SlideShare a Scribd company logo
June 2008 Volume 3 Number 2                                                                                                              www.irdonline.com

Metadata may not be the best word to use to try to get senior management excited about
reference data projects. But metadata management is a vital part of enterprise data management
(EDM), and as EDM projects are now maturing, metadata is swiftly moving up the agenda.
Tine Thoresen explores the best strategies for implementing metadata tools and systems


                     Getting Meta All the Time
John Carroll, who recently retired from Merrill          says Serenita. It is often difficult to improve data   research. When assessing applications, firms
Lynch, had been working in the same role for 10          quality if data definitions are all over the place.    should look for harvesting population utilities,
years. He was initially hired to build on the vision     Everyone needs to be on the same page—both to          according to Carty. He says most customers will be
of an enterprise data repository. But this type          improve reporting and consolidate silos.               able to automatically load 80% of definitions into
of project is not done overnight. Carroll was still         To succeed, firms simply need to identify the       the system, while 20% will typically be manually
working on enhancing the system 10 years on.             best strategy to overcome challenges such as           inputted. So when reviewing applications, firms
This is the reality of reference data initiatives—the    structuring the data, increasing automation,           should be shooting for that 80%.
projects often seem never-ending. Yet, many enter-       keeping the content current and managing the              And standards can offer better integration
prise data management projects are now entering          refresh rate. But this is obviously not that simple    opportunities. Greg Keller, vice-president, product
a new phase—the metadata management phase.               when there is little public information on how to      management at metadata management product
Firms are starting to focus more on standardizing        get there for financial institutions.                  vendor Embarcadero Technologies, advises firms
and centralizing ‘data about the data.’                     So, as with every other data problem, can firms     to move on if the tool does not speak ‘standards.’
   Peter Serenita, chief data officer at JP Morgan       turn to vendors for help? Honore, who focuses on       “There is no panacea, but the only way to collect,
Chase, says the types of reference data technology       financial services, says the projects he has seen      refine, integrate and communicate this data (about
he expects firms to invest in this year are meta-        have been internal developments, and he does not       data) is to ensure it can bi-directionally integrate
data management tools. “Firms will invest in the         know of anyone who is using off-the-shelf tools.       via open standards such as the OMG’s [object
ability to define data using data management                There are, however, many vendors targeting the      management group] set of data interchange stan-
tools so that this information is not buried in          metadata management space across industries.           dards,” he says, adding that OMG’s forthcoming
code,” he says (Inside Reference Data, Reference         Stu Carty, founder and metadata solutions expert       information management metamodel (IMM)
Data Technology Special Report, May 2008).               at Gavilian Research, says there are 17 vendors        implementation is rooted in universally defining
   But so far there have not been many metadata          offering metadata solutions. The providers can be      storage for data standards.
success stories in the financial industry. These         divided into two groups—one group offers inde-            Keller also says firms should choose model-
types of projects can require a lot of resources, as     pendent metadata management tools that can be          driven products—“critical to be able to express
a large portion of the work tends to be taxonomic.       bought separately and the other offers metadata        complex business rules in a manner that can
Adam Honore, senior analyst at Aite Group, says          management tools bundled into a tool suite.            abstract the information in a graphical format”—
some of the larger firms are currently working on           The third option, which Honore mentioned, is        and products that embrace logical and physical
these projects, but that it is probably too early to     building systems in-house. Carty says most firms       data modeling as a means to express the core
talk about successes.                                    might start with internal developments, mainly         underlying metadata.
   Yet, this is not to say that metadata management      using Excel, but since vendors are getting better         In fact, ease of use of the application is vital to
tools cannot add tremendous value. “By providing         and better, off-the-shelf solutions are becoming       review when assessing metadata tools. This might
visibility to the data definitions, the firm’s ability   more viable. Metadata management solutions             sound very basic, but it is particularly important
to manage the data increases exponentially,”             are database applications that can be filled with      in this market, where some tools have tradition-
                                                         descriptions and relationships. Carty says Google      ally had a poor reputation. Carty says some prod-
                                                         is an example of a metadata tool—probably the          ucts are difficult to use and implement, but the
                                                         biggest one.                                           best vendors today recognize that problem, are
                                                                                                                focusing on making it easier for customers and
                                                         Finding the Right Product                              are leveraging new technology.
                                                         Although Google might help firms find informa-            So the area is worth exploring. Some firms have
                                                         tion, selecting vendors requires more thorough         seen early successes, according to Keller, who has
                                                                                                                witnessed some “well-implemented metadata
                                                                                                                management programs in large household banks
                                                           “The only way to collect, refine,                    both in the UK and US.” In most cases, the proj-
                                                           integrate and communicate this                       ects revolved around data rationalisation, refining
                                                           data (about data) is to ensure it                    and documenting the metadata values of core
                                                                                                                business attributes in an effort to point to live data
                                                           can bi-directionally integrate via                   in order to continually assess quality, he says.
                                                                   open standards”                                 And as metadata management tools mature,
                                                               Greg Keller, Embarcadero Technologies            the industry is set to see more of these projects
                                                                                                                succeed and materialize.

