SlideShare ist ein Scribd-Unternehmen logo

The art of implementing data lineage

•Als PPTX, PDF herunterladen•
•
L
Leigh Hill

Data lineage is a regulatory and internal requirement with potential to deliver significant operational and business benefits, but financial institutions can find it difficult to implement and complex to maintain as systems and regulatory requirements themselves, change quickly. The importance of understanding where the true source of the data is coming from, where the data flows to and what has changed cannot be overstated. The webinar defines data lineage and discuss implementation through the eyes of those that have implemented and sustained successful lineage solutions with significant benefits. Listen to the webinar to find out about: - Data management for data lineage - Winning buy-in for projects - Best practice implementation - Operational and business benefits - Expert practitioner advice

Technologie
1 von 28
FROM DataManagementReview.comSeptember 29, 2016 The art of implementing data lineage The webinar will start soon Check out other upcoming webinars, white papers, blogs and events at www.DataManagementReview.com If you’re a vendor looking for high quality content to help articulate your message, take a look at www.a- teamgroup.com. Or get in touch: 020 8090 2055 / theteam@a-teamgroup.com
FROM DataManagementReview.comSeptember 29, 2016 Welcome to A-Team Group’s webinar: The art of implementing data lineage
FROM DataManagementReview.comSeptember 29, 2016 Moderator: Sarah Underwood, Editor, A-Team Group
FROM DataManagementReview.comSeptember 29, 2016 Panel Member: Jesse Canada*, Vice President of Business Metadata, Rules, and Reference Data Management, Citizens Bank Areas of Expertise: • Defining innovative metadata solutions for proficient problem solving, demonstrating value added business results, and supporting the enterprise programme • Integrating metadata into day-to-day business processes by changing attitudes and behaviours related to data use and understanding • Identifying metadata processes for Hadoop and Big Insights to ensure seamless data usability for stakeholders * Any comments made by Jesse Canada on the webinar are her own personal views and not those of Citizens Bank
FROM DataManagementReview.comSeptember 29, 2016 Panel Member: Sue Habas, Vice President, Strategic Technologies, ASG Areas of Expertise: • Worked to structure and drive enterprise metadata/data governance programmes • 18 years’ experience working with metadata, both client and customer side • Responsible for launching and guiding ASG’s Enterprise Data Intelligence solutions • Vertical experience including financial, insurance, healthcare, manufacturing and e-commerce
FROM DataManagementReview.comSeptember 29, 2016 Panel Member: Yetkin Ozkucur, Global Practice Vice President for Data Intelligence, ASG Areas of Expertise: • Worked to structure and drive enterprise metadata/data governance programmes • 15 years’ experience working with metadata • Designed and delivered many projects with a wide range of clients including financial, insurance, healthcare, manufacturing and e-commerce • Responsible for the delivery of the ASG Enterprise Data Intelligence solution
FROM DataManagementReview.comSeptember 29, 2016 What exactly is meant by data lineage Key business use cases for data lineage Client projects in the banking sector Securing buy-in for implementation projects Milestones to reach successful implementation How firms are using data lineage to respond to enquiries Advice on approaches to tracking data lineage A 10-step process to implementing data lineage Talking Points
FROM DataManagementReview.comSeptember 29, 2016 Can you give us a definition of data lineage as it applies to data management?
FROM DataManagementReview.comSeptember 29, 2016 What is data lineage?  A critical supply chain App-File-Field Transform Rule DB-Tab-Col Calculation Rule Universe- Rep-Field Data Supply Chain Customer/Patient/Event Business Terms Policies Critical Data Elements Business Traceability E2E Data Driven Lineage VerticalBusinessContext Driven
FROM DataManagementReview.comSeptember 29, 2016 The 5 W’s of Data Lineage  Where and how data lineage  Who is using the data?  What does it mean (data dictionary/glossary)?  Where does it exist and where did it come from?  When was it captured and how did it change over time?  How is it being used and how is it related? Backward Lineage Forward Lineage Where Lineage • What is the Source? • Who is the Application Owner? • What is the Quality? How Lineage • Where are my CDE’s going? • How is data being Transformed? • What reports use them?
FROM DataManagementReview.comSeptember 29, 2016 Can you explain some of the key use cases for getting data lineage right?
FROM DataManagementReview.comSeptember 29, 2016 Can you describe client projects you’ve been working on to address data lineage?
FROM DataManagementReview.comSeptember 29, 2016 How do clients secure buy-in across their organisations for projects and budget?
FROM DataManagementReview.comSeptember 29, 2016 What were the benefits you used to secure that buy-in?
FROM DataManagementReview.comSeptember 29, 2016 What objections did you meet and how did you address them?
FROM DataManagementReview.comSeptember 29, 2016 What are the key milestones in a project plan to reach successful implementation?
FROM DataManagementReview.comSeptember 29, 2016 How long do projects typically take and what are the hold ups or complications that firms experience?
FROM DataManagementReview.comSeptember 29, 2016 What does a successful implementation enable an organisation to do that it couldn’t before?
FROM DataManagementReview.comSeptember 29, 2016 A couple of scenarios in which an organisation would need to track data lineage to respond to a regulatory or internal enquiry?
FROM DataManagementReview.comSeptember 29, 2016 What advice would you give to organisations figuring out their approach to tracking data lineage?
FROM DataManagementReview.comSeptember 29, 2016 Your 10-Step Process to Implementing Data Lineage Below is a checklist of the key elements you should use when planning any data lineage project. Preparation Phase 1. Always begin with the end in mind. Determine your goals, taking into account your regulatory requirements, the business critical reports you need, and the critical insights you’re seeking 2. Define your user types, which could include: risk analysts, auditors, business stewards, BI analysts, developers/IT or enterprise architects etc 3. Prepare for your data lineage project by identifying the critical data and source systems, creating data architecture diagrams, identifying application owners 4. Prepare manual baseline, describe the effort and quality of creating lineage manually
FROM DataManagementReview.comSeptember 29, 2016 Your 10-Step Process to Implementing Data Lineage Below is a checklist of the key elements you should use when planning any data lineage project. Execution Phase 1. Create the business terms, definitions and controls that surround the data and link it to the critical data 2. Use a tool to automate the pull of the data dictionary schema’s and ETL code in order to quickly and accurately find the true source of information 3. Validate the lineage. Identify gaps and remediate 4. Roll out to end users. Visualization of the lineage. Provide views, exports, and embed lineage in other tools
FROM DataManagementReview.comSeptember 29, 2016 Your 10-Step Process to Implementing Data Lineage Below is a checklist of the key elements you should use when planning any data lineage project. Subscribe to Survive 1. Automatic change detection and notification 2. Assign responsible users to be notified of any change to the critical lineage supply chain This approach allows you to build out a reverse tracing methodology and base line for comprehensive and accurate end-to-end data lineage.
FROM DataManagementReview.comSeptember 29, 2016 Thank you to our sponsor Contact: Sue Habas VP of Strategic Technologies-Data Intelligence, ASG Email: sue.habas@asg.com Website: www.asg.com/intelligence
FROM DataManagementReview.comSeptember 29, 2016 October 6th Data Management Summit London November 17th Data Management Summit New York Upcoming A-Team Group Events Visit DataManagementReview.com/events
FROM DataManagementReview.comSeptember 29, 2016 Upcoming A-Team Group Webinars October 11th Practical approaches to improving entity data quality October 13th Integrating beneficial ownership data with client onboarding and KYC October 18th GDPR: How to build a data protection framework Visit webinars section of DataManagementReview.com
FROM DataManagementReview.comSeptember 29, 2016 A-Team Group Handbook Series Visit the data management handbooks section of DataManagementReview.com
FROM DataManagementReview.comSeptember 29, 2016 Please take the time to complete our post webinar survey We will notify you when the webinar recording is available Thank you for joining us

