Spouire
Reference
Architecture
Direct
via
ODBC
Spotfire
Professional
Spotfire
Web Player
Hadoop A/RDBMS/EDWWeb Server File Server Email Server CMS, CRM, ERP
ACTIVE
INTELLIGENCE
ENGINE
(AIE)

26. Proprietary
Learn
more
AEvio
Big
Data
Resources
hBp://go.aEvio.com/analyze-­‐everything/

27. Proprietary
Thank
you!