 © 2008 Incisive Media Investments. All rights reserved. Used by permission. First published in IRD June 2008.

More Related Content

What's hot

Mike2.0 Information Governance Overview
Mike2.0 Information Governance OverviewMike2.0 Information Governance Overview
Mike2.0 Information Governance Overview
sean.mcclowry
 
Overcoming Big Data Challenges on System z
Overcoming Big Data Challenges on System zOvercoming Big Data Challenges on System z
Overcoming Big Data Challenges on System z
CA Technologies
 
Data Architecture Strategies: Data Architecture for Digital Transformation
Data Architecture Strategies: Data Architecture for Digital TransformationData Architecture Strategies: Data Architecture for Digital Transformation
Data Architecture Strategies: Data Architecture for Digital Transformation
DATAVERSITY
 
Demystifying Big Data for Associations
Demystifying Big Data for AssociationsDemystifying Big Data for Associations
Demystifying Big Data for Associations
Patrick Dorsey
 
CIO Applications Magazine Names Bardess One of the Top 25 ML Solution Providers
CIO Applications Magazine Names Bardess One of the Top 25 ML Solution ProvidersCIO Applications Magazine Names Bardess One of the Top 25 ML Solution Providers
CIO Applications Magazine Names Bardess One of the Top 25 ML Solution Providers
chrishems1
 
Business & Decision MDM Summit (english version)
Business & Decision MDM Summit (english version)Business & Decision MDM Summit (english version)
Business & Decision MDM Summit (english version)
Jean-Michel Franco
 
Analyst field reports on top 20 MDM and Data Governance implementation partne...
Analyst field reports on top 20 MDM and Data Governance implementation partne...Analyst field reports on top 20 MDM and Data Governance implementation partne...
Analyst field reports on top 20 MDM and Data Governance implementation partne...
Aaron Zornes
 
Modernizing the Enterprise Monolith: EQengineered Consulting Green Paper
Modernizing the Enterprise Monolith: EQengineered Consulting Green PaperModernizing the Enterprise Monolith: EQengineered Consulting Green Paper
Modernizing the Enterprise Monolith: EQengineered Consulting Green Paper
Mark Hewitt
 
O'Reilly ebook: Machine Learning at Enterprise Scale | Qubole
O'Reilly ebook: Machine Learning at Enterprise Scale | QuboleO'Reilly ebook: Machine Learning at Enterprise Scale | Qubole
O'Reilly ebook: Machine Learning at Enterprise Scale | Qubole
Vasu S
 
Where the Warehouse Ends: A New Age of Information Access
Where the Warehouse Ends: A New Age of Information AccessWhere the Warehouse Ends: A New Age of Information Access
Where the Warehouse Ends: A New Age of Information Access
Inside Analysis
 
Assignment 3 - Big Data - Ed.02
Assignment 3 - Big Data - Ed.02Assignment 3 - Big Data - Ed.02
Assignment 3 - Big Data - Ed.02
Hosein Nafisi
 
The Value of a Smarter Data Centre
The Value of a Smarter Data CentreThe Value of a Smarter Data Centre
The Value of a Smarter Data Centre
None
 
The New Enterprise Data Platform
The New Enterprise Data PlatformThe New Enterprise Data Platform
The New Enterprise Data Platform
Krishnan Parasuraman
 
Virtual Data Steward: Data Management 3.0
Virtual Data Steward: Data Management 3.0Virtual Data Steward: Data Management 3.0
Virtual Data Steward: Data Management 3.0
CrowdFlower
 
Big Data Forum - Phoenix
Big Data Forum - PhoenixBig Data Forum - Phoenix
Big Data Forum - Phoenix
Krishnan Parasuraman
 
Data Discovery for Big Big Insights - Tableau Webinar Slides
Data Discovery for Big Big Insights - Tableau Webinar SlidesData Discovery for Big Big Insights - Tableau Webinar Slides
Data Discovery for Big Big Insights - Tableau Webinar Slides
Fitzgerald Analytics, Inc.
 
