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SPEAKER & COMPANY INTRODUCTIONS
Harald SmithDirector of Product ManagementTrillium Software
• 20 years in Information Management incl. data quality, integration, and governance
– Consulting, product management,
software & solution development
• Co-author of Patterns of Information Management, as well as two Redbooks on Information Governance and Data Integration
Ian RowlandsProduct Marketing ManagerASG Technologies
Ian is responsible for the communication of ASG's metadata-management based solutions. He was previously VP of Metadata Development and VP for Product Management. Before ASG, Rowlands was Director of Indirect Channels for Viasoft, a leading EAM vendor (acquired by ASG), owning relationships with partners outside North America. Rowlands has worked extensively in metadata management and IT systems and financial management
DO YOU HAVE CONFIDENCE IN YOUR DATA?
“Diagnosing Key Data Management Challenges,.” FIMA Benchmark Report, 2017
have deployed data lineage to shed light on the transformations their data undergoes from a point of origination.
of organizations employ Data Quality Analysis for Data Intelligence
But Only 34%
65%
POLL QUESTION 1
Which of these use cases of Data Quality/Data Governance are most important to your organization?
1. Compliance (e.g. GDPR, CCAR, KYC)
2. Risk Mitigation
3. Business Value (e.g. data monetization)
4. Cost Reduction (e.g. process optimization)
Volume and Complexity Is Growing
Compliance Demands Broader and Deeper
Trust and Confidence in Data Is Decreasing
Can I trust this data to support
our new business initiative?
Are we compliant with Federal
Reporting Regulations?
Do we have PII or PCI exposed
in our data lake?
How many places have we stored the same
data?
SIGNIFICANT CHALLENGES FOR DATA DRIVEN ORGANIZATIONS
▪ EU GDPR, CCAR, KYC, AML
• Protect personal data
• Provide for “right to be forgotten” and data portability
• Demonstrate “privacy by design”
• Document data accuracy, privacy and security
▪ Public Health Service Act Section 340B
• Ensure price transparency
• Enable covered entities to stretch Federal resources
• Document pricing, strength, dosage, delivery mechanisms
• Report to Health Resources and Services Administration
▪ Data Monetization
• Test ability to generate new revenue stream from available data
• Ensure highest quality data delivery to 3rd parties
• Self Service shopping cart with quality data sets
• Modernization of data estate
• Better quality insights and analytics
• Trusted, traceable data
Compliance Risk Mitigation Business Value Cost
▪ Claims Processing
• Cost in rejected claims
• Manual rework cost to fix errors
• Delays in adjusting claims
• Customer dissatisfaction
• Impacts and corrections to downstream reports
POLL QUESTION 2
How integrated, automated and available is Data Quality for your users today?
1. Very much integrated and available
2. Somewhat integrated and available
3. Not at all integrated or available
4. Integrated but not very available
5. Available but not integrated
Risk Data Aggregation: Banks and other financial institutions must show prudent management
of risk.
The Ask: Reliably demonstrate, on demand, knowledge of how risk is calculated and
aggregated.
CHALLENGE
SOLUTION
BENEFIT
Financial institutions must access multiple sources for risk related data such as loan
balances, geographic risk and collateral. This calls into question whether banks know the
lineage, quality, completeness, and accuracy of the data.
With Enterprise Data Intelligence and Trillium data quality, financial institutions can
identify key data elements, use Zero-Gap Data lineage to accurately trace the data
through applications and data flows and judge quality at each stage.
Avoid increased intensity of supervision, be ready for audits, limit cost of expanded
capital “buffers” and other limits on risk-taking and growth opportunities required when
confidence in reliability and quality of compliance metrics is low.
TRILLIUM + ASG INTEGRATION USE CASES
ENTERPRISE DATA INTELLIGENCE (& QUALITY) SOLUTION OVERVIEW
Comprehensive Metadata Repository
DI Platform – Deploy On-Premise or Partner Hosted
Policy Based Data Governance Data Quality Insight For Any User
Depth & Breadth: 220 ScannersZero-Gap Data Lineage Transparent Data Flow Visualization
DATA LINEAGE DELIVERS CONFIDENCE
Report Audit – Traceability of Process and Data
• Where does this data come from?
• What calculations are applied?
• What records are selected?
• How recent is the report?
• Can you trust this report and all of its data fields?
• Can I trace my data quality?
Knowing the flow of data proves its worth
Source Data ETL Data WarehousesData Lakes
Business Objects
BusinessReports
How Confident Is
Your Decision?
POLL QUESTION 3
Which of the following is most important to you?
1. Quality of critical data elements
2. Gain insight into data quality gaps
3. Quality being performed near source
4. Know where quality is compromised
5. Know if changes affect data/quality
6. View data quality trends over time
PATENT PENDING ZERO GAP LINEAGEDYNAMIC VIEWS OF CROSS PLATFORM TRACING
COBOL IMS/DBD
COBOL BMS MapCopybook
JAVA
MAINFRAME
Business Objects Universe
ETL
Oracle EDW{PLSQL}
EDW to BI
Data Quality Indicators
Transformation Indicator
Transformation Detail
INCREASED VALUE FROM DATA LINEAGE AND DATA QUALITY ACROSS YOUR ENTERPRISE
1 Associate quality measures to your critical data elements.
ValiditySun 05/01/2016 12:00:00 PM MDTThreshold: 96Pass: 100Dimensions: Accuracy
CompletenessSun 05/01/2016 12:00:00 PM MDTThreshold: 98Pass: 99Dimensions: Completeness
2 Ensure data quality is being performed near the source.
INCREASED VALUE FROM DATA LINEAGE AND DATA QUALITY ACROSS YOUR ENTERPRISE
INCREASED VALUE FROM DATA LINEAGE AND DATA QUALITY ACROSS YOUR ENTERPRISE
3 Gain insight into where data quality might be compromised by data transformations and why.
4 Understand any changes that may impact critical data elements and data quality.
5 View data quality measures over time (aka, trend analysis).
INCREASED VALUE FROM DATA LINEAGE AND DATA QUALITY ACROSS YOUR ENTERPRISE
6 View data quality summary or details associated with specified results
DRILL INTO IDENTIFIED DATA QUALITY ISSUES
DELIVERING VALUE THROUGH DATA LINEAGE AND DATA QUALITY INTEGRATION
▪ Associate quality measures to your critical data elements.▪ Gain insight into where data quality gaps exist.▪ Ensure data quality is being performed near the source.▪ Gain insight into where data quality might be compromised by data transformations and why.▪ Understand any changes that may impact critical data elements and data quality.▪ View data quality measures over time (aka, trend analysis).
Check out the website at: www.asg.com
Or reach out to:Jill [email protected]
Check out the website at : www.trilliumsoftware.com
Or reach out to:Don [email protected]
CONTACT ASG CONTACT TRILLIUM
DISCOVER MORE
Download the new Information Management whitepaper, Discover the Value of Data Quality for Data Governance Success http://response.trilliumsoftware.com/WP-Info-Management-Discover-Value Data-Quality-For-Data-Gov-Success-2017