Empfohlen

Data Quality Best Practices
Data Quality Best PracticesData Quality Best Practices
Data Quality Best PracticesDATAVERSITY
 
Databricks Platform.pptx
Databricks Platform.pptxDatabricks Platform.pptx
Databricks Platform.pptxAlex Ivy
 
Improving Data Literacy Around Data Architecture
Improving Data Literacy Around Data ArchitectureImproving Data Literacy Around Data Architecture
Improving Data Literacy Around Data ArchitectureDATAVERSITY
 
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...Jochem van Grondelle
 
Data platform modernization with Databricks.pptx
Data platform modernization with Databricks.pptxData platform modernization with Databricks.pptx
Data platform modernization with Databricks.pptxCalvinSim10
 
Data Lakehouse, Data Mesh, and Data Fabric (r1)
Data Lakehouse, Data Mesh, and Data Fabric (r1)Data Lakehouse, Data Mesh, and Data Fabric (r1)
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
 
Data Governance and Metadata Management
Data Governance and Metadata Management Data Governance and Metadata Management
Data Governance and Metadata Management DATAVERSITY
 
Activate Data Governance Using the Data Catalog
Activate Data Governance Using the Data CatalogActivate Data Governance Using the Data Catalog
Activate Data Governance Using the Data CatalogDATAVERSITY
 

Empfohlen

Data Quality Best Practices
Data Quality Best PracticesData Quality Best Practices
Data Quality Best PracticesDATAVERSITY
 
Databricks Platform.pptx
Databricks Platform.pptxDatabricks Platform.pptx
Databricks Platform.pptxAlex Ivy
 
Improving Data Literacy Around Data Architecture
Improving Data Literacy Around Data ArchitectureImproving Data Literacy Around Data Architecture
Improving Data Literacy Around Data ArchitectureDATAVERSITY
 
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...Jochem van Grondelle
 
Data platform modernization with Databricks.pptx
Data platform modernization with Databricks.pptxData platform modernization with Databricks.pptx
Data platform modernization with Databricks.pptxCalvinSim10
 
Data Lakehouse, Data Mesh, and Data Fabric (r1)
Data Lakehouse, Data Mesh, and Data Fabric (r1)Data Lakehouse, Data Mesh, and Data Fabric (r1)
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
 
Data Governance and Metadata Management
Data Governance and Metadata Management Data Governance and Metadata Management
Data Governance and Metadata Management DATAVERSITY
 
Activate Data Governance Using the Data Catalog
Activate Data Governance Using the Data CatalogActivate Data Governance Using the Data Catalog
Activate Data Governance Using the Data CatalogDATAVERSITY
 
You Need a Data Catalog. Do You Know Why?
You Need a Data Catalog. Do You Know Why?You Need a Data Catalog. Do You Know Why?
You Need a Data Catalog. Do You Know Why?Precisely
 
Data Governance
Data GovernanceData Governance
Data GovernanceRob Lux
 
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance BigID Inc
 
Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
 
Creating an Enterprise AI Strategy
Creating an Enterprise AI StrategyCreating an Enterprise AI Strategy
Creating an Enterprise AI StrategyAtScale
 
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
 
Introducing Databricks Delta
Introducing Databricks DeltaIntroducing Databricks Delta
Introducing Databricks DeltaDatabricks
 
Data Mesh in Azure using Cloud Scale Analytics (WAF)
Data Mesh in Azure using Cloud Scale Analytics (WAF)Data Mesh in Azure using Cloud Scale Analytics (WAF)
Data Mesh in Azure using Cloud Scale Analytics (WAF)Nathan Bijnens
 
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsBuilding a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
 
8 Steps to Creating a Data Strategy
8 Steps to Creating a Data Strategy8 Steps to Creating a Data Strategy
8 Steps to Creating a Data StrategySilicon Valley Data Science
 
Introduction to Azure Data Lake
Introduction to Azure Data LakeIntroduction to Azure Data Lake
Introduction to Azure Data LakeAntonios Chatzipavlis
 
DAS Slides: Data Quality Best Practices
DAS Slides: Data Quality Best PracticesDAS Slides: Data Quality Best Practices
DAS Slides: Data Quality Best PracticesDATAVERSITY
 
Data Catalog for Better Data Discovery and Governance
Data Catalog for Better Data Discovery and GovernanceData Catalog for Better Data Discovery and Governance
Data Catalog for Better Data Discovery and GovernanceDenodo
 
Enterprise Data Management
Enterprise Data ManagementEnterprise Data Management
Enterprise Data ManagementBhavendra Chavan
 
Data Modeling Fundamentals
Data Modeling FundamentalsData Modeling Fundamentals
Data Modeling FundamentalsDATAVERSITY
 
Customer-Centric Data Management for Better Customer Experiences
Customer-Centric Data Management for Better Customer ExperiencesCustomer-Centric Data Management for Better Customer Experiences
Customer-Centric Data Management for Better Customer ExperiencesInformatica
 
The what, why, and how of master data management
The what, why, and how of master data managementThe what, why, and how of master data management
The what, why, and how of master data managementMohammad Yousri
 
Architecting a datalake
Architecting a datalakeArchitecting a datalake
Architecting a datalakeLaurent Leturgez
 
Microsoft Fabric Intro D Koutsanastasis
Microsoft Fabric Intro D KoutsanastasisMicrosoft Fabric Intro D Koutsanastasis
Microsoft Fabric Intro D KoutsanastasisUni Systems S.M.S.A.
 