A Glimpse into Software Defined Data Center
A Glimpse into Software Defined Data CenterA Glimpse into Software Defined Data Center
A Glimpse into Software Defined Data Center
Fung Ping
 

What's hot (17)

Mike2.0 Information Governance Overview
Mike2.0 Information Governance OverviewMike2.0 Information Governance Overview
Mike2.0 Information Governance Overview
 
Overcoming Big Data Challenges on System z
Overcoming Big Data Challenges on System zOvercoming Big Data Challenges on System z
Overcoming Big Data Challenges on System z
 
Data Architecture Strategies: Data Architecture for Digital Transformation
Data Architecture Strategies: Data Architecture for Digital TransformationData Architecture Strategies: Data Architecture for Digital Transformation
Data Architecture Strategies: Data Architecture for Digital Transformation
 
Demystifying Big Data for Associations
Demystifying Big Data for AssociationsDemystifying Big Data for Associations
Demystifying Big Data for Associations
 
CIO Applications Magazine Names Bardess One of the Top 25 ML Solution Providers
CIO Applications Magazine Names Bardess One of the Top 25 ML Solution ProvidersCIO Applications Magazine Names Bardess One of the Top 25 ML Solution Providers
CIO Applications Magazine Names Bardess One of the Top 25 ML Solution Providers
 
Business & Decision MDM Summit (english version)
Business & Decision MDM Summit (english version)Business & Decision MDM Summit (english version)
Business & Decision MDM Summit (english version)
 
Analyst field reports on top 20 MDM and Data Governance implementation partne...
Analyst field reports on top 20 MDM and Data Governance implementation partne...Analyst field reports on top 20 MDM and Data Governance implementation partne...
Analyst field reports on top 20 MDM and Data Governance implementation partne...
 
Modernizing the Enterprise Monolith: EQengineered Consulting Green Paper
Modernizing the Enterprise Monolith: EQengineered Consulting Green PaperModernizing the Enterprise Monolith: EQengineered Consulting Green Paper
Modernizing the Enterprise Monolith: EQengineered Consulting Green Paper
 
O'Reilly ebook: Machine Learning at Enterprise Scale | Qubole
O'Reilly ebook: Machine Learning at Enterprise Scale | QuboleO'Reilly ebook: Machine Learning at Enterprise Scale | Qubole
O'Reilly ebook: Machine Learning at Enterprise Scale | Qubole
 
Where the Warehouse Ends: A New Age of Information Access
Where the Warehouse Ends: A New Age of Information AccessWhere the Warehouse Ends: A New Age of Information Access
Where the Warehouse Ends: A New Age of Information Access
 
Assignment 3 - Big Data - Ed.02
Assignment 3 - Big Data - Ed.02Assignment 3 - Big Data - Ed.02
Assignment 3 - Big Data - Ed.02
 
The Value of a Smarter Data Centre
The Value of a Smarter Data CentreThe Value of a Smarter Data Centre
The Value of a Smarter Data Centre
 
The New Enterprise Data Platform
The New Enterprise Data PlatformThe New Enterprise Data Platform
The New Enterprise Data Platform
 
Virtual Data Steward: Data Management 3.0
Virtual Data Steward: Data Management 3.0Virtual Data Steward: Data Management 3.0
Virtual Data Steward: Data Management 3.0
 
Big Data Forum - Phoenix
Big Data Forum - PhoenixBig Data Forum - Phoenix
Big Data Forum - Phoenix
 
Data Discovery for Big Big Insights - Tableau Webinar Slides
Data Discovery for Big Big Insights - Tableau Webinar SlidesData Discovery for Big Big Insights - Tableau Webinar Slides
Data Discovery for Big Big Insights - Tableau Webinar Slides
 
A Glimpse into Software Defined Data Center
A Glimpse into Software Defined Data CenterA Glimpse into Software Defined Data Center
A Glimpse into Software Defined Data Center
 

Similar to Getting Enterprise Meta Data All the Time

Business process based analytics
Business process based analyticsBusiness process based analytics
Business process based analytics
Korea Advanced Institute of Science and Technology
 
Running head Database and Data Warehousing design1Database and.docx
Running head Database and Data Warehousing design1Database and.docxRunning head Database and Data Warehousing design1Database and.docx
Running head Database and Data Warehousing design1Database and.docx
healdkathaleen
 
Running head Database and Data Warehousing design1Database and.docx
Running head Database and Data Warehousing design1Database and.docxRunning head Database and Data Warehousing design1Database and.docx
Running head Database and Data Warehousing design1Database and.docx
todd271
 
Pivotal CRM - Analytics
Pivotal CRM - Analytics Pivotal CRM - Analytics
Pivotal CRM - Analytics
Pivotal CRM
 
Making advanced analytics work for you
Making advanced analytics work for youMaking advanced analytics work for you
Making advanced analytics work for you
Ayushi Verma
 
3 Keys To Successful Master Data Management - Final Presentation
3 Keys To Successful Master Data Management - Final Presentation3 Keys To Successful Master Data Management - Final Presentation
3 Keys To Successful Master Data Management - Final Presentation
James Chi
 
DAMA Australia: How to Choose a Data Management Tool
DAMA Australia: How to Choose a Data Management ToolDAMA Australia: How to Choose a Data Management Tool
DAMA Australia: How to Choose a Data Management Tool
Precisely
 
