SlideShare a Scribd company logo
YourModerator
Karen Lopez
Sr. Project Manager / Architect
Infoadvisors
@datachick
#BCDModeling
JoiningKaren
Dan McCreary
Principal
Kelly-McCreary & Associates
@dmccreary
NoSQL And Data Modeling
Big Challenges in Data Modeling
Making Sense of NoSQL clearly
and concisely explains the
concepts, features, benefits,
potential, and limitations of
NoSQL technologies. Using
examples and use cases,
illustrations, and plain, jargon-
free writing, this guide shows
how you can effectively
assemble a NoSQL solution to
replace or augment the
traditional RDBMS you have
now.
Data Models – Traditional Process
Conceptual
(Data)
Model
Logical
Data Model
Physical
Data
Model(s) OLTP
OLTP
OLTP OLTP
OLTP
MARTMART
OLTP
OLTP
OLTP
NoSQL Data Store Types
• Key Value
• Graph
• Columnar
• Document
• XML
• ….more?
Traditional Data Modeler Involvement
Project
Initiation
Architecture
and
Infrastructure
Design
SW
Requirements
Development
Deployment
Modern Data Modeler Involvement
Project
Initiation
Architecture
and
Infrastructure
Design
SW
Requirements
Development
Deployment
ETL
EDW
Data
Mart
Data
Mart
Hadoop
ETL
EDW
Analytics
Mart
Data
Mart
“Every design decision should
include cost, benefit and risk”
• - Karen Lopez
10 Tips For Modeling in a Hybrid World
1. Models require a modeler
2. Data modeling tools are essential – choose wisely
3. There are many types of data models: know which ones
you need
4. Modeling does not have to happen at the same time in
every project. It should happen at the right time
5. Modeling is not just schema design. Think outside the
boxes and lines
10 Tips for Modeling in a Hybrid World
6. A data model is much more than a diagram
7. You will need training. More than you think.
8. Team members may not understand modeling.
They will need training
9. NoSQL is not one thing. Learn many patterns
10.Modern data architectures are likely hybrid
solutions. You can’t just support one part.
This book is written for anyone
who is working with, or will be
working with MongoDB, including
business analysts, data
modelers, database
administrators, developers,
project managers, and data
scientists.
See you 24 July
Big Data - Myths, Misunderstandings and Mistakes
Thank you!
Karen Lopez
@datachick

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Big Challenges in Data Modeling: NoSQL and Data Modeling

  • 1. YourModerator Karen Lopez Sr. Project Manager / Architect Infoadvisors @datachick #BCDModeling JoiningKaren Dan McCreary Principal Kelly-McCreary & Associates @dmccreary
  • 2. NoSQL And Data Modeling Big Challenges in Data Modeling
  • 3. Making Sense of NoSQL clearly and concisely explains the concepts, features, benefits, potential, and limitations of NoSQL technologies. Using examples and use cases, illustrations, and plain, jargon- free writing, this guide shows how you can effectively assemble a NoSQL solution to replace or augment the traditional RDBMS you have now.
  • 4. Data Models – Traditional Process Conceptual (Data) Model Logical Data Model Physical Data Model(s) OLTP OLTP OLTP OLTP OLTP MARTMART OLTP OLTP OLTP
  • 5. NoSQL Data Store Types • Key Value • Graph • Columnar • Document • XML • ….more?
  • 6. Traditional Data Modeler Involvement Project Initiation Architecture and Infrastructure Design SW Requirements Development Deployment
  • 7. Modern Data Modeler Involvement Project Initiation Architecture and Infrastructure Design SW Requirements Development Deployment
  • 10. “Every design decision should include cost, benefit and risk” • - Karen Lopez
  • 11. 10 Tips For Modeling in a Hybrid World 1. Models require a modeler 2. Data modeling tools are essential – choose wisely 3. There are many types of data models: know which ones you need 4. Modeling does not have to happen at the same time in every project. It should happen at the right time 5. Modeling is not just schema design. Think outside the boxes and lines
  • 12. 10 Tips for Modeling in a Hybrid World 6. A data model is much more than a diagram 7. You will need training. More than you think. 8. Team members may not understand modeling. They will need training 9. NoSQL is not one thing. Learn many patterns 10.Modern data architectures are likely hybrid solutions. You can’t just support one part.
  • 13. This book is written for anyone who is working with, or will be working with MongoDB, including business analysts, data modelers, database administrators, developers, project managers, and data scientists.
  • 14. See you 24 July Big Data - Myths, Misunderstandings and Mistakes Thank you! Karen Lopez @datachick