SlideShare a Scribd company logo
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 1
Karen Lopez @datachick #HeartData
Heart of Data Modeling
7 Ways Your Agile Project
Is Managing Your Data Wrong
Yes, Please do Tweet/Share
today’s event
@datachick #heartdata
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 2
Karen López
Karen has 20+ years of data and information architecture
experience on large, multi-project programs.
She is a frequent speaker on data modeling, data-driven
methodologies and pattern data models.
She wants you to love your data.
Data Modelers are people,
too.
...so let’s get to know you….
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 3
POLL: Who Are
You?
What Have You Worked
on?
Aug 2014
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 4
Attendees, be part of the webinar
Use Q&A
for formal
questions
Use chat
to discuss
with each
other
Plan for Today
What is Agile? What isn’t Agile?What is Agile? What isn’t Agile?
Where does data modeling fit in Agile?Where does data modeling fit in Agile?
What role should a data modeler fill?What role should a data modeler fill?
7 data modeling mistakes on Agile projects7 data modeling mistakes on Agile projects
10 Tips for making Agile + Data Modeling work10 Tips for making Agile + Data Modeling work
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 5
Agile Methods
What are they? What else are they?
Plus at little bit of SCRUM
I love working on
Agile projects
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 6
It’s FRAGILE
projects I hate.
Agile
Manifesto
http://www.agilemanifesto.org/
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 7
Agile Principles
…readable copy coming next…
Principles Behind the Agile Manifesto
1. Our highest priority is to satisfy the
customer through early and
continuous delivery of valuable
software.
2. Welcome changing requirements,
even late in development. Agile
processes harness change for the
customer's competitive advantage.
3. Deliver working software frequently,
from a couple of weeks to a couple of
months, with preference to the
shorter timescale.
4. Business people and developers must
work together daily throughout the
project.
5. Build projects around motivated
individuals. Give them the
environment and support they
need, and trust them to get the job
done.
6. The most efficient and effective
method of conveying information to
and within a development team is
face-to-face conversation.
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 8
Principles Behind the Agile Manifesto
7. Working software is the primary
measure of progress.
8. Agile processes promote sustainable
development. The sponsors,
developers, and users should be
able to maintain a constant pace
indefinitely.
9. Continuous attention to technical
excellence and good design enhances
agility.
10. Simplicity--the art of maximizing the
amount of work not done--is
essential.
11. The best architectures,
requirements, and designs emerge
from self-organizing teams.
12. At regular intervals, the team
reflects on how to become more
effective, then tunes and adjusts its
behavior accordingly.
Manifesto for Agile Software Development
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 9
Agile “Extensions”…
Everyone is a generalist
Agile Blocking
Excluded titles
•Administrators
•Architects
•Managers
Test Driven Development
No BMUF/BDUF
Paired programming
Did I say Blocking?
Agile Blocking & Data Modeling
The blockers effectively implement a “process façade” around your
team that makes it appear to the rest of the organization that your team
is following their existing procedures. This satisfies the bureaucrats, yet
prevents them from meddling with the people that are doing the real
work. Although it sounds like a wasted overhead, and it is because it
would be far more effective to divert both the blockers and bureaucrats
to efforts that produce something of value, the advantage is that it
enables the rest of the team to get the job done. The role of blocker is
often taken on by your team’s project manager or coach, although in
the past I have let this be a revolving role on the project so as to spread
out the pain of dealing with the paper pushers.
http://www.agiledata.org/essays/adopting.html#sthash.gvFL7Hd4.dpuf
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 10
Scrum Values
Focus
• Because we focus on only a few things at a
time, we work well together and produce
excellent work. We deliver valuable items
sooner.
Courage
• Because we work as a team, we feel
supported and have more resources at our
disposal. This gives us the courage to
undertake greater challenges.
Openness
• As we work together, we express how we're
doing, what's in our way, and our concerns
so they can be addressed.
Commitment
• Because we have great control over our own
destiny, we are more committed to success.
Respect
• As we work together, sharing successes and
failures, we come to respect each other and
to help each other become worthy of
respect.
- https://www.scrumalliance.org/why-scrum/core-scrum-values-roles#sthash.RgaO3uIK.dpuf
All work performed in Scrum needs a set of values as the foundation for the team's processes and
interactions. And by embracing these five values, the team makes them even more instrumental to its
health and success.
Agile/Scrum Concepts
Parking
Lots
Backlogs
Scrum
Masters
Self
Organizing
Teams
Daily
Scrum
(stand ups)
Stories
Sprints
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 11
https://www.scrumalliance.org/why-scrum
Agile/Scrum development project
22
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 12
Typical Sprint
Sprint Planning
Backlog Stories
START
READING DEVELOPMENT DELIVER
END
Where the hell
is our
database?
Managing Data Wrong - One
Expecting data
modeling & database
design to be completed
in an instant at the
beginning of a sprint
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 13
Managing Data – Fix it
Sprint Planning
Backlog Stories
START READING DEVELOPMENT DELIVER
END
Managing Data – Fix it Better
Sprint Planning
Backlog Stories
SART
READING DEVELOPMENT
START
READING DEVELOPMENT DELIVER
END
Sprint Planning
Backlog Stories
START
READING
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 14
Enterprise Applications are Complex
27
Enterprise data
Enterprise Solutions involve complex applications &
databases
•Data Modelers understand the data
•Metadata is available
•Enterprise tools are complex
•Vendor packages are used
•External data is used
•NoSQL data & tech are used
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 15
Metadata
Security Requirements
Privacy Requirements
Stewardship
Quality Requirements
Semantics of data
Managing Data Wrong - Two
Thinking that “Just
Enough Documentation”
means “Don’t USE
EXISTING MODELS”
Let me go get a
pen and paper
Where do we
start?
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 16
Managing Data – Fix it
There is data wealth in
the enterprise. Use it.
Use data professionals
who know where it is,
how to use it.
Enterprise Projects are Integration Projects
32
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 17
Managing Data Wrong - Three
Expecting Enterprise
data modeling &
database design to be
completed Quickly,
By Generalists
I don’t want to
do the
database…let’s
get mickey. Hey
Mickey!
It’s your turn
to do the
database
Managing Data Wrong - Four
Doing Sprint Planning
without data
professionals
Let’s start with
Payroll. It’s just
reading some
data
Where should
we start?
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 18
Sprint Planning
Backlog Stories
All kinds of other
infrastructure
things
Managing Data Wrong - Five
Thinking of data
models & DDL as
just more code or
Just Documentation
I don’t have time
for
documentation
right now
When are you
going to get
writing the
data model
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 19
Managing Data – Fix it
Data models are
just enough
documentation, if
done by
professionals.
Use data
professionals who
know where it is,
how to use it.
Build better
databases with
existing data
models
Build faster with
existing data
models
Sprints
Agile Sprints
1-3 weeks
2-3 back-to-back sprints
Recovery Sprint
Special sprints
Like running intervals
Jim Galloway Sprints
- http://www.jeffgalloway.com/training/run-walk/#sthash.Uv8cdU3R.dpuf
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 20
Managing Data Wrong - Six
Expecting data
Modelers to
Sprint a
Marathon
I heard maybe
sometime next
year
When is our
Recovery
Sprint?
Managing Data Wrong - Seven
Embracing
iterative
development for
everyone ELSE.
Yeah, let’s go
find some
waterfalls to
play in
Um, no more
changes to the
database,
m‘Kay?
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 21
Managing Data – Fix it
Iterations
are
awesome…
…Except for
those that
are iterated
upon.
Don’t make
gratuitous
changes
Collaborate
on changes
that do need
to be made
Plan for
delivering
the change.
Why is there a conflict?
Most people have been taught data models
are documentation.
Most people understand data models as
ONLY mechanisms to generate DDL
Most data modelers are stuck to traditional
development methods. Overly stuck to
them.
Most people think software is the most
important, most complex part of IT
Most people think data models are boxes
and lines
Most people have never seen productive,
iterative, responsive, flexible model driven
development
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 22
10 Tips for Data Modelers
1. Stop using the word Documentation when talking
about data models
2. Get Scrum training. Get certified even
3. Learn the lingo.
4. Use the lingo
5. Push, advocate, lobby, educate, rant until others
understand that data models are gold-filled
resources for agile teams.
10 Tips for Data Modelers
6. Get data models and DDL tasks moved sprints
ahead
7. Don’t get pushed into sprinting a marathon
8. Don’t back off from Agile teams, even if they are
hostile.
9. Don’t be a roadbock. Get ahead of the sprints
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 23
10 Tips for Data Modelers
10. Practice Agile techniques on your own
deliverables
• Paired modeling (whiteboard, paper)
• Test driven development
• Backlogging
• Parkinglotting
• Continuous delivery
Plan for Today
What is Agile? What isn’t Agile?What is Agile? What isn’t Agile?
Where does data modeling fit in Agile?Where does data modeling fit in Agile?
What role should a data modeler fill?What role should a data modeler fill?
7 data modeling mistakes on Agile projects7 data modeling mistakes on Agile projects
10 Tips for making Agile + Data Modeling work10 Tips for making Agile + Data Modeling work
Karen Lopez
@DATACHICK
Feb 2015
www.dataversity.net
www.datamodel.com 24
http://edw2015.dataversity.net
AM8: Architecting and Modeling Columnar Data Stores
ER/Studio and Data Modeling Special Interest Group
Data Modeling and Design Throwdown (Double Session)
…and likely some other fun things!
Thank you, you were great.
Let’s do this next month!
Karen Lopez @datachick
#heartdata