Using Big Data Smarter Decision Making
Using Big Data Smarter Decision MakingUsing Big Data Smarter Decision Making
Using Big Data Smarter Decision Making
IBM India Smarter Computing
 
Top Trends & Predictions That Will Drive Data Science in 2022.pdf
Top Trends & Predictions That Will Drive Data Science in 2022.pdfTop Trends & Predictions That Will Drive Data Science in 2022.pdf
Top Trends & Predictions That Will Drive Data Science in 2022.pdf
Data Science Council of America
 
2016 Strata Conference New York - Vendor Briefings
2016 Strata Conference New York - Vendor Briefings2016 Strata Conference New York - Vendor Briefings
2016 Strata Conference New York - Vendor Briefings
Digital Enterprise Journal
 
2012 Data Acquisition Report
2012 Data Acquisition Report 2012 Data Acquisition Report
2012 Data Acquisition Report
Oceanos
 
Modernizing And Advancing Info Magagement
Modernizing And Advancing Info MagagementModernizing And Advancing Info Magagement
Modernizing And Advancing Info Magagement
William McKnight
 
Article Evaluation 4
Article Evaluation 4Article Evaluation 4
Article Evaluation 4
AnshumanRaina
 
Developing A Universal Approach to Cleansing Customer and Product Data
Developing A Universal Approach to Cleansing Customer and Product DataDeveloping A Universal Approach to Cleansing Customer and Product Data
Developing A Universal Approach to Cleansing Customer and Product Data
FindWhitePapers
 
Ciber Master Data Management
Ciber Master Data ManagementCiber Master Data Management
Ciber Master Data Management
spearcy
 
Bidata
BidataBidata
Bidata
Tamojit Das
 
Smarter Big Data Strategies
Smarter Big Data StrategiesSmarter Big Data Strategies
Smarter Big Data Strategies
Infosys
 
Overview of mit sloan case study on ge data and analytics initiative titled g...
Overview of mit sloan case study on ge data and analytics initiative titled g...Overview of mit sloan case study on ge data and analytics initiative titled g...
Overview of mit sloan case study on ge data and analytics initiative titled g...
Gregg Barrett
 
MDM AS A METHODOLOGY
MDM AS A METHODOLOGYMDM AS A METHODOLOGY
MDM AS A METHODOLOGY
Janet Wetter
 
Getting down to business on Big Data analytics
Getting down to business on Big Data analyticsGetting down to business on Big Data analytics
Getting down to business on Big Data analytics
The Marketing Distillery
 

Similar to Getting Enterprise Meta Data All the Time (20)

Business process based analytics
Business process based analyticsBusiness process based analytics
Business process based analytics
 
Running head Database and Data Warehousing design1Database and.docx
Running head Database and Data Warehousing design1Database and.docxRunning head Database and Data Warehousing design1Database and.docx
Running head Database and Data Warehousing design1Database and.docx
 
Running head Database and Data Warehousing design1Database and.docx
Running head Database and Data Warehousing design1Database and.docxRunning head Database and Data Warehousing design1Database and.docx
Running head Database and Data Warehousing design1Database and.docx
 
Pivotal CRM - Analytics
Pivotal CRM - Analytics Pivotal CRM - Analytics
Pivotal CRM - Analytics
 
Making advanced analytics work for you
Making advanced analytics work for youMaking advanced analytics work for you
Making advanced analytics work for you
 
3 Keys To Successful Master Data Management - Final Presentation
3 Keys To Successful Master Data Management - Final Presentation3 Keys To Successful Master Data Management - Final Presentation
3 Keys To Successful Master Data Management - Final Presentation
 
DAMA Australia: How to Choose a Data Management Tool
DAMA Australia: How to Choose a Data Management ToolDAMA Australia: How to Choose a Data Management Tool
DAMA Australia: How to Choose a Data Management Tool
 
Using Big Data Smarter Decision Making
Using Big Data Smarter Decision MakingUsing Big Data Smarter Decision Making
Using Big Data Smarter Decision Making
 
Top Trends & Predictions That Will Drive Data Science in 2022.pdf
Top Trends & Predictions That Will Drive Data Science in 2022.pdfTop Trends & Predictions That Will Drive Data Science in 2022.pdf
Top Trends & Predictions That Will Drive Data Science in 2022.pdf
 
2016 Strata Conference New York - Vendor Briefings
2016 Strata Conference New York - Vendor Briefings2016 Strata Conference New York - Vendor Briefings
2016 Strata Conference New York - Vendor Briefings
 
2012 Data Acquisition Report
2012 Data Acquisition Report 2012 Data Acquisition Report
2012 Data Acquisition Report
 
Modernizing And Advancing Info Magagement
Modernizing And Advancing Info MagagementModernizing And Advancing Info Magagement
Modernizing And Advancing Info Magagement
 
