Enabling Flexible Governance for All Data Sources

Welcome

Host:
Eric Kavanagh
eric.kavanagh@bloorgroup.com

Twitter Tag: #briefr The Briefing Room

Mission

!   Reveal the essential characteristics of enterprise software,
good and bad

!   Provide a forum for detailed analysis of today s innovative
technologies

!   Give vendors a chance to explain their product to savvy
analysts

!   Allow audience members to pose serious questions... and get
answers!


FEBRUARY: Analytics

March: OPERATIONAL INTELLIGENCE
April: INTELLIGENCE

May: INTEGRATION


Analytics

Flexibility Accessibility Integrity


Analyst: Robin Bloor

Robin Bloor is
Chief Analyst at
The Bloor Group

robin.bloor@bloorgroup.com


Birst

! Birst offers a SaaS-based, multi-tenant BI platform; it can
also be deployed on-premise

!   The Birst solution is capable of unifying siloed technologies,
automating data management and providing agile
enterprise-class analytics

! Birst’s approach enables self-service analytics by allowing
business users to manage and add new data sources, create
custom dashboards and collaborate across the organization


Brad Peters

Brad Peters is the CEO and co-founder of
Birst. Brad has spent the last 10 years building
analytics products and solutions. Prior to
working at Birst, he helped found and later
led the Analytics product line at Siebel
Systems, which forms the basis of Oracle’s
current OBIEE product family. Brad started his
career as an investment banker for Morgan
Stanley in the New York M&A practice. Brad
regularly blogs for Forbes.com where he
writes about Cloud and business software
related issues.


REIN
IN
DATA
CHAOS:

BRINGING
FLEXIBLE
GOVERNANCE
TO
ALL

DATA
SOURCES

Brad
Peters

CEO
and
Co-‐Founder

February
5,
2013

BI
AS
ORIGINALLY
CONCEIVED

•  A
centralized
data
warehouse

•  Data
is
“clean”
and
run
through
rigorous
checks

•  IT
is
the
steward
of
master
data

10

X

BI
AS
ORIGINALLY
CONCEIVED

Except
It
Doesn’t
Work
As
AdverDsed

• Does
not
scale
organizaJonally

• Very
inﬂexible

• IT
cannot
possibly
take
responsibility
for
all
data

• For
users
where
100%
of
their
data
is
not
in
the
warehouse,

they
must
resort
to
extracts

•  A
centralized
data
warehouse

•  Data
is
“clean”
and
run
through
rigorous
checks

•  IT
is
the
steward
of
master
data

11

BI
VERSION
2.0
-‐
HUB
AND
SPOKE

•  Warehouse
is
a
“staging
area”

•  Departments
build
their
own
data
sets

•  IT
is
the
steward
of
master
data

12

X

BI
VERSION
2.0
-‐
HUB
AND
SPOKE

Except
It
Also
Doesn’t
Work

• Scales
slightly
beRer

• Hugely
labor
and
integraJon
intensive

• Requires
deep
technical
skill
at
mart
level

• Loss
of
central
data
integrity

• Latency

• Loss
of
control
and
governance

•  Warehouse
tandards
for
uJlizing
central
data

• No
s is
a
“staging
area”

•  Departments
build
their
own
data
sets

• No
“single
version
of
truth”
•  IT
is
the
steward
of
master
data

13

WHAT
REALLY
HAPPENS

Business
Users
“Go
Rogue”
Extracts
Are
Taken
And

Combined
With
Local
Data

In
Excel
For
One-‐oﬀ
Analysis

• No single version of truth
• Infrequent analysis and stale data

14

WHAT
REALLY
HAPPENS

• Really
need
an
environment
that
can
host
mulJple

diﬀerent
sets
of
data
–
some
high
quality,
some
not

• That
allows
IT
to
manage
their
data

• But
allows
other
organizaJons
to
self-‐serve
with

their
own
data
AND,
most
importantly,
combine

these
data
sets

Business
Uneed
a
mRogue”
analyJcs
infrastructure
with

• I.e.
You
sers
“Go
ulJ-‐tenant
Extracts
Are
Taken
And

Combined
With
Local
Data

that
allows
business
users
to
manage
their
own
data
nalysis

In
Excel
For
One-‐oﬀ
A
• No single version of truth
• Infrequent analysis and stale data

15

MANAGED
DATA
MASHUPS

16

BIRST
ARCHITECTURE

17

Example:
Sales
AnalyJcs
Datamart

(Birst
Managed)

Simple
campaign
data
source
loaded

separately
in
self-‐contained
space

Import
Contacts
and
Sales
OpportuniJes

Package

Use
Birst
Modeling
to
link
Package
Objects

to
New
Campaign
Data
Source

End-‐user
can
select
columns
from
either

place
seemlessly

Metadata
coming
from
parent

space

Metadata
coming
from
child
space

ABOUT
BIRST

Key
Birst
Facts

•  #1
Cloud
BI
Provider
Market
&
Product
Leader

•  Over
1,000
organizaJons
rely
on
Birst
across
all
verJcals

•  Direct
customers

•  ISV’s
for
embedded
analyJcs

•  Typical
deployment
have
mulJple
data
sources
with
large
data

volumes
(>100’s
M
records)

Slide
24

FIND
OUT
MORE

Test
Drive
Birst
Express

•  Register
at
birst.com/express

Join
a
Birst
live
demo

•  Register
at
birst.com/livedemo

Contact
us

•  Email:
info@birst.com

•  Phone:

(866)
940-‐1496

Slide
25

Perceptions & Questions

Analyst:
Robin Bloor


Data Pools and Flows

DATA POOLS DATA FLOWS

!   Transactional databases !   Data integration flows

!   Data warehouse !   External streams

!   Operational data store !   Emails, texts, etc.

! Hadoop !   Log files

!   Data marts !   RFID, embedded sensors

!   Desktop data !   People data (social media)

!   Archiving

The Bloor Group

Data Flow Processes
HADOOP/DBMS (QUERIES) ETL

CLEANSING

GOVERNANCE

SECURITY

BI/ANALYTICS

The Bloor Group

The Data Flow Analytics Issue

The Bloor Group

The Challenge
And at the same time, the data has to move as fast
as possible…

The Bloor Group

The Challenge
And at the same time, the data has to move as fast
as possible…

THIS IS NOT SO EASY TO ACHIEVE

The Bloor Group

Questions

!   In my presentation I highlight the issue of
“repetitive self-service.” Is this something that Birst
can cater for?

!   Performance is in our view increasingly becoming a
factor in “data flow management.” How does Birst
scale to meet escalating performance demands?

!   Can you describe the nature of the automated multi-
dimensional database – what workloads does it
optimize?

The Bloor Group

Questions

!   How does Birst fit data governance in with the flow
of data?

!   Which types of business/size of business do you see
as most suited to this capability?

!   Which companies/products do you regard as
competitors (either direct or near)?

!   Which companies/products do you partner with?

!   Does Birst offer this as an appliance?

The Bloor Group

Upcoming Topics

This month: Analytics

March: Operational
Intelligence

April: Intelligence

May: Integration
www.insideanalysis.com


Thank You
for Your
Attention

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Enabling Flexible Governance for All Data Sources

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