Using a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricUsing a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricCambridge Semantics
 
Lean Data Lineage v10
Lean Data Lineage v10Lean Data Lineage v10
Lean Data Lineage v10Data to Value Ltd
 
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...DATAVERSITY
 

Weitere ähnliche Inhalte

Was ist angesagt?

You Need a Data Catalog. Do You Know Why?
You Need a Data Catalog. Do You Know Why?You Need a Data Catalog. Do You Know Why?
You Need a Data Catalog. Do You Know Why?Precisely
 
Data Governance
Data GovernanceData Governance
Data GovernanceRob Lux
 
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance BigID Inc
 
Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
 
Creating an Enterprise AI Strategy
Creating an Enterprise AI StrategyCreating an Enterprise AI Strategy
Creating an Enterprise AI StrategyAtScale
 
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
 
Introducing Databricks Delta
Introducing Databricks DeltaIntroducing Databricks Delta
Introducing Databricks DeltaDatabricks
 
Data Mesh in Azure using Cloud Scale Analytics (WAF)
Data Mesh in Azure using Cloud Scale Analytics (WAF)Data Mesh in Azure using Cloud Scale Analytics (WAF)
Data Mesh in Azure using Cloud Scale Analytics (WAF)Nathan Bijnens
 
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsBuilding a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
 
DAS Slides: Data Quality Best Practices
DAS Slides: Data Quality Best PracticesDAS Slides: Data Quality Best Practices
DAS Slides: Data Quality Best PracticesDATAVERSITY
 
Data Catalog for Better Data Discovery and Governance
Data Catalog for Better Data Discovery and GovernanceData Catalog for Better Data Discovery and Governance
Data Catalog for Better Data Discovery and GovernanceDenodo
 
Enterprise Data Management
Enterprise Data ManagementEnterprise Data Management
Enterprise Data ManagementBhavendra Chavan
 
Data Modeling Fundamentals
Data Modeling FundamentalsData Modeling Fundamentals
Data Modeling FundamentalsDATAVERSITY
 
Customer-Centric Data Management for Better Customer Experiences
Customer-Centric Data Management for Better Customer ExperiencesCustomer-Centric Data Management for Better Customer Experiences
Customer-Centric Data Management for Better Customer ExperiencesInformatica
 
The what, why, and how of master data management
The what, why, and how of master data managementThe what, why, and how of master data management
The what, why, and how of master data managementMohammad Yousri
 
Microsoft Fabric Intro D Koutsanastasis
Microsoft Fabric Intro D KoutsanastasisMicrosoft Fabric Intro D Koutsanastasis
Microsoft Fabric Intro D KoutsanastasisUni Systems S.M.S.A.
 
Using a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricUsing a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricCambridge Semantics
 

Was ist angesagt? (20)

You Need a Data Catalog. Do You Know Why?
You Need a Data Catalog. Do You Know Why?You Need a Data Catalog. Do You Know Why?
You Need a Data Catalog. Do You Know Why?
 
Data Governance
Data GovernanceData Governance
Data Governance
 
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance
 
Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?
 
Creating an Enterprise AI Strategy
Creating an Enterprise AI StrategyCreating an Enterprise AI Strategy
Creating an Enterprise AI Strategy
 
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
 
Introducing Databricks Delta
Introducing Databricks DeltaIntroducing Databricks Delta
Introducing Databricks Delta
 
Data Mesh in Azure using Cloud Scale Analytics (WAF)
Data Mesh in Azure using Cloud Scale Analytics (WAF)Data Mesh in Azure using Cloud Scale Analytics (WAF)
Data Mesh in Azure using Cloud Scale Analytics (WAF)
 
Building a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business GoalsBuilding a Data Strategy – Practical Steps for Aligning with Business Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
 
8 Steps to Creating a Data Strategy
8 Steps to Creating a Data Strategy8 Steps to Creating a Data Strategy
8 Steps to Creating a Data Strategy
 
Introduction to Azure Data Lake
Introduction to Azure Data LakeIntroduction to Azure Data Lake
Introduction to Azure Data Lake
 
DAS Slides: Data Quality Best Practices
DAS Slides: Data Quality Best PracticesDAS Slides: Data Quality Best Practices
DAS Slides: Data Quality Best Practices
 
Data Catalog for Better Data Discovery and Governance
Data Catalog for Better Data Discovery and GovernanceData Catalog for Better Data Discovery and Governance
Data Catalog for Better Data Discovery and Governance
 
Enterprise Data Management
Enterprise Data ManagementEnterprise Data Management
Enterprise Data Management
 
Data Modeling Fundamentals
Data Modeling FundamentalsData Modeling Fundamentals
Data Modeling Fundamentals
 
Customer-Centric Data Management for Better Customer Experiences
Customer-Centric Data Management for Better Customer ExperiencesCustomer-Centric Data Management for Better Customer Experiences
Customer-Centric Data Management for Better Customer Experiences
 
The what, why, and how of master data management
The what, why, and how of master data managementThe what, why, and how of master data management
The what, why, and how of master data management
 
Architecting a datalake
Architecting a datalakeArchitecting a datalake
Architecting a datalake
 
Microsoft Fabric Intro D Koutsanastasis
Microsoft Fabric Intro D KoutsanastasisMicrosoft Fabric Intro D Koutsanastasis
Microsoft Fabric Intro D Koutsanastasis
 
Using a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricUsing a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Using a Semantic and Graph-based Data Catalog in a Modern Data Fabric
 