Article Evaluation 4
Article Evaluation 4Article Evaluation 4
Article Evaluation 4
 
Developing A Universal Approach to Cleansing Customer and Product Data
Developing A Universal Approach to Cleansing Customer and Product DataDeveloping A Universal Approach to Cleansing Customer and Product Data
Developing A Universal Approach to Cleansing Customer and Product Data
 
Ciber Master Data Management
Ciber Master Data ManagementCiber Master Data Management
Ciber Master Data Management
 
Bidata
BidataBidata
Bidata
 
Smarter Big Data Strategies
Smarter Big Data StrategiesSmarter Big Data Strategies
Smarter Big Data Strategies
 
Overview of mit sloan case study on ge data and analytics initiative titled g...
Overview of mit sloan case study on ge data and analytics initiative titled g...Overview of mit sloan case study on ge data and analytics initiative titled g...
Overview of mit sloan case study on ge data and analytics initiative titled g...
 
MDM AS A METHODOLOGY
MDM AS A METHODOLOGYMDM AS A METHODOLOGY
MDM AS A METHODOLOGY
 
Getting down to business on Big Data analytics
Getting down to business on Big Data analyticsGetting down to business on Big Data analytics
Getting down to business on Big Data analytics
 

More from Embarcadero Technologies

PyTorch for Delphi - Python Data Sciences Libraries.pdf
PyTorch for Delphi - Python Data Sciences Libraries.pdfPyTorch for Delphi - Python Data Sciences Libraries.pdf
PyTorch for Delphi - Python Data Sciences Libraries.pdf
Embarcadero Technologies
 
Android on Windows 11 - A Developer's Perspective (Windows Subsystem For Andr...
Android on Windows 11 - A Developer's Perspective (Windows Subsystem For Andr...Android on Windows 11 - A Developer's Perspective (Windows Subsystem For Andr...
Android on Windows 11 - A Developer's Perspective (Windows Subsystem For Andr...
Embarcadero Technologies
 
Linux GUI Applications on Windows Subsystem for Linux
Linux GUI Applications on Windows Subsystem for LinuxLinux GUI Applications on Windows Subsystem for Linux
Linux GUI Applications on Windows Subsystem for Linux
Embarcadero Technologies
 
Python on Android with Delphi FMX - The Cross Platform GUI Framework
Python on Android with Delphi FMX - The Cross Platform GUI Framework Python on Android with Delphi FMX - The Cross Platform GUI Framework
Python on Android with Delphi FMX - The Cross Platform GUI Framework
Embarcadero Technologies
 
Introduction to Python GUI development with Delphi for Python - Part 1: Del...
Introduction to Python GUI development with Delphi for Python - Part 1:   Del...Introduction to Python GUI development with Delphi for Python - Part 1:   Del...
Introduction to Python GUI development with Delphi for Python - Part 1: Del...
Embarcadero Technologies
 
FMXLinux Introduction - Delphi's FireMonkey for Linux
FMXLinux Introduction - Delphi's FireMonkey for LinuxFMXLinux Introduction - Delphi's FireMonkey for Linux
FMXLinux Introduction - Delphi's FireMonkey for Linux
Embarcadero Technologies
 
Python for Delphi Developers - Part 2
Python for Delphi Developers - Part 2Python for Delphi Developers - Part 2
Python for Delphi Developers - Part 2
Embarcadero Technologies
 
Python for Delphi Developers - Part 1 Introduction
Python for Delphi Developers - Part 1 IntroductionPython for Delphi Developers - Part 1 Introduction
Python for Delphi Developers - Part 1 Introduction
Embarcadero Technologies
 
RAD Industrial Automation, Labs, and Instrumentation
RAD Industrial Automation, Labs, and InstrumentationRAD Industrial Automation, Labs, and Instrumentation
RAD Industrial Automation, Labs, and Instrumentation
Embarcadero Technologies
 
Embeddable Databases for Mobile Apps: Stress-Free Solutions with InterBase
Embeddable Databases for Mobile Apps: Stress-Free Solutions with InterBaseEmbeddable Databases for Mobile Apps: Stress-Free Solutions with InterBase
Embeddable Databases for Mobile Apps: Stress-Free Solutions with InterBase
Embarcadero Technologies
 
Rad Server Industry Template - Connected Nurses Station - Setup Document
Rad Server Industry Template - Connected Nurses Station - Setup DocumentRad Server Industry Template - Connected Nurses Station - Setup Document
Rad Server Industry Template - Connected Nurses Station - Setup Document
Embarcadero Technologies
 
TMS Google Mapping Components
TMS Google Mapping ComponentsTMS Google Mapping Components
TMS Google Mapping Components
Embarcadero Technologies
 
