“I had the distinct honor and pleasure of working with Dale while at Talend where he served as a Customer Success Architect and Regional Manager NORAM. He is one of the hardest-working, competent, and dedicated colleagues I have had the opportunity to work with on highly complex data integration and governance projects for enterprise-class entities. As the founding member and leader of our Customer Success Architecture Team, Dale always worked diligently to develop and present technical guidance, architecture and job designs for many customers and user groups across the USA ensuring their long-term success and the deliverance of maximum value on their investment. Dale’s technical acumen is unmatched relative to conducting deep professional discovery thereby understanding and articulately presenting solutions to customers who require data analytics but lack the resources to build a modern data infrastructure themselves. He has a true passion for helping organizations succeed and I took note of how his commitment and leadership often inspired others to do their best work. His expertise leveraging Talend, Snowflake, Azure, Data Vault 2.0 Architecture Methodology and Data Model make him a tremendously valuable resource for any organization seeking a state-of-the-art data infrastructure. I offer my strongest recommendation in support of Dale as he is a tremendous asset to any team, and I would be honored to collaborate with him again downrange!”
Dale Anderson (CDVP2)
El Dorado Hills, California, United States
4K followers
500+ connections
About
Experienced, technology protagonist in:
Talend, Snowflake, Data Vault…
Contributions
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What are the key differences between data lakes and data warehouses?
Data by any other name (data lake, data hub, data mesh, data lakehouse, data warehouse, etc.), is still just DATA. Why do we need data? It's not because we create so much if it, it's more about getting valuable information and insights to the business. Data structures (all data has structure; even semi- or un-structured data has metadata about its structure) which suggest there must be a Data Model. Something that defines the data structure AND the relationships between them (E.F. Codd and C.J. Date defined Relational Theory & Modeling; read up on that). Why do we want the data? or a Data Model? That is simple. A Data Model 'validates' the Business (cr: Dan Linstedt) providing value to its users. Without the structure, we just have data.
Activity
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Leadership want a silver bullet to improving data quality, but that doesn’t exist Below, I list out how you can start to think about data quality…
Leadership want a silver bullet to improving data quality, but that doesn’t exist Below, I list out how you can start to think about data quality…
Liked by Dale Anderson (CDVP2)
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DataRebels is offering this CDVP2.0 Course for the last time. 🗓️August 20-23 📍USA - 100% virtual Mark your calendar and register for the last…
DataRebels is offering this CDVP2.0 Course for the last time. 🗓️August 20-23 📍USA - 100% virtual Mark your calendar and register for the last…
Liked by Dale Anderson (CDVP2)
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When was the last time you asked someone if they truly trust or understand the data they work with? It's an important question because trust and…
When was the last time you asked someone if they truly trust or understand the data they work with? It's an important question because trust and…
Liked by Dale Anderson (CDVP2)
Experience
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Education
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Software Engineering
Licenses & Certifications
Volunteer Experience
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Video Production Technician
Rolling Hills Christian Church
Science and Technology
Publications
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Introduction to the Agile Data Lake (video)
Talend, Inc.
See publicationBecome informed on the proper Architecture, Methodology, and Data Model required for building a successful Data Lake that serves ALL business users.
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Introduction to the Agile Data Lake
Talend, Inc.
See publicationWhat is a Data Lake? How do you build a successful Data Lake? It should be Agile! Read on for an in depth look at the Data Lake Life Cycle.
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Talend Job Design Patterns & Best Practices Part 3&4 (video)
Talend, INc.
See publicationExtended series on the best way to write Talend Jobs.;
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Talend Job Design Patterns & Best Practices Part 1&2 (video)
Talend, Inc.
See publicationWatch the Talend User Group session held in Detroit, MI for the foundational precepts of good Talend code.
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Successful Methodologies with Talend – Part 2
Talend, Inc.
See publicationContinuation discussion about Talend Job Design Patterns
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Successful Methodologies with Talend
Talend Inc.
See publicationSuccessful Talend projects should use these proper methodologies.
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Data Model Design & Best Practices Part 2
Talend, Inc.
