The document discusses cloud-based self-service data discovery tools for IBM Cognos TM1 and IBM mainframes. It describes RESTful APIs and OData standards that allow for uniform data modeling and operations. Rocket Software's Rocket Discover product is presented as enabling end-to-end data discovery across disparate data sources through intuitive dashboard creation and sharing capabilities.

1. #ibmvision
CBS-­‐1148
Cloud-­‐based
Self-­‐Service
Data
Discovery
for
IBM
Cognos
TM1
and
IBM
Mainframes
Patrick Spedding
Managing Director, BI R&D
Rocket Software
Ronnie Rich
Product Manager IBM Cognos TM1
IBM
IBM Vision 2015 Conference

2. ©2015 IBM Corporation#ibmvision
RESTful
API
§ REpresenta(onal
State
Transfer
is
a
style
of
so/ware
architecture
for
distributed
systems
– REST
is
rapidly
becoming
the
predominant
Web
service
design
model
– O/en
associated
to
HTTP
but
the
RESTful
principles
are
protocol
independent
§ Basic
CRUD
opera(ons,
if
applicable,
are
preFy
well
defined
and
associated
with
their
respec(ve
HTTP
method
(GET,
POST,
PUT
and
DELETE)
§ As
of
10.2
RP2
added
a
OData
compliant
version
of
the
RESTful
API
2

3. ©2015 IBM Corporation#ibmvision
TM1
Server
APIs
–
Overview
3
RESTful API stack
Core TM1 Server
Classic API
Classic API
C, Java & .NET APIs
HTTP based client
consuming RESTful API
Proprietary
protocol
HTTP(S)

4. ©2015 IBM Corporation#ibmvision4
OData
§ Designed
through
an
Open
Process
– OData.org,
mailing
lists
– Released
under
the
Open
Specifica(on
Promise
§ Growing
Industry
Support
– Government,
Enterprise,
Consumer,
internal
systems
§ Recently
announced
OData
Technical
CommiFee
in
OASIS
for
Standardiza(on
– Support
from
IBM,
Microso/,
SAP,
Progress,
WSO2,
Citrix,
CA,
Red
Hat
§ Work
with
schema.org
on
vocabularies
for
common
seman(cs

5. ©2015 IBM Corporation#ibmvision5
OData
Provides
§
Uniform
way
to
model
data
– Intui(ve,
familiar
model
of
en((es
and
rela(onships
§ A
uniform
way
of
represen(ng
structured
data
– Atom/XML,
JSON
formats
§ Uniform
URL
conven(ons
– Naviga(on,
filtering,
sor(ng,
paging,
custom
func(ons,
etc.
§ Uniform
opera(ons
– Addressability
– GET,
POST,
PATCH,
DELETE,
custom
ac(ons
§ Uniform
data
and
metadata
annota(ons
for
shared
vocabularies
– Define
common
seman(cs
across
schemas,
opera(ons
§ while
keeping
the
barrier
of
entry
as
low
as
possible

6. ©2015 IBM Corporation#ibmvision
Rocket
SoGware:
Driving
IBM
Customer
Successes
for
20
Years

7. ©2015 IBM Corporation#ibmvision
Digital
DisrupMon:
The
Future
of
BI
“By
2017,
most
business
users
and
analysts
in
organisa(ons
will
have
access
to
self-­‐service
tools
to
prepare
data
for
analysis.”
Gartner
“Managed BI self-service will continue to close
the business and technology gap.”
Forrester
“Visual data-discovery, an important enabler of
end user self-service, will grow 2.5x faster than
the rest of the market, becoming a requirement
for all enterprises by 2018”.
Forbes

8. ©2015 IBM Corporation#ibmvision 88
“Given the remarkably fast
pace of innovation and
change, if you’re not focused
on speed, you’re dead in the
water. Creativity without
speed is useless. Old rules and
standard operating procedures
don’t lead to innovation”
Speed
“Today’s markets demand
speed. Speed trumps all else.”
(Nolan Bushnell “Finding the Next Steve Jobs”)