More Related Content

What's hot

Michael Stonebraker: Big Data, Disruption, and the 800 Pound Gorilla in the ...
Michael Stonebraker:  Big Data, Disruption, and the 800 Pound Gorilla in the ...Michael Stonebraker:  Big Data, Disruption, and the 800 Pound Gorilla in the ...
Michael Stonebraker: Big Data, Disruption, and the 800 Pound Gorilla in the ...
TamrMarketing
 
Data-Ed Online: Data Architecture Requirements
Data-Ed Online: Data Architecture RequirementsData-Ed Online: Data Architecture Requirements
Data-Ed Online: Data Architecture Requirements
DATAVERSITY
 
How to Create a Data Analytics Roadmap
How to Create a Data Analytics RoadmapHow to Create a Data Analytics Roadmap
How to Create a Data Analytics Roadmap
CCG
 
Data Strategy Best Practices
Data Strategy Best PracticesData Strategy Best Practices
Data Strategy Best Practices
DATAVERSITY
 
Emerging Trends in Data Architecture – What’s the Next Big Thing
Emerging Trends in Data Architecture – What’s the Next Big ThingEmerging Trends in Data Architecture – What’s the Next Big Thing
Emerging Trends in Data Architecture – What’s the Next Big Thing
DATAVERSITY
 
Unlocking the Value of Your Data Lake
Unlocking the Value of Your Data LakeUnlocking the Value of Your Data Lake
Unlocking the Value of Your Data Lake
DATAVERSITY
 
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
DATAVERSITY
 
Architecting Data For The Modern Enterprise - Data Summit 2017, Closing Keynote
Architecting Data For The Modern Enterprise - Data Summit 2017, Closing KeynoteArchitecting Data For The Modern Enterprise - Data Summit 2017, Closing Keynote
Architecting Data For The Modern Enterprise - Data Summit 2017, Closing Keynote
Caserta
 
The Rise of the CDO in Today's Enterprise
The Rise of the CDO in Today's EnterpriseThe Rise of the CDO in Today's Enterprise
The Rise of the CDO in Today's Enterprise
Caserta
 
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
 
Agile Leadership: Guiding DataOps Teams Through Rapid Change and Uncertainty
Agile Leadership: Guiding DataOps Teams Through Rapid Change and UncertaintyAgile Leadership: Guiding DataOps Teams Through Rapid Change and Uncertainty
Agile Leadership: Guiding DataOps Teams Through Rapid Change and Uncertainty
TamrMarketing
 
A modern, flexible approach to Hadoop implementation incorporating innovation...
A modern, flexible approach to Hadoop implementation incorporating innovation...A modern, flexible approach to Hadoop implementation incorporating innovation...
A modern, flexible approach to Hadoop implementation incorporating innovation...
DataWorks Summit
 
Slides: Enterprise Architecture vs. Data Architecture
Slides: Enterprise Architecture vs. Data ArchitectureSlides: Enterprise Architecture vs. Data Architecture
Slides: Enterprise Architecture vs. Data Architecture
DATAVERSITY
 
DI&A Slides: Data-Centric Development
DI&A Slides: Data-Centric DevelopmentDI&A Slides: Data-Centric Development
DI&A Slides: Data-Centric Development
DATAVERSITY
 