Move Desktop Apps to the Cloud - RollApp & Embarcadero webinar
Move Desktop Apps to the Cloud - RollApp & Embarcadero webinarMove Desktop Apps to the Cloud - RollApp & Embarcadero webinar
Move Desktop Apps to the Cloud - RollApp & Embarcadero webinar
Embarcadero Technologies
 
Useful C++ Features You Should be Using
Useful C++ Features You Should be UsingUseful C++ Features You Should be Using
Useful C++ Features You Should be Using
Embarcadero Technologies
 
Getting Started Building Mobile Applications for iOS and Android
Getting Started Building Mobile Applications for iOS and AndroidGetting Started Building Mobile Applications for iOS and Android
Getting Started Building Mobile Applications for iOS and Android
Embarcadero Technologies
 
Embarcadero RAD server Launch Webinar
Embarcadero RAD server Launch WebinarEmbarcadero RAD server Launch Webinar
Embarcadero RAD server Launch Webinar
Embarcadero Technologies
 
ER/Studio 2016: Build a Business-Driven Data Architecture
ER/Studio 2016: Build a Business-Driven Data ArchitectureER/Studio 2016: Build a Business-Driven Data Architecture
ER/Studio 2016: Build a Business-Driven Data Architecture
Embarcadero Technologies
 
The Secrets of SQL Server: Database Worst Practices
The Secrets of SQL Server: Database Worst PracticesThe Secrets of SQL Server: Database Worst Practices
The Secrets of SQL Server: Database Worst Practices
Embarcadero Technologies
 
Driving Business Value Through Agile Data Assets
Driving Business Value Through Agile Data AssetsDriving Business Value Through Agile Data Assets
Driving Business Value Through Agile Data Assets
Embarcadero Technologies
 
Troubleshooting Plan Changes with Query Store in SQL Server 2016
Troubleshooting Plan Changes with Query Store in SQL Server 2016Troubleshooting Plan Changes with Query Store in SQL Server 2016
Troubleshooting Plan Changes with Query Store in SQL Server 2016
Embarcadero Technologies
 

More from Embarcadero Technologies (20)

PyTorch for Delphi - Python Data Sciences Libraries.pdf
PyTorch for Delphi - Python Data Sciences Libraries.pdfPyTorch for Delphi - Python Data Sciences Libraries.pdf
PyTorch for Delphi - Python Data Sciences Libraries.pdf
 
Android on Windows 11 - A Developer's Perspective (Windows Subsystem For Andr...
Android on Windows 11 - A Developer's Perspective (Windows Subsystem For Andr...Android on Windows 11 - A Developer's Perspective (Windows Subsystem For Andr...
Android on Windows 11 - A Developer's Perspective (Windows Subsystem For Andr...
 
Linux GUI Applications on Windows Subsystem for Linux
Linux GUI Applications on Windows Subsystem for LinuxLinux GUI Applications on Windows Subsystem for Linux
Linux GUI Applications on Windows Subsystem for Linux
 
Python on Android with Delphi FMX - The Cross Platform GUI Framework
Python on Android with Delphi FMX - The Cross Platform GUI Framework Python on Android with Delphi FMX - The Cross Platform GUI Framework
Python on Android with Delphi FMX - The Cross Platform GUI Framework
 
Introduction to Python GUI development with Delphi for Python - Part 1: Del...
Introduction to Python GUI development with Delphi for Python - Part 1:   Del...Introduction to Python GUI development with Delphi for Python - Part 1:   Del...
Introduction to Python GUI development with Delphi for Python - Part 1: Del...
 
FMXLinux Introduction - Delphi's FireMonkey for Linux
FMXLinux Introduction - Delphi's FireMonkey for LinuxFMXLinux Introduction - Delphi's FireMonkey for Linux
FMXLinux Introduction - Delphi's FireMonkey for Linux
 
Python for Delphi Developers - Part 2
Python for Delphi Developers - Part 2Python for Delphi Developers - Part 2
Python for Delphi Developers - Part 2
 
Python for Delphi Developers - Part 1 Introduction
Python for Delphi Developers - Part 1 IntroductionPython for Delphi Developers - Part 1 Introduction
Python for Delphi Developers - Part 1 Introduction
 
RAD Industrial Automation, Labs, and Instrumentation
RAD Industrial Automation, Labs, and InstrumentationRAD Industrial Automation, Labs, and Instrumentation
RAD Industrial Automation, Labs, and Instrumentation
 
Embeddable Databases for Mobile Apps: Stress-Free Solutions with InterBase
Embeddable Databases for Mobile Apps: Stress-Free Solutions with InterBaseEmbeddable Databases for Mobile Apps: Stress-Free Solutions with InterBase
Embeddable Databases for Mobile Apps: Stress-Free Solutions with InterBase
 
