Dcode42 Demo Day Materials

1. 1
Analytics Accelerator
What questions do you have?
1
Mike Gormley
Federal Team Lead,
michael.gormley@tamr.com, 410-271-6321
2017
Tamr – Dcode42 Demo Day

2. Tamr Overview
Key ManagementCompany Overview
Tamr enables enterprises to harness the analytic power of
all their data using “Enterprise Data Unification”
Headquarters: Cambridge MA;
Additional Offices: San Francisco, NYC, DC
Founded: 2013
Customers
Andy Palmer
Co-Founder & CEO
Previously: Founder, CEO Vertica
Dr. Michael Stonebraker
Co-Founder & CTO
Previously: Founder,
Ingres/Postgres, HP Vertica
Confidential
Investors
US Intelligence
Community

3. 33
It would be useful if enterprise
data looked like this.
HOW DATA IS ORGANIZED IN THE ENTERPRISE

4. 44
HOW DATA IS ORGANIZED IN THE ENTERPRISE
What enterprise data is really like
Prone to constant change/entropy
Budgets
Re-orgs
Leadership
Changes
Security
Data
Hoarding
Legacy
Burden
Data
Governance Competing
Agendas
It would be useful if enterprise
data looked like this.

5. 5
THE EFFECTS OF HOW DATA IS ORGANIZED
According to Ventana Research...
Analysts spend 60 to 80 percent of their time on data preparation instead
of analysis.
Data heterogeneity creates a challenge for connecting disparate
sources needed for powerful business processes.

6. 6
Budgets
Re-orgs
Leadership
Changes
Security Data
HoardingLegacy
BurdenData
Governance Competing
Agendas
THE CHALLENGES OF HOW DATA IS ORGANIZED
1. Longer IT Projects: Major data
projects take 6-12+ months.
2. Manual Effort: Review 20-50% to
ensure usable and quality data.
3. Instant Obsolescence: Rules-
based systems can’t keep up with
changing data.
4. Data Quality Problems: Can the
results be trusted?

7. 77
THE MACHINE + HUMAN PROPOSITION
7
1. Rapidly Build 360 Views: rich data
with additional attributes and new
columns.
2. Enable Decision Process: use
granular data with existing tools and
teams.
3. Trusted Data: data quality drives
adoption and is critical for business
users.
SME Input
• Data driven
• Probabilistic
• Not rules
based
Machine Learning
+
• Transfer
knowledge
and
context
from SMEs

8. 8
In SAP Lambda,
is “MaterialTotal” the
same as “Part Price”?
Is “Husky #.25 J Bit” in
table “Invoices” a
“Hardware > Bolt”?
Emerson SA
342 Suite 34
KY
Rosemount
Emerson
342 Main St
KY, USA
Data Expert
De-Duplicating Records
Classifying/Categorizing Items
DATA UNIFICATION TASKS AND ITERATIVE LEARNING
Mapping Attributes & Schema
• Map in Hundreds of Data Sources
• Dynamic and Robust With Data Change
• Granular Insight From Level 3+ Classification
• Near Real-time Visibility
• Map in Hundreds of Data Sources
• Dynamic and Robust With Data Change

9. 99
TAMR PUBLIC SECTOR USE CASES
US INTELLIGENCE
AGENCY
• Match data of known entities with inbound, open source data
• Consolidate and score output of various intel gathering systems
• Consolidate and harmonize traveler information from watchlists,
reservations systems and manifest list
• Identify and track sources of non-compliant imported goods
• Supplier and logistic data mastering
• Automating personnel record merging
Proposed projects
and POCs with DoD
and other agencies

10. 1010
TAMR COMMERCIAL USE CASES
CHALLENGE:
TAMR RESULTS:
Reduce costs across thousands of suppliers and hundreds of internal
ERP systems
Unified vendor and part dated yielded $80M savings in Year 1, expect
$300M in Year 2
Finance and Risk database had outgrown the curation process,
compromising data quality with outdated content
Expedited process by several months, reduced manual effort by 40%
saving 28 FTEs annually, achieve precision and recall rates over 95%
Unify and clean Toyota Motor Europe customer data that is collected by
hundreds of systems across 30 national marketing and sales companies
Complete view of each customer at a regional level with an automated
ongoing process
CHALLENGE:
TAMR RESULTS:
CHALLENGE:
TAMR RESULTS:

11. 11
Analytics Accelerator
What questions do you have?
11
Tamr Q & A