ADV Slides: 2021 Trends in Enterprise Analytics
ADV Slides: 2021 Trends in Enterprise AnalyticsADV Slides: 2021 Trends in Enterprise Analytics
ADV Slides: 2021 Trends in Enterprise Analytics
DATAVERSITY
 
Fasten you seatbelt and listen to the Data Steward
Fasten you seatbelt and listen to the Data StewardFasten you seatbelt and listen to the Data Steward
Fasten you seatbelt and listen to the Data Steward
Jean-Pierre Riehl
 
Modeling Webinar: State of the Union for Data Innovation - 2016
Modeling Webinar: State of the Union for Data Innovation - 2016Modeling Webinar: State of the Union for Data Innovation - 2016
Modeling Webinar: State of the Union for Data Innovation - 2016
DATAVERSITY
 
Sailing Toward Global Data Alignment with Carnival Corporation
 Sailing Toward Global Data Alignment with Carnival Corporation Sailing Toward Global Data Alignment with Carnival Corporation
Sailing Toward Global Data Alignment with Carnival Corporation
TamrMarketing
 
Data-Ed: A Framework for no sql and Hadoop
Data-Ed: A Framework for no sql and HadoopData-Ed: A Framework for no sql and Hadoop
Data-Ed: A Framework for no sql and Hadoop
Data Blueprint
 
DI&A Slides: Data Lake vs. Data Warehouse
DI&A Slides: Data Lake vs. Data WarehouseDI&A Slides: Data Lake vs. Data Warehouse
DI&A Slides: Data Lake vs. Data Warehouse
DATAVERSITY
 

What's hot (20)

Michael Stonebraker: Big Data, Disruption, and the 800 Pound Gorilla in the ...
Michael Stonebraker:  Big Data, Disruption, and the 800 Pound Gorilla in the ...Michael Stonebraker:  Big Data, Disruption, and the 800 Pound Gorilla in the ...
Michael Stonebraker: Big Data, Disruption, and the 800 Pound Gorilla in the ...
 
Data-Ed Online: Data Architecture Requirements
Data-Ed Online: Data Architecture RequirementsData-Ed Online: Data Architecture Requirements
Data-Ed Online: Data Architecture Requirements
 
How to Create a Data Analytics Roadmap
How to Create a Data Analytics RoadmapHow to Create a Data Analytics Roadmap
How to Create a Data Analytics Roadmap
 
Data Strategy Best Practices
Data Strategy Best PracticesData Strategy Best Practices
Data Strategy Best Practices
 
Emerging Trends in Data Architecture – What’s the Next Big Thing
Emerging Trends in Data Architecture – What’s the Next Big ThingEmerging Trends in Data Architecture – What’s the Next Big Thing
Emerging Trends in Data Architecture – What’s the Next Big Thing
 
Unlocking the Value of Your Data Lake
Unlocking the Value of Your Data LakeUnlocking the Value of Your Data Lake
Unlocking the Value of Your Data Lake
 
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...
 
Architecting Data For The Modern Enterprise - Data Summit 2017, Closing Keynote
Architecting Data For The Modern Enterprise - Data Summit 2017, Closing KeynoteArchitecting Data For The Modern Enterprise - Data Summit 2017, Closing Keynote
Architecting Data For The Modern Enterprise - Data Summit 2017, Closing Keynote
 
The Rise of the CDO in Today's Enterprise
The Rise of the CDO in Today's EnterpriseThe Rise of the CDO in Today's Enterprise
The Rise of the CDO in Today's Enterprise
 
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 ...
 
Agile Leadership: Guiding DataOps Teams Through Rapid Change and Uncertainty
Agile Leadership: Guiding DataOps Teams Through Rapid Change and UncertaintyAgile Leadership: Guiding DataOps Teams Through Rapid Change and Uncertainty
Agile Leadership: Guiding DataOps Teams Through Rapid Change and Uncertainty
 
A modern, flexible approach to Hadoop implementation incorporating innovation...
A modern, flexible approach to Hadoop implementation incorporating innovation...A modern, flexible approach to Hadoop implementation incorporating innovation...
A modern, flexible approach to Hadoop implementation incorporating innovation...
 
Slides: Enterprise Architecture vs. Data Architecture
Slides: Enterprise Architecture vs. Data ArchitectureSlides: Enterprise Architecture vs. Data Architecture
Slides: Enterprise Architecture vs. Data Architecture
 
DI&A Slides: Data-Centric Development
DI&A Slides: Data-Centric DevelopmentDI&A Slides: Data-Centric Development
DI&A Slides: Data-Centric Development
 
ADV Slides: 2021 Trends in Enterprise Analytics
ADV Slides: 2021 Trends in Enterprise AnalyticsADV Slides: 2021 Trends in Enterprise Analytics
ADV Slides: 2021 Trends in Enterprise Analytics
 
Fasten you seatbelt and listen to the Data Steward
Fasten you seatbelt and listen to the Data StewardFasten you seatbelt and listen to the Data Steward
Fasten you seatbelt and listen to the Data Steward
 
Modeling Webinar: State of the Union for Data Innovation - 2016
Modeling Webinar: State of the Union for Data Innovation - 2016Modeling Webinar: State of the Union for Data Innovation - 2016
Modeling Webinar: State of the Union for Data Innovation - 2016
 
Sailing Toward Global Data Alignment with Carnival Corporation
 Sailing Toward Global Data Alignment with Carnival Corporation Sailing Toward Global Data Alignment with Carnival Corporation
Sailing Toward Global Data Alignment with Carnival Corporation
 
Data-Ed: A Framework for no sql and Hadoop
Data-Ed: A Framework for no sql and HadoopData-Ed: A Framework for no sql and Hadoop
Data-Ed: A Framework for no sql and Hadoop
 
DI&A Slides: Data Lake vs. Data Warehouse
DI&A Slides: Data Lake vs. Data WarehouseDI&A Slides: Data Lake vs. Data Warehouse
DI&A Slides: Data Lake vs. Data Warehouse
 

Similar to The Heart of Data Modeling: 7 Ways Your Agile Project is Managing Data Wrong

Data Governance in an Agile SCRUM Lean MVP World
Data Governance in an Agile SCRUM Lean MVP WorldData Governance in an Agile SCRUM Lean MVP World
Data Governance in an Agile SCRUM Lean MVP World
DATAVERSITY
 