Andere mochten auch

Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...DATAVERSITY
 
Informatica Becomes Part of the Business Data Lake Ecosystem
Informatica Becomes Part of the Business Data Lake EcosystemInformatica Becomes Part of the Business Data Lake Ecosystem
Informatica Becomes Part of the Business Data Lake EcosystemCapgemini
 
How Cognizant's ZDLC solution is helping Data Lineage for compliance to Basel...
How Cognizant's ZDLC solution is helping Data Lineage for compliance to Basel...How Cognizant's ZDLC solution is helping Data Lineage for compliance to Basel...
How Cognizant's ZDLC solution is helping Data Lineage for compliance to Basel...Dr. Bippin Makoond
 
Meta Data Presentation 2013
Meta Data Presentation 2013Meta Data Presentation 2013
Meta Data Presentation 2013Angela Boyd
 
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...DATAVERSITY
 
DAMA Ireland - GDPR
DAMA Ireland - GDPRDAMA Ireland - GDPR
DAMA Ireland - GDPRDAMA Ireland
 
How to establish a sustainable solution for data lineage
How to establish a sustainable solution for data lineageHow to establish a sustainable solution for data lineage
How to establish a sustainable solution for data lineageLeigh Hill
 
How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...
How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...
How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...Neo4j
 
Graphically understand and interactively explore your Data Lineage
Graphically understand and interactively explore your Data LineageGraphically understand and interactively explore your Data Lineage
Graphically understand and interactively explore your Data LineageMohammad Ahmed
 
Webianr: GDPR: How to build a data protection framework
Webianr: GDPR: How to build a data protection frameworkWebianr: GDPR: How to build a data protection framework
Webianr: GDPR: How to build a data protection frameworkLeigh Hill
 
Data Discovery & Lineage in Enterprise Hadoop
Data Discovery & Lineage in Enterprise HadoopData Discovery & Lineage in Enterprise Hadoop
Data Discovery & Lineage in Enterprise HadoopDataWorks Summit
 
The Parts Of Plants
The Parts Of PlantsThe Parts Of Plants
The Parts Of Plantsehostetler
 
LUMA's State of Digital Marketing at DMS West 16
LUMA's State of Digital Marketing at DMS West 16LUMA's State of Digital Marketing at DMS West 16
LUMA's State of Digital Marketing at DMS West 16LUMA Partners
 
Parts of the plant and their functions
Parts of the plant and their functionsParts of the plant and their functions
Parts of the plant and their functionsGenedkin Charm Aquino
 

Andere mochten auch (19)

Lean Data Lineage v10
Lean Data Lineage v10Lean Data Lineage v10
Lean Data Lineage v10
 
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...
Subscribing to Your Critical Data Supply Chain - Getting Value from True Data...
 
ASG Sector Snapshots
ASG Sector SnapshotsASG Sector Snapshots
ASG Sector Snapshots
 
Mazda Trio Meeting
Mazda Trio MeetingMazda Trio Meeting
Mazda Trio Meeting
 
Lean Data Lineage
Lean Data LineageLean Data Lineage
Lean Data Lineage
 
Informatica Becomes Part of the Business Data Lake Ecosystem
Informatica Becomes Part of the Business Data Lake EcosystemInformatica Becomes Part of the Business Data Lake Ecosystem
Informatica Becomes Part of the Business Data Lake Ecosystem
 
How Cognizant's ZDLC solution is helping Data Lineage for compliance to Basel...
How Cognizant's ZDLC solution is helping Data Lineage for compliance to Basel...How Cognizant's ZDLC solution is helping Data Lineage for compliance to Basel...
How Cognizant's ZDLC solution is helping Data Lineage for compliance to Basel...
 
Meta Data Presentation 2013
Meta Data Presentation 2013Meta Data Presentation 2013
Meta Data Presentation 2013
 
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...
 
DAMA Ireland - GDPR
DAMA Ireland - GDPRDAMA Ireland - GDPR
DAMA Ireland - GDPR
 
How to establish a sustainable solution for data lineage
How to establish a sustainable solution for data lineageHow to establish a sustainable solution for data lineage
How to establish a sustainable solution for data lineage
 
How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...
How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...
How to Search, Explore and Visualize Neo4j with Linkurious - Jean Villedieu @...
 
Graphically understand and interactively explore your Data Lineage
Graphically understand and interactively explore your Data LineageGraphically understand and interactively explore your Data Lineage
Graphically understand and interactively explore your Data Lineage
 
Webianr: GDPR: How to build a data protection framework
Webianr: GDPR: How to build a data protection frameworkWebianr: GDPR: How to build a data protection framework
Webianr: GDPR: How to build a data protection framework
 
Data Discovery & Lineage in Enterprise Hadoop
Data Discovery & Lineage in Enterprise HadoopData Discovery & Lineage in Enterprise Hadoop
Data Discovery & Lineage in Enterprise Hadoop
 
GDPR: Key Article Overview
GDPR: Key Article OverviewGDPR: Key Article Overview
GDPR: Key Article Overview
 
The Parts Of Plants
The Parts Of PlantsThe Parts Of Plants
The Parts Of Plants
 
LUMA's State of Digital Marketing at DMS West 16
LUMA's State of Digital Marketing at DMS West 16LUMA's State of Digital Marketing at DMS West 16
LUMA's State of Digital Marketing at DMS West 16
 
Parts of the plant and their functions
Parts of the plant and their functionsParts of the plant and their functions
Parts of the plant and their functions
 

Ähnlich wie The art of implementing data lineage

Approaches to data quality
Approaches to data qualityApproaches to data quality
Approaches to data qualityLeigh Hill
 
How to leverage a market data inventory platform for enterprise-wide gains
How to leverage a market data inventory platform for enterprise-wide gainsHow to leverage a market data inventory platform for enterprise-wide gains
How to leverage a market data inventory platform for enterprise-wide gainsLeigh Hill
 
Four categories of entity data quality management
Four categories of entity data quality managementFour categories of entity data quality management
Four categories of entity data quality managementLeigh Hill
 
Webinar: Solving the problem of integrating beneficial ownership data with cl...
Webinar: Solving the problem of integrating beneficial ownership data with cl...Webinar: Solving the problem of integrating beneficial ownership data with cl...
Webinar: Solving the problem of integrating beneficial ownership data with cl...Leigh Hill
 