9. ©2015 IBM Corporation#ibmvision
Buyer/User
Profile
• Excel
Savvy,
mastering
all
func(onality
from
pivot
tables
to
complex
func(on
support
• Well-­‐versed
in
data
and
knows
what
enterprise
systems
they
need
to
access
for
each
business
need
Pain
Points
• Needs
an
easy
to
use
data
prep
tool
so
she
can
easily
connect
to
and
enhance
data
• Looking
to
replicate
excel
func(onality
within
dashboards
Persona
Profiles
&
Pain
Points
Buyer/User
Profile
• Believes
in
analyzing
data
to
support
business
decisions.
• His
reputa(on
is
on
the
line,
he
needs
to
be
able
to
make
the
right
business
decisions.
Pain
Points
• He
needs
a
quick
and
easy
way
to
access
all
the
data
sources
he
needs.
• Wants
a
simple
tool
that
allows
him
to
create
dashboards
at
a
moments
no(ce.
Influencer
Profile
• Burdened
by
demands
of
users
throughout
the
org
reques(ng
visualiza(ons.
• Cares
about
system/data
reliability,
scale,
security
and
worthiness
Pain
Points
• Wants
flexibility
to
run
on-­‐
premise
or
in
the
cloud,
one
that’s
easy
to
administer
• Doesn’t
want
to
hire
more
BI
focused
support
staff
C-Level Exec & Line of
Business User
Business Unit Controller,
Business/Financial Analyst
VP/Director of IT, Director
of System Operations

10. ©2015 IBM Corporation#ibmvision
From
Complexity
to
Clarity:
Rocket
Discover
A Business Intelligence Solution for Line of Business
Managers and Senior Level Executives
who need an intuitive, self-service offering
that empowers them to access any data and create
visual interactive dashboards
that expose trends, outliers, historical details, and
information
so they’re equipped to share information and make
better, more informed business decisions.

11. ©2015 IBM Corporation#ibmvision
End-­‐to-­‐End
Data
Discovery
Business Need
• Connecting disparate data across the
enterprise
• A single solution for enrichment & discovery
• No time for data warehouse development
• Access to siloed desktop sources
From Desktop to
Relational, MultiValue,
Mainframe, OLAP, and
more
No need to purchase
additional products
Business Need
• Intuitive environment to create dashboards
• Easy and quick data exploration & analytics
• Business user solution
• Views for trending, outliers, comparison
• Proactive notification of issues
Self-service, Guided
navigation, Drag-and-
drop dashboard
creation, One-click
drilldown to pinpoint
focused data
Proactive pre-built
analytic functions
Auto Alerts for
proactive action,
Intelligent Filters
Business Need
• Easily share data views with team
• Instant and live discussion within data portal
• Ongoing communication on issues
• Share with individuals, team, internal and
external
• Templating for reuse and easy adoption
Instant messaging,
share dashboards,
personal & team
annotations
Create and share
dashboard
templates
Share & Collaborate

12. ©2015 IBM Corporation#ibmvision
Rocket
Discover
Architecture

13. ©2015 IBM Corporation#ibmvision
Designed
to
complement
the
IBM
stack
Na(ve
Connec(vity
to
IBM
Cognos
TM1
Cubes
and
Cube
Views.
Support
for
IBM
RAVE
Charts.
Support
for
IBM
So/layer

14. ©2015 IBM Corporation#ibmvision
TM1
API:
LisMng
TM1
Servers
Ac(on:
Press
Reconnect/
Connect
Result:
Populates
TM1
Server
drop-­‐down
list
Ac(on:
Select
a
TM1
Server
Result:
Shows
users
a
list
of
Cubes
in
the
TM1
Server

15. ©2015 IBM Corporation#ibmvision
TM1
API:
Showing
Cubes
from
TM1
Server
§ TM1
Authen(ca(on
(BASIC)
and
CAM
Namespace
Authen(ca(on
(CAMNamespace)
are
supported
for
all
TM1
Server
API
calls.