The Heart of Data Modeling Webinar: State of the Union Data Modeling
The Heart of Data Modeling Webinar: State of the Union Data ModelingThe Heart of Data Modeling Webinar: State of the Union Data Modeling
The Heart of Data Modeling Webinar: State of the Union Data Modeling
DATAVERSITY
 
How to Start a Data Science Initiative and Grow Your Team
How to Start a Data Science Initiative and Grow Your TeamHow to Start a Data Science Initiative and Grow Your Team
How to Start a Data Science Initiative and Grow Your Team
Annie Flippo
 
Data-Ed Slides: Exorcising the Seven Deadly Data Sins
Data-Ed Slides: Exorcising the Seven Deadly Data SinsData-Ed Slides: Exorcising the Seven Deadly Data Sins
Data-Ed Slides: Exorcising the Seven Deadly Data Sins
DATAVERSITY
 
Data-Ed Webinar: Data Modeling Fundamentals
Data-Ed Webinar: Data Modeling FundamentalsData-Ed Webinar: Data Modeling Fundamentals
Data-Ed Webinar: Data Modeling Fundamentals
DATAVERSITY
 
Big dataplatform operationalstrategy
Big dataplatform operationalstrategyBig dataplatform operationalstrategy
Big dataplatform operationalstrategy
Himanshu Bari
 
Surge engr 245 lean launchpad stanford 2020
Surge engr 245 lean launchpad stanford 2020Surge engr 245 lean launchpad stanford 2020
Surge engr 245 lean launchpad stanford 2020
Stanford University
 
Data-Ed Webinar: Data Quality Engineering
Data-Ed Webinar: Data Quality EngineeringData-Ed Webinar: Data Quality Engineering
Data-Ed Webinar: Data Quality Engineering
DATAVERSITY
 
2014 dqe handouts
2014 dqe handouts2014 dqe handouts
2014 dqe handouts
Data Blueprint
 
How to Scale your Analytics in a Maturing Organization
How to Scale your Analytics in a Maturing OrganizationHow to Scale your Analytics in a Maturing Organization
How to Scale your Analytics in a Maturing Organization
Kissmetrics on SlideShare
 
Creating a data driven culture
Creating a data driven cultureCreating a data driven culture
Creating a data driven culture
Poojitha B
 
Business in the Driver’s Seat – An Improved Model for Integration
Business in the Driver’s Seat – An Improved Model for IntegrationBusiness in the Driver’s Seat – An Improved Model for Integration
Business in the Driver’s Seat – An Improved Model for Integration
Inside Analysis
 
Product Management in the Era of Data Science
Product Management in the Era of Data ScienceProduct Management in the Era of Data Science
Product Management in the Era of Data Science
Mandar Parikh
 
Measuring the Business Impact of Learning: Lagging indicators to predictive a...
Measuring the Business Impact of Learning: Lagging indicators to predictive a...Measuring the Business Impact of Learning: Lagging indicators to predictive a...
Measuring the Business Impact of Learning: Lagging indicators to predictive a...
Watershed
 
Strategy and roadmap slides
Strategy and roadmap slidesStrategy and roadmap slides
Strategy and roadmap slides
Data Blueprint
 
Data-Ed Online Webinar: Data-centric Strategy & Roadmap
Data-Ed Online Webinar: Data-centric Strategy & RoadmapData-Ed Online Webinar: Data-centric Strategy & Roadmap
Data-Ed Online Webinar: Data-centric Strategy & Roadmap
DATAVERSITY
 
7 Things Agile Leaders and Executives Do Differently - Agile Australia 2016 b...
7 Things Agile Leaders and Executives Do Differently - Agile Australia 2016 b...7 Things Agile Leaders and Executives Do Differently - Agile Australia 2016 b...
7 Things Agile Leaders and Executives Do Differently - Agile Australia 2016 b...
Dipesh Pala
 
Data-Ed Online: Trends in Data Modeling
Data-Ed Online: Trends in Data ModelingData-Ed Online: Trends in Data Modeling
Data-Ed Online: Trends in Data Modeling
DATAVERSITY
 
Data-Ed: Trends in Data Modeling
Data-Ed: Trends in Data ModelingData-Ed: Trends in Data Modeling
Data-Ed: Trends in Data Modeling
Data Blueprint
 
Mastering your data with ca e rwin dm 09082010
Mastering your data with ca e rwin dm 09082010Mastering your data with ca e rwin dm 09082010
Mastering your data with ca e rwin dm 09082010
ERwin Modeling
 

Similar to The Heart of Data Modeling: 7 Ways Your Agile Project is Managing Data Wrong (20)

Data Governance in an Agile SCRUM Lean MVP World
Data Governance in an Agile SCRUM Lean MVP WorldData Governance in an Agile SCRUM Lean MVP World
Data Governance in an Agile SCRUM Lean MVP World
 
The Heart of Data Modeling Webinar: State of the Union Data Modeling
The Heart of Data Modeling Webinar: State of the Union Data ModelingThe Heart of Data Modeling Webinar: State of the Union Data Modeling
The Heart of Data Modeling Webinar: State of the Union Data Modeling
 
How to Start a Data Science Initiative and Grow Your Team
How to Start a Data Science Initiative and Grow Your TeamHow to Start a Data Science Initiative and Grow Your Team
How to Start a Data Science Initiative and Grow Your Team
 
Data-Ed Slides: Exorcising the Seven Deadly Data Sins
Data-Ed Slides: Exorcising the Seven Deadly Data SinsData-Ed Slides: Exorcising the Seven Deadly Data Sins
Data-Ed Slides: Exorcising the Seven Deadly Data Sins
 
Data-Ed Webinar: Data Modeling Fundamentals
Data-Ed Webinar: Data Modeling FundamentalsData-Ed Webinar: Data Modeling Fundamentals
Data-Ed Webinar: Data Modeling Fundamentals
 
Big dataplatform operationalstrategy
Big dataplatform operationalstrategyBig dataplatform operationalstrategy
Big dataplatform operationalstrategy
 
Surge engr 245 lean launchpad stanford 2020
Surge engr 245 lean launchpad stanford 2020Surge engr 245 lean launchpad stanford 2020
Surge engr 245 lean launchpad stanford 2020
 
Data-Ed Webinar: Data Quality Engineering
Data-Ed Webinar: Data Quality EngineeringData-Ed Webinar: Data Quality Engineering
Data-Ed Webinar: Data Quality Engineering
 