Hub16: Why Bespoke Supply Chain Analytics?
Hub16: Why Bespoke Supply Chain Analytics?Hub16: Why Bespoke Supply Chain Analytics?
Hub16: Why Bespoke Supply Chain Analytics?Anaplan
 
Implementing Agile Data Governance
Implementing Agile Data GovernanceImplementing Agile Data Governance
Implementing Agile Data GovernanceTami Flowers
 
Journey to analytics in the cloud
Journey to analytics in the cloudJourney to analytics in the cloud
Journey to analytics in the cloudSaama
 
World of Watson 2016: Journey to Cognitive Excellence - Harness the Force of ...
World of Watson 2016: Journey to Cognitive Excellence - Harness the Force of ...World of Watson 2016: Journey to Cognitive Excellence - Harness the Force of ...
World of Watson 2016: Journey to Cognitive Excellence - Harness the Force of ...Julie Severance
 
3 Steps for Measuring ROI of Data Quality for Data-Driven Marketers
3 Steps for Measuring ROI of Data Quality for Data-Driven Marketers3 Steps for Measuring ROI of Data Quality for Data-Driven Marketers
3 Steps for Measuring ROI of Data Quality for Data-Driven MarketersAlex Yastrebenetsky
 
Moving from data to insights: How to effectively drive business decisions & g...
Moving from data to insights: How to effectively drive business decisions & g...Moving from data to insights: How to effectively drive business decisions & g...
Moving from data to insights: How to effectively drive business decisions & g...Cloudera, Inc.
 
Kudu Forrester Webinar
Kudu Forrester WebinarKudu Forrester Webinar
Kudu Forrester WebinarCloudera, Inc.
 
Counting Your Chickens - Analytics for Small Business
Counting Your Chickens - Analytics for Small BusinessCounting Your Chickens - Analytics for Small Business
Counting Your Chickens - Analytics for Small BusinessMiiA Communications
 
Network of networks webinar v3 ac
Network of networks webinar v3 acNetwork of networks webinar v3 ac
Network of networks webinar v3 acTBRMarketing
 
Network of Networks - Slide Deck
Network of Networks - Slide DeckNetwork of Networks - Slide Deck
Network of Networks - Slide DeckLora Cecere
 
Best practice solutions for client lifecycle management
Best practice solutions for client lifecycle managementBest practice solutions for client lifecycle management
Best practice solutions for client lifecycle managementLeigh Hill
 
Get to grips with FRTB data and data management requirements
Get to grips with FRTB data and data management requirementsGet to grips with FRTB data and data management requirements
Get to grips with FRTB data and data management requirementsLeigh Hill
 
Predictive Analytics: From Insight to Action
Predictive Analytics: From Insight to ActionPredictive Analytics: From Insight to Action
Predictive Analytics: From Insight to ActionPhilippe Nemery
 
Preparing for Major Disruptions in Digital Asset Management
Preparing for Major Disruptions in Digital Asset ManagementPreparing for Major Disruptions in Digital Asset Management
Preparing for Major Disruptions in Digital Asset ManagementNuxeo
 
JU Analytics Day Presentation by Naveen Agarwal, Creative Analytics Solutions...
JU Analytics Day Presentation by Naveen Agarwal, Creative Analytics Solutions...JU Analytics Day Presentation by Naveen Agarwal, Creative Analytics Solutions...
JU Analytics Day Presentation by Naveen Agarwal, Creative Analytics Solutions...Naveen Agarwal
 
MT108 On the Edge of Eminence:When Will Services Transform the System?
MT108 On the Edge of Eminence:When Will Services Transform the System?MT108 On the Edge of Eminence:When Will Services Transform the System?
MT108 On the Edge of Eminence:When Will Services Transform the System?Dell EMC World
 

Ähnlich wie The art of implementing data lineage (20)

Approaches to data quality
Approaches to data qualityApproaches to data quality
Approaches to data quality
 
How to leverage a market data inventory platform for enterprise-wide gains
How to leverage a market data inventory platform for enterprise-wide gainsHow to leverage a market data inventory platform for enterprise-wide gains
How to leverage a market data inventory platform for enterprise-wide gains
 
Four categories of entity data quality management
Four categories of entity data quality managementFour categories of entity data quality management
Four categories of entity data quality management
 
Webinar: Solving the problem of integrating beneficial ownership data with cl...
Webinar: Solving the problem of integrating beneficial ownership data with cl...Webinar: Solving the problem of integrating beneficial ownership data with cl...
Webinar: Solving the problem of integrating beneficial ownership data with cl...
 
Hub16: Why Bespoke Supply Chain Analytics?
Hub16: Why Bespoke Supply Chain Analytics?Hub16: Why Bespoke Supply Chain Analytics?
Hub16: Why Bespoke Supply Chain Analytics?
 
Implementing Agile Data Governance
Implementing Agile Data GovernanceImplementing Agile Data Governance
Implementing Agile Data Governance
 
Journey to analytics in the cloud
Journey to analytics in the cloudJourney to analytics in the cloud
Journey to analytics in the cloud
 
World of Watson 2016: Journey to Cognitive Excellence - Harness the Force of ...
World of Watson 2016: Journey to Cognitive Excellence - Harness the Force of ...World of Watson 2016: Journey to Cognitive Excellence - Harness the Force of ...
World of Watson 2016: Journey to Cognitive Excellence - Harness the Force of ...
 
3 Steps for Measuring ROI of Data Quality for Data-Driven Marketers
3 Steps for Measuring ROI of Data Quality for Data-Driven Marketers3 Steps for Measuring ROI of Data Quality for Data-Driven Marketers
3 Steps for Measuring ROI of Data Quality for Data-Driven Marketers
 
Moving from data to insights: How to effectively drive business decisions & g...
Moving from data to insights: How to effectively drive business decisions & g...Moving from data to insights: How to effectively drive business decisions & g...
Moving from data to insights: How to effectively drive business decisions & g...
 
