Big Data and NoSQL have led to big changes In the data environment, but are they all in the best interest of data? Are they technologies that "free us from the harsh limitations of relational databases?" In this month's webinar, we will be answering questions like these, plus: Have we managed to free organizations from having to do Data Modeling? Is there a need for a Data Modeler on NoSQL projects? If we build Data Models, which types will work? If we build Data Models, how will they be used? If we build Data Models, when will they be used? Who will use Data Models? Where does Data Quality happen? Finally, we will wrap with 10 tips for data modelers in organizations incorporating NoSQL in their modern Data Architectures.

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

8. ETL
EDW
Data
Mart
Data
Mart

9. Hadoop
ETL
EDW
Analytics
Mart
Data
Mart

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