2014 dqe handouts
2014 dqe handouts2014 dqe handouts
2014 dqe handouts
 
How to Scale your Analytics in a Maturing Organization
How to Scale your Analytics in a Maturing OrganizationHow to Scale your Analytics in a Maturing Organization
How to Scale your Analytics in a Maturing Organization
 
Creating a data driven culture
Creating a data driven cultureCreating a data driven culture
Creating a data driven culture
 
Business in the Driver’s Seat – An Improved Model for Integration
Business in the Driver’s Seat – An Improved Model for IntegrationBusiness in the Driver’s Seat – An Improved Model for Integration
Business in the Driver’s Seat – An Improved Model for Integration
 
Product Management in the Era of Data Science
Product Management in the Era of Data ScienceProduct Management in the Era of Data Science
Product Management in the Era of Data Science
 
Measuring the Business Impact of Learning: Lagging indicators to predictive a...
Measuring the Business Impact of Learning: Lagging indicators to predictive a...Measuring the Business Impact of Learning: Lagging indicators to predictive a...
Measuring the Business Impact of Learning: Lagging indicators to predictive a...
 
Strategy and roadmap slides
Strategy and roadmap slidesStrategy and roadmap slides
Strategy and roadmap slides
 
Data-Ed Online Webinar: Data-centric Strategy & Roadmap
Data-Ed Online Webinar: Data-centric Strategy & RoadmapData-Ed Online Webinar: Data-centric Strategy & Roadmap
Data-Ed Online Webinar: Data-centric Strategy & Roadmap
 
7 Things Agile Leaders and Executives Do Differently - Agile Australia 2016 b...
7 Things Agile Leaders and Executives Do Differently - Agile Australia 2016 b...7 Things Agile Leaders and Executives Do Differently - Agile Australia 2016 b...
7 Things Agile Leaders and Executives Do Differently - Agile Australia 2016 b...
 
Data-Ed Online: Trends in Data Modeling
Data-Ed Online: Trends in Data ModelingData-Ed Online: Trends in Data Modeling
Data-Ed Online: Trends in Data Modeling
 
Data-Ed: Trends in Data Modeling
Data-Ed: Trends in Data ModelingData-Ed: Trends in Data Modeling
Data-Ed: Trends in Data Modeling
 
Mastering your data with ca e rwin dm 09082010
Mastering your data with ca e rwin dm 09082010Mastering your data with ca e rwin dm 09082010
Mastering your data with ca e rwin dm 09082010
 

More from DATAVERSITY

Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
DATAVERSITY
 
Data at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and GovernanceData at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and Governance
DATAVERSITY
 
Exploring Levels of Data Literacy
Exploring Levels of Data LiteracyExploring Levels of Data Literacy
Exploring Levels of Data Literacy
DATAVERSITY
 
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
DATAVERSITY
 
Make Data Work for You
Make Data Work for YouMake Data Work for You
Make Data Work for You
DATAVERSITY
 
Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?
DATAVERSITY
 
Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?
DATAVERSITY
 
Data Modeling Fundamentals
Data Modeling FundamentalsData Modeling Fundamentals
Data Modeling Fundamentals
DATAVERSITY
 
Showing ROI for Your Analytic Project
Showing ROI for Your Analytic ProjectShowing ROI for Your Analytic Project
Showing ROI for Your Analytic Project
DATAVERSITY
 
How a Semantic Layer Makes Data Mesh Work at Scale
How a Semantic Layer Makes  Data Mesh Work at ScaleHow a Semantic Layer Makes  Data Mesh Work at Scale
How a Semantic Layer Makes Data Mesh Work at Scale
DATAVERSITY
 
Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?
DATAVERSITY
 
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
DATAVERSITY
 
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
 
Data Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and ForwardsData Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and Forwards
DATAVERSITY
 
Data Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement TodayData Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement Today
DATAVERSITY
 
2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics
DATAVERSITY
 
Data Strategy Best Practices
Data Strategy Best PracticesData Strategy Best Practices
Data Strategy Best Practices
DATAVERSITY
 
Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?
DATAVERSITY
 
Data Management Best Practices
Data Management Best PracticesData Management Best Practices
Data Management Best Practices
DATAVERSITY
 
MLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive AdvantageMLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive Advantage
DATAVERSITY
 

More from DATAVERSITY (20)

Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
 
Data at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and GovernanceData at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and Governance
 
Exploring Levels of Data Literacy
Exploring Levels of Data LiteracyExploring Levels of Data Literacy
Exploring Levels of Data Literacy
 
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
 
Make Data Work for You
Make Data Work for YouMake Data Work for You
Make Data Work for You
 
Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?
 
Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?
 
Data Modeling Fundamentals
Data Modeling FundamentalsData Modeling Fundamentals
Data Modeling Fundamentals
 
Showing ROI for Your Analytic Project
Showing ROI for Your Analytic ProjectShowing ROI for Your Analytic Project
Showing ROI for Your Analytic Project
 
How a Semantic Layer Makes Data Mesh Work at Scale
How a Semantic Layer Makes  Data Mesh Work at ScaleHow a Semantic Layer Makes  Data Mesh Work at Scale
How a Semantic Layer Makes Data Mesh Work at Scale
 
Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?
 
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
 
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?
 
Data Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and ForwardsData Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and Forwards
 
Data Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement TodayData Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement Today
 
2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics
 
Data Strategy Best Practices
Data Strategy Best PracticesData Strategy Best Practices
Data Strategy Best Practices
 
Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?
 