16. ©2015 IBM Corporation#ibmvision
TM1
API:
Cube
Views,
Subsets,
Hierarchies,
Aliases
List
Views
for
the
selected
Cube
Get
Row
Subset(s)
Get
Column
Subset(s)
Get
Title
Subsets
(aka
Contexts)
Find
out
aliases
used
for
every
Dimension
subset
Get
hierarchy
informa(on
and
business
rules

17. ©2015 IBM Corporation#ibmvision
TM1
API:
Cube
updates,
text
in
Crosstab
cells
Cell
updates
reflected
straight
away
Text
in
crosstabs

18. ©2015 IBM Corporation#ibmvision
Support
for
TM1
and
non-­‐TM1
data
Na(ve
Mainframe
VSAM
connector
(DB2
on
z/OS
coming
soon)
Other
data
sources
(e.g.
CSV,
DB2
on
LUW,
SQL
Server,
Oracle)
Social
Data
(TwiFer,
News,
Blogs)
TM1/TM1
Web

19. ©2015 IBM Corporation#ibmvision
1.5
2.0
Next Releases
Connectivity: IBM Cognos TM1, DVS, VSAM z/
OS, DB2 LUW, Social (Darwin Eco)
Analytics: Cardinality, Outliers, Auto hierarchies
Dashboarding: RAVE
1.1
Rocket
Discover
Roadmap:
IBM
specific
Connectivity: Cloud sources (Web Services/REST), Bluemix, Netezza
Analytics: Forecasting, decision tree, SPSS (Bluemix)
Connectivity: MultiValue (Universe/Unidata), DB2 z/OS,
Cognos BI SDK, IBM BigInsights
Collaboration: Storypoints, Alerts, IBM Connections
Analytics: Correlations, Segmentation/clustering
Dashboarding:, RAVE 2.0 extensibility
Reporting: ‘Lite’ Reporting/Ad-hoc Query
Other: Freemium, Hosted Trial (IBM Cloud)

20. ©2015 IBM Corporation#ibmvision
Examples

21. ©2015 IBM Corporation#ibmvision
Example:
Dynamic
Dashboard
updates

22. ©2015 IBM Corporation#ibmvision
Example:
TM1
data
in
KPIs,
Charts,
Maps

23. ©2015 IBM Corporation#ibmvision
IBM Rapidly Adaptive Visualization Engine
RAVE Engine
Visualization
"Description"

24. ©2015 IBM Corporation#ibmvision
Extensible
VisualizaMon
provides
a
growing
range
of
visualizaMon
opMons
The
Challenge:
– New
requirements
for
visualiza(ons
are
constantly
emerging
– Each
requirement
is
unique
and
is
difficult
to
meet
The
Solu.on:
– Provide
a
wider
variety
of
visualiza(ons
with
the
means
to
extend
and
customize

25. ©2015 IBM Corporation#ibmvision
Composable
Set
of
Chart
Features
Element Type
• Point, line, area, interval
(bar), polygon, schema,
text
• Each element can be
used with any data
(numeric, category, time
…)
• As many elements on a
chart as you like
Coordinates
• Any number of dimensions
can be defined, with a chain
of transformations
• Clustering and stacking
• Polar
• Transpose
• Map projections
Aesthetics
• Map Data to Graphic
Attributes.
• Works on all elements
• Color (exterior, interior,
works with gradients)
• Size (width/height/both)
• Symbol
• Dashing, General Styles
• Label, Tooltip, Meta
Layouts
• Graph Layouts (Network,
Treelike)
• Treemaps
• Custom Layouts
Faceting
• Chart-in-chart
• Paneling
Guides
• Simple Axis
• Nested Axis
• Facet Axis
• Legend

26. ©2015 IBM Corporation#ibmvision
2
IBM
RAVE
Example:
Bubble
Chart

27. ©2015 IBM Corporation#ibmvision
Rocket
DVS
–
Data
VirtualizaMon
for
IBM
zIIP
SQL
JDBC/ODBC/
DRDA
NoSQL
MongoDB API
Services
SOAP/REST/
HTML
Web
HTTP
Events
CDC/Data
Streams
Rocket
Data Virtualization
Server
Map/Reduce
Query
Op(miza(on
Parallel/IO
Data
Mapping
Caching
Design
Security
Metadata
Monitoring
Web/
Mobile
Analytics, SearchESB, ETL Transactional
Data
Landing Zones
Oracle
Infor
mix
Derby
DB2
LUW
SQL
Server
Big
Insights
Big
SQL
Mongo
DB
Cloud
Data
Adaba
s
VSAM
Sequen(
al
DB2
for
z/
OS
CICS
IMS
Natur
al
IDMS
IBM
Federa(on
Server
IBM
IDAA
IBM
Pure
Data
Landing Zones
Hadoop
Clouda
nt
DataStage
IBM
IDAA
IBM zIIP Specialty Engine
Requesting
Client
Applications
BATCH
CICS
Other
Started
Task
IMS