Rad Server Industry Template - Connected Nurses Station - Setup Document
Rad Server Industry Template - Connected Nurses Station - Setup DocumentRad Server Industry Template - Connected Nurses Station - Setup Document
Rad Server Industry Template - Connected Nurses Station - Setup Document
 
TMS Google Mapping Components
TMS Google Mapping ComponentsTMS Google Mapping Components
TMS Google Mapping Components
 
Move Desktop Apps to the Cloud - RollApp & Embarcadero webinar
Move Desktop Apps to the Cloud - RollApp & Embarcadero webinarMove Desktop Apps to the Cloud - RollApp & Embarcadero webinar
Move Desktop Apps to the Cloud - RollApp & Embarcadero webinar
 
Useful C++ Features You Should be Using
Useful C++ Features You Should be UsingUseful C++ Features You Should be Using
Useful C++ Features You Should be Using
 
Getting Started Building Mobile Applications for iOS and Android
Getting Started Building Mobile Applications for iOS and AndroidGetting Started Building Mobile Applications for iOS and Android
Getting Started Building Mobile Applications for iOS and Android
 
Embarcadero RAD server Launch Webinar
Embarcadero RAD server Launch WebinarEmbarcadero RAD server Launch Webinar
Embarcadero RAD server Launch Webinar
 
ER/Studio 2016: Build a Business-Driven Data Architecture
ER/Studio 2016: Build a Business-Driven Data ArchitectureER/Studio 2016: Build a Business-Driven Data Architecture
ER/Studio 2016: Build a Business-Driven Data Architecture
 
The Secrets of SQL Server: Database Worst Practices
The Secrets of SQL Server: Database Worst PracticesThe Secrets of SQL Server: Database Worst Practices
The Secrets of SQL Server: Database Worst Practices
 
Driving Business Value Through Agile Data Assets
Driving Business Value Through Agile Data AssetsDriving Business Value Through Agile Data Assets
Driving Business Value Through Agile Data Assets
 
Troubleshooting Plan Changes with Query Store in SQL Server 2016
Troubleshooting Plan Changes with Query Store in SQL Server 2016Troubleshooting Plan Changes with Query Store in SQL Server 2016
Troubleshooting Plan Changes with Query Store in SQL Server 2016
 

Recently uploaded

Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Brandon Minnick, MBA
 
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
Edge AI and Vision Alliance
 
The Microsoft 365 Migration Tutorial For Beginner.pptx
The Microsoft 365 Migration Tutorial For Beginner.pptxThe Microsoft 365 Migration Tutorial For Beginner.pptx
The Microsoft 365 Migration Tutorial For Beginner.pptx
operationspcvita
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
Tatiana Kojar
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Alpen-Adria-Universität
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
akankshawande
 
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframeDigital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Precisely
 
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
Alex Pruden
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
MichaelKnudsen27
 
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsConnector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
DianaGray10
 
Dandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity serverDandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity server
Antonios Katsarakis
 
GNSS spoofing via SDR (Criptored Talks 2024)
GNSS spoofing via SDR (Criptored Talks 2024)GNSS spoofing via SDR (Criptored Talks 2024)
GNSS spoofing via SDR (Criptored Talks 2024)
Javier Junquera
 
Taking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdfTaking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdf
ssuserfac0301
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
panagenda
 
Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |
AstuteBusiness
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
saastr
 
Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving
 
Principle of conventional tomography-Bibash Shahi ppt..pptx
Principle of conventional tomography-Bibash Shahi ppt..pptxPrinciple of conventional tomography-Bibash Shahi ppt..pptx
Principle of conventional tomography-Bibash Shahi ppt..pptx
BibashShahi
 
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyFreshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
ScyllaDB
 

Recently uploaded (20)

Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
 
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
 
The Microsoft 365 Migration Tutorial For Beginner.pptx
The Microsoft 365 Migration Tutorial For Beginner.pptxThe Microsoft 365 Migration Tutorial For Beginner.pptx
The Microsoft 365 Migration Tutorial For Beginner.pptx
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
 
Artificial Intelligence and Electronic Warfare
Artificial Intelligence and Electronic WarfareArtificial Intelligence and Electronic Warfare
Artificial Intelligence and Electronic Warfare
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
 
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframeDigital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
Digital Banking in the Cloud: How Citizens Bank Unlocked Their Mainframe
 
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
 
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsConnector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
 
Dandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity serverDandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity server
 
GNSS spoofing via SDR (Criptored Talks 2024)
GNSS spoofing via SDR (Criptored Talks 2024)GNSS spoofing via SDR (Criptored Talks 2024)
GNSS spoofing via SDR (Criptored Talks 2024)
 
Taking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdfTaking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdf
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
 
Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
 
Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving | Nameplate Manufacturing Process - 2024
 