Data Management Best Practices
Data Management Best PracticesData Management Best Practices
Data Management Best Practices
 
MLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive AdvantageMLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive Advantage
 

Recently uploaded

RPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptx
RPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptxRPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptx
RPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptx
SynapseIndia
 
"Mastering Graphic Design: Essential Tips and Tricks for Beginners and Profes...
"Mastering Graphic Design: Essential Tips and Tricks for Beginners and Profes..."Mastering Graphic Design: Essential Tips and Tricks for Beginners and Profes...
"Mastering Graphic Design: Essential Tips and Tricks for Beginners and Profes...
Anant Gupta
 
Evolution of iPaaS - simplify IT workloads to provide a unified view of data...
Evolution of iPaaS - simplify IT workloads to provide a unified view of  data...Evolution of iPaaS - simplify IT workloads to provide a unified view of  data...
Evolution of iPaaS - simplify IT workloads to provide a unified view of data...
Torry Harris
 
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-In
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-InTrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-In
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-In
TrustArc
 
“Deploying Large Language Models on a Raspberry Pi,” a Presentation from Usef...
“Deploying Large Language Models on a Raspberry Pi,” a Presentation from Usef...“Deploying Large Language Models on a Raspberry Pi,” a Presentation from Usef...
“Deploying Large Language Models on a Raspberry Pi,” a Presentation from Usef...
Edge AI and Vision Alliance
 
Opencast Summit 2024 — Opencast @ University of Münster
Opencast Summit 2024 — Opencast @ University of MünsterOpencast Summit 2024 — Opencast @ University of Münster
Opencast Summit 2024 — Opencast @ University of Münster
Matthias Neugebauer
 
Figma AI Design Generator_ In-Depth Review.pdf
Figma AI Design Generator_ In-Depth Review.pdfFigma AI Design Generator_ In-Depth Review.pdf
Figma AI Design Generator_ In-Depth Review.pdf
Management Institute of Skills Development
 
How to Build a Profitable IoT Product.pptx
How to Build a Profitable IoT Product.pptxHow to Build a Profitable IoT Product.pptx
How to Build a Profitable IoT Product.pptx
Adam Dunkels
 
(CISOPlatform Summit & SACON 2024) Digital Personal Data Protection Act.pdf
(CISOPlatform Summit & SACON 2024) Digital Personal Data Protection Act.pdf(CISOPlatform Summit & SACON 2024) Digital Personal Data Protection Act.pdf
(CISOPlatform Summit & SACON 2024) Digital Personal Data Protection Act.pdf
Priyanka Aash
 
High Profile Girls call Service Pune 000XX00000 Provide Best And Top Girl Ser...
High Profile Girls call Service Pune 000XX00000 Provide Best And Top Girl Ser...High Profile Girls call Service Pune 000XX00000 Provide Best And Top Girl Ser...
High Profile Girls call Service Pune 000XX00000 Provide Best And Top Girl Ser...
bhumivarma35300
 
Three New Criminal Laws in India 1 July 2024
Three New Criminal Laws in India 1 July 2024Three New Criminal Laws in India 1 July 2024
Three New Criminal Laws in India 1 July 2024
aakash malhotra
 
Girls Call Churchgate 9910780858 Provide Best And Top Girl Service And No1 in...
Girls Call Churchgate 9910780858 Provide Best And Top Girl Service And No1 in...Girls Call Churchgate 9910780858 Provide Best And Top Girl Service And No1 in...
Girls Call Churchgate 9910780858 Provide Best And Top Girl Service And No1 in...
maigasapphire
 
Recent Advancements in the NIST-JARVIS Infrastructure
Recent Advancements in the NIST-JARVIS InfrastructureRecent Advancements in the NIST-JARVIS Infrastructure
Recent Advancements in the NIST-JARVIS Infrastructure
KAMAL CHOUDHARY
 
Google I/O Extended Harare Merged Slides
Google I/O Extended Harare Merged SlidesGoogle I/O Extended Harare Merged Slides
Google I/O Extended Harare Merged Slides
Google Developer Group - Harare
 
Litestack talk at Brighton 2024 (Unleashing the power of SQLite for Ruby apps)
Litestack talk at Brighton 2024 (Unleashing the power of SQLite for Ruby apps)Litestack talk at Brighton 2024 (Unleashing the power of SQLite for Ruby apps)
Litestack talk at Brighton 2024 (Unleashing the power of SQLite for Ruby apps)
Muhammad Ali
 
CHAPTER-8 COMPONENTS OF COMPUTER SYSTEM CLASS 9 CBSE
CHAPTER-8 COMPONENTS OF COMPUTER SYSTEM CLASS 9 CBSECHAPTER-8 COMPONENTS OF COMPUTER SYSTEM CLASS 9 CBSE
CHAPTER-8 COMPONENTS OF COMPUTER SYSTEM CLASS 9 CBSE
kumarjarun2010
 
Acumatica vs. Sage Intacct vs. NetSuite _ NOW CFO.pdf
Acumatica vs. Sage Intacct vs. NetSuite _ NOW CFO.pdfAcumatica vs. Sage Intacct vs. NetSuite _ NOW CFO.pdf
Acumatica vs. Sage Intacct vs. NetSuite _ NOW CFO.pdf
BrainSell Technologies
 
BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdf
BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdfBT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdf
BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdf
Neo4j
 
Introduction-to-the-IAM-Platform-Implementation-Plan.pptx
Introduction-to-the-IAM-Platform-Implementation-Plan.pptxIntroduction-to-the-IAM-Platform-Implementation-Plan.pptx
Introduction-to-the-IAM-Platform-Implementation-Plan.pptx
313mohammedarshad
 
Best Practices for Effectively Running dbt in Airflow.pdf
Best Practices for Effectively Running dbt in Airflow.pdfBest Practices for Effectively Running dbt in Airflow.pdf
Best Practices for Effectively Running dbt in Airflow.pdf
Tatiana Al-Chueyr
 

Recently uploaded (20)

RPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptx
RPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptxRPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptx
RPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptx
 
"Mastering Graphic Design: Essential Tips and Tricks for Beginners and Profes...
"Mastering Graphic Design: Essential Tips and Tricks for Beginners and Profes..."Mastering Graphic Design: Essential Tips and Tricks for Beginners and Profes...
"Mastering Graphic Design: Essential Tips and Tricks for Beginners and Profes...
 
Evolution of iPaaS - simplify IT workloads to provide a unified view of data...
Evolution of iPaaS - simplify IT workloads to provide a unified view of  data...Evolution of iPaaS - simplify IT workloads to provide a unified view of  data...
Evolution of iPaaS - simplify IT workloads to provide a unified view of data...
 
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-In
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-InTrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-In
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-In
 
“Deploying Large Language Models on a Raspberry Pi,” a Presentation from Usef...
“Deploying Large Language Models on a Raspberry Pi,” a Presentation from Usef...“Deploying Large Language Models on a Raspberry Pi,” a Presentation from Usef...
“Deploying Large Language Models on a Raspberry Pi,” a Presentation from Usef...
 