28. ©2015 IBM Corporation#ibmvision
Rocket
DVS
in
Rocket
Discover

29. ©2015 IBM Corporation#ibmvision
Summary
–
Rocket
Discover
§ Designed
for
business
users,
consumers
of
TM1
data
§ Supports
Cloud/On-­‐Premise,
Linux
and
Windows
Server
§ Designed
to
minimize
services/training
requirements
§ Support
for
TM1
and
non-­‐TM1
data
§ Self-­‐paced
training
via
extensive
ac(ve
eLearning
modules
§ Na(ve
connec(vity
preserves
TM1
hierarchies
and
business
rules,
leverages
fast
performance
of
TM1
engine
§ Extrac(ng
TM1
data
to
load
into
3rd
party
Data
Discovery
tools
is
not
an
op(mal
approach
for
most
situa(ons

30. ©2015 IBM Corporation#ibmvision
For
More
InformaMon:
FOM-­‐1106
The
Benefits
of
Business
Partner
Authored
Pre-­‐Built
TM1
Applica(ons
Hilton
Bonnet
Creek
–
Palm
Beach
Tue,
19-­‐May
10:00
AM
-­‐
11:00
AM
1097A
Hands-­‐on
Lab
with
IBM
Cognos
TM1
SDK
–
REST,
Java
and
IBM
Cognos
TM1
Web
Hilton
Bonnet
Creek
-­‐
Dade
Wed,
20-­‐May
09:00
AM
-­‐
12:00
PM

31. ©2015 IBM Corporation#ibmvision
SupporMng
Material
Rocket
Discover
30
Day
Trial
Ø Register
for
the
trial
Ø Watch
the
eLearning
Tutorials
Ø Join
the
Conversa(on
on
the
Rocket
Discover
Forum
Ø Par(cipate
in
the
Discovering
New
Insights
contest.
The
winner
receives
an
Apple
Watch
Interested
in
Learning
More
Ø Inforgraphic
–
The
Game
of
Self-­‐Service
Intelligence
Ø Rocket
Discover
Brochure
Ø Rocket
Discover
&
IBM
Cognos
TM1
Brochure
Ø IDC
Dat-­‐a-­‐Glance:
Self-­‐Service
BI
and
Data
Discovery
Feedback
Channel
Ø Contact
the
Discover
Team
at
rocket-­‐discover@rocketso/ware.com
and
share
your
opinion
on
Rocket
Discover
and
the
30
Day
Trial.
© 2014 Rocket Software, Inc. All Rights Reserved.

32. ©2015 IBM Corporation#ibmvision
eLearning:
hYp://www.rocketsoGware.com/product-­‐families/rocket-­‐discover
§ Navigation Overview:
hFp://www3.rocketso/ware.com/discover/naviga(on.html
§ Introducing Dashboard:
hFp://www3.rocketso/ware.com/discover/intro-­‐dashboards.html
§ Editing a Dashboard:
hFp://www3.rocketso/ware.com/discover/edi(ng-­‐dashboard.html
§ Drilling into Data:
hFp://www3.rocketso/ware.com/discover/drilling-­‐into-­‐data.html
§ Data Preparation:
hFp://www3.rocketso/ware.com/discover/data-­‐prepara(on.html
§ Sharing and Collaborating:
hFp://www3.rocketso/ware.com/discover/sharing-­‐collabora(ng.html
§ Using TM1: hFp://www3.rocketso/ware.com/discover/tm1.html

33. 33
Thank
You!
Patrick
Spedding
Managing
Director,
BI
R&D
Rocket
SoGware
pspedding@rs.com
@spedding
www.rocketsoftware.com
Rocket Software Group
@Rocket
Ronnie
Rich
Product
Manager
IBM
Cognos
TM1
IBM

34. 34
Presenter
Name
Here,
Presenter
Mtle
here
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