Principle of conventional tomography-Bibash Shahi ppt..pptx
Principle of conventional tomography-Bibash Shahi ppt..pptxPrinciple of conventional tomography-Bibash Shahi ppt..pptx
Principle of conventional tomography-Bibash Shahi ppt..pptx
 
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyFreshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
 

Getting Enterprise Meta Data All the Time

  • 1. June 2008 Volume 3 Number 2 www.irdonline.com Metadata may not be the best word to use to try to get senior management excited about reference data projects. But metadata management is a vital part of enterprise data management (EDM), and as EDM projects are now maturing, metadata is swiftly moving up the agenda. Tine Thoresen explores the best strategies for implementing metadata tools and systems Getting Meta All the Time John Carroll, who recently retired from Merrill says Serenita. It is often difficult to improve data research. When assessing applications, firms Lynch, had been working in the same role for 10 quality if data definitions are all over the place. should look for harvesting population utilities, years. He was initially hired to build on the vision Everyone needs to be on the same page—both to according to Carty. He says most customers will be of an enterprise data repository. But this type improve reporting and consolidate silos. able to automatically load 80% of definitions into of project is not done overnight. Carroll was still To succeed, firms simply need to identify the the system, while 20% will typically be manually working on enhancing the system 10 years on. best strategy to overcome challenges such as inputted. So when reviewing applications, firms This is the reality of reference data initiatives—the structuring the data, increasing automation, should be shooting for that 80%. projects often seem never-ending. Yet, many enter- keeping the content current and managing the And standards can offer better integration prise data management projects are now entering refresh rate. But this is obviously not that simple opportunities. Greg Keller, vice-president, product a new phase—the metadata management phase. when there is little public information on how to management at metadata management product Firms are starting to focus more on standardizing get there for financial institutions. vendor Embarcadero Technologies, advises firms and centralizing ‘data about the data.’ So, as with every other data problem, can firms to move on if the tool does not speak ‘standards.’ Peter Serenita, chief data officer at JP Morgan turn to vendors for help? Honore, who focuses on “There is no panacea, but the only way to collect, Chase, says the types of reference data technology financial services, says the projects he has seen refine, integrate and communicate this data (about he expects firms to invest in this year are meta- have been internal developments, and he does not data) is to ensure it can bi-directionally integrate data management tools. “Firms will invest in the know of anyone who is using off-the-shelf tools. via open standards such as the OMG’s [object ability to define data using data management There are, however, many vendors targeting the management group] set of data interchange stan- tools so that this information is not buried in metadata management space across industries. dards,” he says, adding that OMG’s forthcoming code,” he says (Inside Reference Data, Reference Stu Carty, founder and metadata solutions expert information management metamodel (IMM) Data Technology Special Report, May 2008). at Gavilian Research, says there are 17 vendors implementation is rooted in universally defining But so far there have not been many metadata offering metadata solutions. The providers can be storage for data standards. success stories in the financial industry. These divided into two groups—one group offers inde- Keller also says firms should choose model- types of projects can require a lot of resources, as pendent metadata management tools that can be driven products—“critical to be able to express a large portion of the work tends to be taxonomic. bought separately and the other offers metadata complex business rules in a manner that can Adam Honore, senior analyst at Aite Group, says management tools bundled into a tool suite. abstract the information in a graphical format”— some of the larger firms are currently working on The third option, which Honore mentioned, is and products that embrace logical and physical these projects, but that it is probably too early to building systems in-house. Carty says most firms data modeling as a means to express the core talk about successes. might start with internal developments, mainly underlying metadata. Yet, this is not to say that metadata management using Excel, but since vendors are getting better In fact, ease of use of the application is vital to tools cannot add tremendous value. “By providing and better, off-the-shelf solutions are becoming review when assessing metadata tools. This might visibility to the data definitions, the firm’s ability more viable. Metadata management solutions sound very basic, but it is particularly important to manage the data increases exponentially,” are database applications that can be filled with in this market, where some tools have tradition- descriptions and relationships. Carty says Google ally had a poor reputation. Carty says some prod- is an example of a metadata tool—probably the ucts are difficult to use and implement, but the biggest one. best vendors today recognize that problem, are focusing on making it easier for customers and Finding the Right Product are leveraging new technology. Although Google might help firms find informa- So the area is worth exploring. Some firms have tion, selecting vendors requires more thorough seen early successes, according to Keller, who has witnessed some “well-implemented metadata management programs in large household banks “The only way to collect, refine, both in the UK and US.” In most cases, the proj- integrate and communicate this ects revolved around data rationalisation, refining data (about data) is to ensure it and documenting the metadata values of core business attributes in an effort to point to live data can bi-directionally integrate via in order to continually assess quality, he says. open standards” And as metadata management tools mature, Greg Keller, Embarcadero Technologies the industry is set to see more of these projects succeed and materialize. © 2008 Incisive Media Investments. All rights reserved. Used by permission. First published in IRD June 2008.