Opencast Summit 2024 — Opencast @ University of Münster
Opencast Summit 2024 — Opencast @ University of MünsterOpencast Summit 2024 — Opencast @ University of Münster
Opencast Summit 2024 — Opencast @ University of Münster
 
Figma AI Design Generator_ In-Depth Review.pdf
Figma AI Design Generator_ In-Depth Review.pdfFigma AI Design Generator_ In-Depth Review.pdf
Figma AI Design Generator_ In-Depth Review.pdf
 
How to Build a Profitable IoT Product.pptx
How to Build a Profitable IoT Product.pptxHow to Build a Profitable IoT Product.pptx
How to Build a Profitable IoT Product.pptx
 
(CISOPlatform Summit & SACON 2024) Digital Personal Data Protection Act.pdf
(CISOPlatform Summit & SACON 2024) Digital Personal Data Protection Act.pdf(CISOPlatform Summit & SACON 2024) Digital Personal Data Protection Act.pdf
(CISOPlatform Summit & SACON 2024) Digital Personal Data Protection Act.pdf
 
High Profile Girls call Service Pune 000XX00000 Provide Best And Top Girl Ser...
High Profile Girls call Service Pune 000XX00000 Provide Best And Top Girl Ser...High Profile Girls call Service Pune 000XX00000 Provide Best And Top Girl Ser...
High Profile Girls call Service Pune 000XX00000 Provide Best And Top Girl Ser...
 
Three New Criminal Laws in India 1 July 2024
Three New Criminal Laws in India 1 July 2024Three New Criminal Laws in India 1 July 2024
Three New Criminal Laws in India 1 July 2024
 
Girls Call Churchgate 9910780858 Provide Best And Top Girl Service And No1 in...
Girls Call Churchgate 9910780858 Provide Best And Top Girl Service And No1 in...Girls Call Churchgate 9910780858 Provide Best And Top Girl Service And No1 in...
Girls Call Churchgate 9910780858 Provide Best And Top Girl Service And No1 in...
 
Recent Advancements in the NIST-JARVIS Infrastructure
Recent Advancements in the NIST-JARVIS InfrastructureRecent Advancements in the NIST-JARVIS Infrastructure
Recent Advancements in the NIST-JARVIS Infrastructure
 
Google I/O Extended Harare Merged Slides
Google I/O Extended Harare Merged SlidesGoogle I/O Extended Harare Merged Slides
Google I/O Extended Harare Merged Slides
 
Litestack talk at Brighton 2024 (Unleashing the power of SQLite for Ruby apps)
Litestack talk at Brighton 2024 (Unleashing the power of SQLite for Ruby apps)Litestack talk at Brighton 2024 (Unleashing the power of SQLite for Ruby apps)
Litestack talk at Brighton 2024 (Unleashing the power of SQLite for Ruby apps)
 
CHAPTER-8 COMPONENTS OF COMPUTER SYSTEM CLASS 9 CBSE
CHAPTER-8 COMPONENTS OF COMPUTER SYSTEM CLASS 9 CBSECHAPTER-8 COMPONENTS OF COMPUTER SYSTEM CLASS 9 CBSE
CHAPTER-8 COMPONENTS OF COMPUTER SYSTEM CLASS 9 CBSE
 
Acumatica vs. Sage Intacct vs. NetSuite _ NOW CFO.pdf
Acumatica vs. Sage Intacct vs. NetSuite _ NOW CFO.pdfAcumatica vs. Sage Intacct vs. NetSuite _ NOW CFO.pdf
Acumatica vs. Sage Intacct vs. NetSuite _ NOW CFO.pdf
 
BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdf
BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdfBT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdf
BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdf
 
Introduction-to-the-IAM-Platform-Implementation-Plan.pptx
Introduction-to-the-IAM-Platform-Implementation-Plan.pptxIntroduction-to-the-IAM-Platform-Implementation-Plan.pptx
Introduction-to-the-IAM-Platform-Implementation-Plan.pptx
 
Best Practices for Effectively Running dbt in Airflow.pdf
Best Practices for Effectively Running dbt in Airflow.pdfBest Practices for Effectively Running dbt in Airflow.pdf
Best Practices for Effectively Running dbt in Airflow.pdf
 