Kudu Forrester Webinar
Kudu Forrester WebinarKudu Forrester Webinar
Kudu Forrester Webinar
 
Counting Your Chickens - Analytics for Small Business
Counting Your Chickens - Analytics for Small BusinessCounting Your Chickens - Analytics for Small Business
Counting Your Chickens - Analytics for Small Business
 
Network of networks webinar v3 ac
Network of networks webinar v3 acNetwork of networks webinar v3 ac
Network of networks webinar v3 ac
 
Network of Networks - Slide Deck
Network of Networks - Slide DeckNetwork of Networks - Slide Deck
Network of Networks - Slide Deck
 
Best practice solutions for client lifecycle management
Best practice solutions for client lifecycle managementBest practice solutions for client lifecycle management
Best practice solutions for client lifecycle management
 
Get to grips with FRTB data and data management requirements
Get to grips with FRTB data and data management requirementsGet to grips with FRTB data and data management requirements
Get to grips with FRTB data and data management requirements
 
Predictive Analytics: From Insight to Action
Predictive Analytics: From Insight to ActionPredictive Analytics: From Insight to Action
Predictive Analytics: From Insight to Action
 
Preparing for Major Disruptions in Digital Asset Management
Preparing for Major Disruptions in Digital Asset ManagementPreparing for Major Disruptions in Digital Asset Management
Preparing for Major Disruptions in Digital Asset Management
 
JU Analytics Day Presentation by Naveen Agarwal, Creative Analytics Solutions...
JU Analytics Day Presentation by Naveen Agarwal, Creative Analytics Solutions...JU Analytics Day Presentation by Naveen Agarwal, Creative Analytics Solutions...
JU Analytics Day Presentation by Naveen Agarwal, Creative Analytics Solutions...
 
MT108 On the Edge of Eminence:When Will Services Transform the System?
MT108 On the Edge of Eminence:When Will Services Transform the System?MT108 On the Edge of Eminence:When Will Services Transform the System?
MT108 On the Edge of Eminence:When Will Services Transform the System?
 

Mehr von Leigh Hill

Data Science & Analytics – New approaches and capabilities for driving busine...
Data Science & Analytics – New approaches and capabilities for driving busine...Data Science & Analytics – New approaches and capabilities for driving busine...
Data Science & Analytics – New approaches and capabilities for driving busine...Leigh Hill
 
Data Standards – progress and case studies
Data Standards – progress and case studiesData Standards – progress and case studies
Data Standards – progress and case studiesLeigh Hill
 
How to run effective client onboarding and KYC processes
How to run effective client onboarding and KYC processesHow to run effective client onboarding and KYC processes
How to run effective client onboarding and KYC processesLeigh Hill
 
Adopting Entity Data Hierarchies to Address Holistic Risk Management
Adopting Entity Data Hierarchies to Address Holistic Risk ManagementAdopting Entity Data Hierarchies to Address Holistic Risk Management
Adopting Entity Data Hierarchies to Address Holistic Risk ManagementLeigh Hill
 
Best Practices for Integrated Regulatory Reporting Across Multiple Jurisdictions
Best Practices for Integrated Regulatory Reporting Across Multiple JurisdictionsBest Practices for Integrated Regulatory Reporting Across Multiple Jurisdictions
Best Practices for Integrated Regulatory Reporting Across Multiple JurisdictionsLeigh Hill
 
Last minute preparations for SFTR: What still needs to be done and are we ready?
Last minute preparations for SFTR: What still needs to be done and are we ready?Last minute preparations for SFTR: What still needs to be done and are we ready?
Last minute preparations for SFTR: What still needs to be done and are we ready?Leigh Hill
 
Data lineage – how to ensure you can deliver the right information, to the ri...
Data lineage – how to ensure you can deliver the right information, to the ri...Data lineage – how to ensure you can deliver the right information, to the ri...
Data lineage – how to ensure you can deliver the right information, to the ri...Leigh Hill
 
Client Experience and Onboarding For Transfer Agents: How to ensure you deliv...
Client Experience and Onboarding For Transfer Agents: How to ensure you deliv...Client Experience and Onboarding For Transfer Agents: How to ensure you deliv...
Client Experience and Onboarding For Transfer Agents: How to ensure you deliv...Leigh Hill
 
How to capture and manage complete and accurate customer data
How to capture and manage complete and accurate customer dataHow to capture and manage complete and accurate customer data
How to capture and manage complete and accurate customer dataLeigh Hill
 
Moving the trading technology stack to the cloud
Moving the trading technology stack to the cloudMoving the trading technology stack to the cloud
Moving the trading technology stack to the cloudLeigh Hill
 
FRTB: The time to get your data in order is now
FRTB: The time to get your data in order is nowFRTB: The time to get your data in order is now
FRTB: The time to get your data in order is nowLeigh Hill
 
How to exploit the opportunities of alternative data
How to exploit the opportunities of alternative dataHow to exploit the opportunities of alternative data
How to exploit the opportunities of alternative dataLeigh Hill
 
FRTB: Laying the groundwork for compliance 6 June 2019
FRTB: Laying the groundwork for compliance 6 June 2019FRTB: Laying the groundwork for compliance 6 June 2019
FRTB: Laying the groundwork for compliance 6 June 2019Leigh Hill
 
An update on data standards and global identifiers
An update on data standards and global identifiersAn update on data standards and global identifiers
An update on data standards and global identifiersLeigh Hill
 
Data lineage to drive compliance and as a business imperative
Data lineage to drive compliance and as a business imperativeData lineage to drive compliance and as a business imperative
Data lineage to drive compliance and as a business imperativeLeigh Hill
 
Operational Change Management Under Brexit
Operational Change Management Under BrexitOperational Change Management Under Brexit
Operational Change Management Under BrexitLeigh Hill
 
Balancing compliance and value in data management initiatives
Balancing compliance and value in data management initiativesBalancing compliance and value in data management initiatives
Balancing compliance and value in data management initiativesLeigh Hill
 
Regtech: How to digitalise the customer experience with KYC and AML Innovation
Regtech: How to digitalise the customer experience with KYC and AML InnovationRegtech: How to digitalise the customer experience with KYC and AML Innovation
Regtech: How to digitalise the customer experience with KYC and AML InnovationLeigh Hill
 
Fast, Cheap, State of the Art: Optimising Execution Quality using Cloud Data,...
Fast, Cheap, State of the Art: Optimising Execution Quality using Cloud Data,...Fast, Cheap, State of the Art: Optimising Execution Quality using Cloud Data,...
Fast, Cheap, State of the Art: Optimising Execution Quality using Cloud Data,...Leigh Hill
 
Balancing Regulatory Transparency with Data Protection
Balancing Regulatory Transparency with Data ProtectionBalancing Regulatory Transparency with Data Protection
Balancing Regulatory Transparency with Data ProtectionLeigh Hill
 

Mehr von Leigh Hill (20)

Data Science & Analytics – New approaches and capabilities for driving busine...
Data Science & Analytics – New approaches and capabilities for driving busine...Data Science & Analytics – New approaches and capabilities for driving busine...
Data Science & Analytics – New approaches and capabilities for driving busine...
 