See publicationWhat is Data Model? Here is my take on the best way to design them.
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Data Model Design & Best Practices – Part 1
Talend, Inc.
See publicationData Models are here to stay: Use them!
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Building a Governed Data Lake in the Cloud
Talend, Inc.
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Talend “Job Design Patterns” & Best Practices ~ Part 4
Talend, Inc.
See publicationWrap up Job Design Patterns & Best Practices with Talend.
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Talend “Job Design Patterns” and Best Practices - Part 3
Talend Inc.
See publicationMore Job Design Patterns & Best Practices with Talend.
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Talend and "The Data Vault"
Talend Inc.
See publicationWhere does Talend and “The Data Vault” converge?
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Talend “Job Design Patterns” and Best Practices - Part 2
Talend Inc.
See publicationAn extended Primer on Talend Job Design Patterns
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Talend “Job Design Patterns” and Best Practices
Talend Inc.
See publicationA Primer on Talend Job Design Patterns.
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Beyond "The Data Vault"
Talend Inc.
See publicationHere is a look beyond the Data Vault. Hope you find this useful.
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What is the Data Vault and why do we need it (updated)
Talend Inc.
See publicationHere is an updated version of my blog on Data Vault inspired by my earlier Jun 2012 post.
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Extract-Transform-Load (ETL) Technologies - Part 2
DB Best Chronicles
See publicationDiscover key vendors in today's ETL Tools marketplace
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Extract-Transform-Load (ETL) Technologies – Part 1
DB Best Chronicles
See publicationOverview and analysis of ETL technology and methodology
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Column Oriented Database Technologies
DB Best Chronicles
See publicationOverview and explaination of Column Based database technologies.
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The Data Vault – What is it? – Why do we need it?
DB Best Chronicles
See publicationOverview and analysis of Dan Linstedt's Data Vault modeling and methodology for data warehouses
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Big Data and NoSQL Technologies
DB Best Chronicles
See publicationFollow up article on how Big Data and emerging 'NoSQL' technologies impact todays marketplace.
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NoSQL .vs. Row .vs. Column
DB Best Chronicles
See publicationDispelling the myths of 'NoSQL' and comparison against Row and Column based database technology.
Projects
Honors & Awards
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2018 Talend Community Champion Award
Talend, Inc.
For top achievements in delivering technical presentations across Talend community user groups.
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2016 Top Gun Award: Customer Success 'Gatling Gun'
Talend, Inc.
for crafting scalable Talend Job Design Patterns & Best Practices content
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2015 President's Club Receipient
Talend, Inc.
Languages
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English
Native or bilingual proficiency
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French
Limited working proficiency
Recommendations received
57 people have recommended Dale
Join now to viewMore activity by Dale
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To fix data quality, you first have to understand what it means and where issues come from Unfortunately too many people complain about data…
To fix data quality, you first have to understand what it means and where issues come from Unfortunately too many people complain about data…
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Why do organizations need data modeling? Find out from Keith Belanger, Product Evangelist, and Kent Graziano, Data Warrior as they discuss the…
Why do organizations need data modeling? Find out from Keith Belanger, Product Evangelist, and Kent Graziano, Data Warrior as they discuss the…
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Don’t push to production on Friday. #crowdstrike
Don’t push to production on Friday. #crowdstrike
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In 2 weeks, I'll be riding the Pan-Mass Challenge (PMC). This will be my 24th time riding. The reason I ride - in less than 3 words - is CANCER…
In 2 weeks, I'll be riding the Pan-Mass Challenge (PMC). This will be my 24th time riding. The reason I ride - in less than 3 words - is CANCER…
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Last Friday was my last day at SqlDBM! I want to thank my bosses, mentors, and colleagues for their support during my time there, especially Anna…
Last Friday was my last day at SqlDBM! I want to thank my bosses, mentors, and colleagues for their support during my time there, especially Anna…
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Data quality, the most boring but essential topic in data At its core data quality can be broken down into six different…
Data quality, the most boring but essential topic in data At its core data quality can be broken down into six different…
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