The Heart of Data Modeling: 7 Ways Your Agile Project is Managing Data Wrong

  • 1. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 1 Karen Lopez @datachick #HeartData Heart of Data Modeling 7 Ways Your Agile Project Is Managing Your Data Wrong Yes, Please do Tweet/Share today’s event @datachick #heartdata
  • 2. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 2 Karen López Karen has 20+ years of data and information architecture experience on large, multi-project programs. She is a frequent speaker on data modeling, data-driven methodologies and pattern data models. She wants you to love your data. Data Modelers are people, too. ...so let’s get to know you….
  • 3. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 3 POLL: Who Are You? What Have You Worked on? Aug 2014
  • 4. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 4 Attendees, be part of the webinar Use Q&A for formal questions Use chat to discuss with each other Plan for Today What is Agile? What isn’t Agile?What is Agile? What isn’t Agile? Where does data modeling fit in Agile?Where does data modeling fit in Agile? What role should a data modeler fill?What role should a data modeler fill? 7 data modeling mistakes on Agile projects7 data modeling mistakes on Agile projects 10 Tips for making Agile + Data Modeling work10 Tips for making Agile + Data Modeling work
  • 5. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 5 Agile Methods What are they? What else are they? Plus at little bit of SCRUM I love working on Agile projects
  • 6. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 6 It’s FRAGILE projects I hate. Agile Manifesto http://www.agilemanifesto.org/
  • 7. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 7 Agile Principles …readable copy coming next… Principles Behind the Agile Manifesto 1. Our highest priority is to satisfy the customer through early and continuous delivery of valuable software. 2. Welcome changing requirements, even late in development. Agile processes harness change for the customer's competitive advantage. 3. Deliver working software frequently, from a couple of weeks to a couple of months, with preference to the shorter timescale. 4. Business people and developers must work together daily throughout the project. 5. Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done. 6. The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.
  • 8. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 8 Principles Behind the Agile Manifesto 7. Working software is the primary measure of progress. 8. Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely. 9. Continuous attention to technical excellence and good design enhances agility. 10. Simplicity--the art of maximizing the amount of work not done--is essential. 11. The best architectures, requirements, and designs emerge from self-organizing teams. 12. At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly. Manifesto for Agile Software Development
  • 9. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 9 Agile “Extensions”… Everyone is a generalist Agile Blocking Excluded titles •Administrators •Architects •Managers Test Driven Development No BMUF/BDUF Paired programming Did I say Blocking? Agile Blocking & Data Modeling The blockers effectively implement a “process façade” around your team that makes it appear to the rest of the organization that your team is following their existing procedures. This satisfies the bureaucrats, yet prevents them from meddling with the people that are doing the real work. Although it sounds like a wasted overhead, and it is because it would be far more effective to divert both the blockers and bureaucrats to efforts that produce something of value, the advantage is that it enables the rest of the team to get the job done. The role of blocker is often taken on by your team’s project manager or coach, although in the past I have let this be a revolving role on the project so as to spread out the pain of dealing with the paper pushers. http://www.agiledata.org/essays/adopting.html#sthash.gvFL7Hd4.dpuf
  • 10. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 10 Scrum Values Focus • Because we focus on only a few things at a time, we work well together and produce excellent work. We deliver valuable items sooner. Courage • Because we work as a team, we feel supported and have more resources at our disposal. This gives us the courage to undertake greater challenges. Openness • As we work together, we express how we're doing, what's in our way, and our concerns so they can be addressed. Commitment • Because we have great control over our own destiny, we are more committed to success. Respect • As we work together, sharing successes and failures, we come to respect each other and to help each other become worthy of respect. - https://www.scrumalliance.org/why-scrum/core-scrum-values-roles#sthash.RgaO3uIK.dpuf All work performed in Scrum needs a set of values as the foundation for the team's processes and interactions. And by embracing these five values, the team makes them even more instrumental to its health and success. Agile/Scrum Concepts Parking Lots Backlogs Scrum Masters Self Organizing Teams Daily Scrum (stand ups) Stories Sprints
  • 11. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 11 https://www.scrumalliance.org/why-scrum Agile/Scrum development project 22
  • 12. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 12 Typical Sprint Sprint Planning Backlog Stories START READING DEVELOPMENT DELIVER END Where the hell is our database? Managing Data Wrong - One Expecting data modeling & database design to be completed in an instant at the beginning of a sprint
  • 13. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 13 Managing Data – Fix it Sprint Planning Backlog Stories START READING DEVELOPMENT DELIVER END Managing Data – Fix it Better Sprint Planning Backlog Stories SART READING DEVELOPMENT START READING DEVELOPMENT DELIVER END Sprint Planning Backlog Stories START READING
  • 14. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 14 Enterprise Applications are Complex 27 Enterprise data Enterprise Solutions involve complex applications & databases •Data Modelers understand the data •Metadata is available •Enterprise tools are complex •Vendor packages are used •External data is used •NoSQL data & tech are used
  • 15. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 15 Metadata Security Requirements Privacy Requirements Stewardship Quality Requirements Semantics of data Managing Data Wrong - Two Thinking that “Just Enough Documentation” means “Don’t USE EXISTING MODELS” Let me go get a pen and paper Where do we start?
  • 16. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 16 Managing Data – Fix it There is data wealth in the enterprise. Use it. Use data professionals who know where it is, how to use it. Enterprise Projects are Integration Projects 32
  • 17. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 17 Managing Data Wrong - Three Expecting Enterprise data modeling & database design to be completed Quickly, By Generalists I don’t want to do the database…let’s get mickey. Hey Mickey! It’s your turn to do the database Managing Data Wrong - Four Doing Sprint Planning without data professionals Let’s start with Payroll. It’s just reading some data Where should we start?
  • 18. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 18 Sprint Planning Backlog Stories All kinds of other infrastructure things Managing Data Wrong - Five Thinking of data models & DDL as just more code or Just Documentation I don’t have time for documentation right now When are you going to get writing the data model
  • 19. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 19 Managing Data – Fix it Data models are just enough documentation, if done by professionals. Use data professionals who know where it is, how to use it. Build better databases with existing data models Build faster with existing data models Sprints Agile Sprints 1-3 weeks 2-3 back-to-back sprints Recovery Sprint Special sprints Like running intervals Jim Galloway Sprints - http://www.jeffgalloway.com/training/run-walk/#sthash.Uv8cdU3R.dpuf
  • 20. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 20 Managing Data Wrong - Six Expecting data Modelers to Sprint a Marathon I heard maybe sometime next year When is our Recovery Sprint? Managing Data Wrong - Seven Embracing iterative development for everyone ELSE. Yeah, let’s go find some waterfalls to play in Um, no more changes to the database, m‘Kay?
  • 21. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 21 Managing Data – Fix it Iterations are awesome… …Except for those that are iterated upon. Don’t make gratuitous changes Collaborate on changes that do need to be made Plan for delivering the change. Why is there a conflict? Most people have been taught data models are documentation. Most people understand data models as ONLY mechanisms to generate DDL Most data modelers are stuck to traditional development methods. Overly stuck to them. Most people think software is the most important, most complex part of IT Most people think data models are boxes and lines Most people have never seen productive, iterative, responsive, flexible model driven development
  • 22. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 22 10 Tips for Data Modelers 1. Stop using the word Documentation when talking about data models 2. Get Scrum training. Get certified even 3. Learn the lingo. 4. Use the lingo 5. Push, advocate, lobby, educate, rant until others understand that data models are gold-filled resources for agile teams. 10 Tips for Data Modelers 6. Get data models and DDL tasks moved sprints ahead 7. Don’t get pushed into sprinting a marathon 8. Don’t back off from Agile teams, even if they are hostile. 9. Don’t be a roadbock. Get ahead of the sprints
  • 23. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 23 10 Tips for Data Modelers 10. Practice Agile techniques on your own deliverables • Paired modeling (whiteboard, paper) • Test driven development • Backlogging • Parkinglotting • Continuous delivery Plan for Today What is Agile? What isn’t Agile?What is Agile? What isn’t Agile? Where does data modeling fit in Agile?Where does data modeling fit in Agile? What role should a data modeler fill?What role should a data modeler fill? 7 data modeling mistakes on Agile projects7 data modeling mistakes on Agile projects 10 Tips for making Agile + Data Modeling work10 Tips for making Agile + Data Modeling work
  • 24. Karen Lopez @DATACHICK Feb 2015 www.dataversity.net www.datamodel.com 24 http://edw2015.dataversity.net AM8: Architecting and Modeling Columnar Data Stores ER/Studio and Data Modeling Special Interest Group Data Modeling and Design Throwdown (Double Session) …and likely some other fun things! Thank you, you were great. Let’s do this next month! Karen Lopez @datachick #heartdata