Data Standards – progress and case studies
Data Standards – progress and case studiesData Standards – progress and case studies
Data Standards – progress and case studies
 
How to run effective client onboarding and KYC processes
How to run effective client onboarding and KYC processesHow to run effective client onboarding and KYC processes
How to run effective client onboarding and KYC processes
 
Adopting Entity Data Hierarchies to Address Holistic Risk Management
Adopting Entity Data Hierarchies to Address Holistic Risk ManagementAdopting Entity Data Hierarchies to Address Holistic Risk Management
Adopting Entity Data Hierarchies to Address Holistic Risk Management
 
Best Practices for Integrated Regulatory Reporting Across Multiple Jurisdictions
Best Practices for Integrated Regulatory Reporting Across Multiple JurisdictionsBest Practices for Integrated Regulatory Reporting Across Multiple Jurisdictions
Best Practices for Integrated Regulatory Reporting Across Multiple Jurisdictions
 
Last minute preparations for SFTR: What still needs to be done and are we ready?
Last minute preparations for SFTR: What still needs to be done and are we ready?Last minute preparations for SFTR: What still needs to be done and are we ready?
Last minute preparations for SFTR: What still needs to be done and are we ready?
 
Data lineage – how to ensure you can deliver the right information, to the ri...
Data lineage – how to ensure you can deliver the right information, to the ri...Data lineage – how to ensure you can deliver the right information, to the ri...
Data lineage – how to ensure you can deliver the right information, to the ri...
 
Client Experience and Onboarding For Transfer Agents: How to ensure you deliv...
Client Experience and Onboarding For Transfer Agents: How to ensure you deliv...Client Experience and Onboarding For Transfer Agents: How to ensure you deliv...
Client Experience and Onboarding For Transfer Agents: How to ensure you deliv...
 
How to capture and manage complete and accurate customer data
How to capture and manage complete and accurate customer dataHow to capture and manage complete and accurate customer data
How to capture and manage complete and accurate customer data
 
Moving the trading technology stack to the cloud
Moving the trading technology stack to the cloudMoving the trading technology stack to the cloud
Moving the trading technology stack to the cloud
 
FRTB: The time to get your data in order is now
FRTB: The time to get your data in order is nowFRTB: The time to get your data in order is now
FRTB: The time to get your data in order is now
 
How to exploit the opportunities of alternative data
How to exploit the opportunities of alternative dataHow to exploit the opportunities of alternative data
How to exploit the opportunities of alternative data
 
FRTB: Laying the groundwork for compliance 6 June 2019
FRTB: Laying the groundwork for compliance 6 June 2019FRTB: Laying the groundwork for compliance 6 June 2019
FRTB: Laying the groundwork for compliance 6 June 2019
 
An update on data standards and global identifiers
An update on data standards and global identifiersAn update on data standards and global identifiers
An update on data standards and global identifiers
 
Data lineage to drive compliance and as a business imperative
Data lineage to drive compliance and as a business imperativeData lineage to drive compliance and as a business imperative
Data lineage to drive compliance and as a business imperative
 
Operational Change Management Under Brexit
Operational Change Management Under BrexitOperational Change Management Under Brexit
Operational Change Management Under Brexit
 
Balancing compliance and value in data management initiatives
Balancing compliance and value in data management initiativesBalancing compliance and value in data management initiatives
Balancing compliance and value in data management initiatives
 
Regtech: How to digitalise the customer experience with KYC and AML Innovation
Regtech: How to digitalise the customer experience with KYC and AML InnovationRegtech: How to digitalise the customer experience with KYC and AML Innovation
Regtech: How to digitalise the customer experience with KYC and AML Innovation
 
Fast, Cheap, State of the Art: Optimising Execution Quality using Cloud Data,...
Fast, Cheap, State of the Art: Optimising Execution Quality using Cloud Data,...Fast, Cheap, State of the Art: Optimising Execution Quality using Cloud Data,...
Fast, Cheap, State of the Art: Optimising Execution Quality using Cloud Data,...
 
Balancing Regulatory Transparency with Data Protection
Balancing Regulatory Transparency with Data ProtectionBalancing Regulatory Transparency with Data Protection
Balancing Regulatory Transparency with Data Protection
 

Kürzlich hochgeladen

GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 

Kürzlich hochgeladen (20)

GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 

The art of implementing data lineage

  • 1. FROM DataManagementReview.comSeptember 29, 2016 The art of implementing data lineage The webinar will start soon Check out other upcoming webinars, white papers, blogs and events at www.DataManagementReview.com If you’re a vendor looking for high quality content to help articulate your message, take a look at www.a- teamgroup.com. Or get in touch: 020 8090 2055 / theteam@a-teamgroup.com
  • 2. FROM DataManagementReview.comSeptember 29, 2016 Welcome to A-Team Group’s webinar: The art of implementing data lineage
  • 4. FROM DataManagementReview.comSeptember 29, 2016 Panel Member: Jesse Canada*, Vice President of Business Metadata, Rules, and Reference Data Management, Citizens Bank Areas of Expertise: • Defining innovative metadata solutions for proficient problem solving, demonstrating value added business results, and supporting the enterprise programme • Integrating metadata into day-to-day business processes by changing attitudes and behaviours related to data use and understanding • Identifying metadata processes for Hadoop and Big Insights to ensure seamless data usability for stakeholders * Any comments made by Jesse Canada on the webinar are her own personal views and not those of Citizens Bank
  • 5. FROM DataManagementReview.comSeptember 29, 2016 Panel Member: Sue Habas, Vice President, Strategic Technologies, ASG Areas of Expertise: • Worked to structure and drive enterprise metadata/data governance programmes • 18 years’ experience working with metadata, both client and customer side • Responsible for launching and guiding ASG’s Enterprise Data Intelligence solutions • Vertical experience including financial, insurance, healthcare, manufacturing and e-commerce
  • 6. FROM DataManagementReview.comSeptember 29, 2016 Panel Member: Yetkin Ozkucur, Global Practice Vice President for Data Intelligence, ASG Areas of Expertise: • Worked to structure and drive enterprise metadata/data governance programmes • 15 years’ experience working with metadata • Designed and delivered many projects with a wide range of clients including financial, insurance, healthcare, manufacturing and e-commerce • Responsible for the delivery of the ASG Enterprise Data Intelligence solution
  • 7. FROM DataManagementReview.comSeptember 29, 2016 What exactly is meant by data lineage Key business use cases for data lineage Client projects in the banking sector Securing buy-in for implementation projects Milestones to reach successful implementation How firms are using data lineage to respond to enquiries Advice on approaches to tracking data lineage A 10-step process to implementing data lineage Talking Points
  • 8. FROM DataManagementReview.comSeptember 29, 2016 Can you give us a definition of data lineage as it applies to data management?
  • 9. FROM DataManagementReview.comSeptember 29, 2016 What is data lineage?  A critical supply chain App-File-Field Transform Rule DB-Tab-Col Calculation Rule Universe- Rep-Field Data Supply Chain Customer/Patient/Event Business Terms Policies Critical Data Elements Business Traceability E2E Data Driven Lineage VerticalBusinessContext Driven
  • 10. FROM DataManagementReview.comSeptember 29, 2016 The 5 W’s of Data Lineage  Where and how data lineage  Who is using the data?  What does it mean (data dictionary/glossary)?  Where does it exist and where did it come from?  When was it captured and how did it change over time?  How is it being used and how is it related? Backward Lineage Forward Lineage Where Lineage • What is the Source? • Who is the Application Owner? • What is the Quality? How Lineage • Where are my CDE’s going? • How is data being Transformed? • What reports use them?
  • 11. FROM DataManagementReview.comSeptember 29, 2016 Can you explain some of the key use cases for getting data lineage right?
  • 12. FROM DataManagementReview.comSeptember 29, 2016 Can you describe client projects you’ve been working on to address data lineage?
  • 13. FROM DataManagementReview.comSeptember 29, 2016 How do clients secure buy-in across their organisations for projects and budget?
  • 14. FROM DataManagementReview.comSeptember 29, 2016 What were the benefits you used to secure that buy-in?
  • 15. FROM DataManagementReview.comSeptember 29, 2016 What objections did you meet and how did you address them?
  • 16. FROM DataManagementReview.comSeptember 29, 2016 What are the key milestones in a project plan to reach successful implementation?
  • 17. FROM DataManagementReview.comSeptember 29, 2016 How long do projects typically take and what are the hold ups or complications that firms experience?
  • 18. FROM DataManagementReview.comSeptember 29, 2016 What does a successful implementation enable an organisation to do that it couldn’t before?
  • 19. FROM DataManagementReview.comSeptember 29, 2016 A couple of scenarios in which an organisation would need to track data lineage to respond to a regulatory or internal enquiry?
  • 20. FROM DataManagementReview.comSeptember 29, 2016 What advice would you give to organisations figuring out their approach to tracking data lineage?
  • 21. FROM DataManagementReview.comSeptember 29, 2016 Your 10-Step Process to Implementing Data Lineage Below is a checklist of the key elements you should use when planning any data lineage project. Preparation Phase 1. Always begin with the end in mind. Determine your goals, taking into account your regulatory requirements, the business critical reports you need, and the critical insights you’re seeking 2. Define your user types, which could include: risk analysts, auditors, business stewards, BI analysts, developers/IT or enterprise architects etc 3. Prepare for your data lineage project by identifying the critical data and source systems, creating data architecture diagrams, identifying application owners 4. Prepare manual baseline, describe the effort and quality of creating lineage manually
  • 22. FROM DataManagementReview.comSeptember 29, 2016 Your 10-Step Process to Implementing Data Lineage Below is a checklist of the key elements you should use when planning any data lineage project. Execution Phase 1. Create the business terms, definitions and controls that surround the data and link it to the critical data 2. Use a tool to automate the pull of the data dictionary schema’s and ETL code in order to quickly and accurately find the true source of information 3. Validate the lineage. Identify gaps and remediate 4. Roll out to end users. Visualization of the lineage. Provide views, exports, and embed lineage in other tools
  • 23. FROM DataManagementReview.comSeptember 29, 2016 Your 10-Step Process to Implementing Data Lineage Below is a checklist of the key elements you should use when planning any data lineage project. Subscribe to Survive 1. Automatic change detection and notification 2. Assign responsible users to be notified of any change to the critical lineage supply chain This approach allows you to build out a reverse tracing methodology and base line for comprehensive and accurate end-to-end data lineage.
  • 24. FROM DataManagementReview.comSeptember 29, 2016 Thank you to our sponsor Contact: Sue Habas VP of Strategic Technologies-Data Intelligence, ASG Email: sue.habas@asg.com Website: www.asg.com/intelligence
  • 25. FROM DataManagementReview.comSeptember 29, 2016 October 6th Data Management Summit London November 17th Data Management Summit New York Upcoming A-Team Group Events Visit DataManagementReview.com/events
  • 26. FROM DataManagementReview.comSeptember 29, 2016 Upcoming A-Team Group Webinars October 11th Practical approaches to improving entity data quality October 13th Integrating beneficial ownership data with client onboarding and KYC October 18th GDPR: How to build a data protection framework Visit webinars section of DataManagementReview.com
  • 27. FROM DataManagementReview.comSeptember 29, 2016 A-Team Group Handbook Series Visit the data management handbooks section of DataManagementReview.com
  • 28. FROM DataManagementReview.comSeptember 29, 2016 Please take the time to complete our post webinar survey We will notify you when the webinar recording is available Thank you for joining us

Hinweis der Redaktion

  1. Point of talk track – if you are competing with Collibra they only do the top half well… ------------------------------------------------------------------------------------------------------- Vertical/horizontal Horizontal – captures the e2e data movement Including transformation rules, how data is formatted & used Vertical – driven from business context Automated – represents precisely on how it exists in the data landscape today