You have been data modeling for forever. You've got your data modeling tool features memorized. You've mastered the trips and tricks of how to get models done fast and accurately. You are feeling very confident about your ability to support new database features from SQL Server, Oracle, DB2 and other RDBMSs. But then your Enterprise architect tells you your next project will be using a few NoSQL database technologies. What do you do? What will your data modeling tools do to help you? In this webinar we'll look at the 3 major tools and how they support NoSQL databases. Expect this session to be demo-heavy and bullet points light.

1. Karen Lopez @datachick #HeartData
Heart of Data Modeling
Baseline: NoSQL & Data Modeling Tools

2. Yes, Please do Tweet/Share
today’s event
@datachick #heartdata

3. 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…
She is loves new tech and gadgets

4. How new tech are you?
...so let’s get to know you….

5. Use Q&A
for
formal
questions
Get them in now!
Use chat
to discuss
with each
other
We have a great
community
Yes!
Slides
Recording
…next week…

6. Plan for Today
Why topic?
Very quick overview of NoSQL
Some Demos, Screenshots & What Not
NoSQL Resources

7. Disclaimer…
This is NOT a review
Today’s webinar is to discuss the current state of NoSQL
database/datastore support in the top three data modeling tools
This should be considered a baseline survey, with future webinars
doing updates.

8. Disclosure I am “experienced”
That means at some point I have done
business with these vendors
InfoAdvisors has participated in partner
programs
We are not a partner with any of them
I formally and informally have participated
in Product Advisory groups for vendors

9. Modern Data Architectures
will have hybrid Technologies
WHERE ‘HYBRID’ = ‘SQL
and NoSQL’

10. ETL
Classic DW Architecture
EDW
Data
Mart
Data
Mart

11. Hadoop
ETL
Modern DW Architecture
EDW
Analytics
Mart
Data Mart

12. NoSQL, Not Only SQL
Relational Graph
Columnar/Column
Family
Key Value
Document
Databases
Others (Hadoop,
hybrids, …)
Not the same, but terms
lead to confusion
Databases/datastores/stores

13. Terminology
Native Support
•Direct Connection
•Feature & version
aware
Round-trip
engineering
•Forward
•Reverse
•Compare
ODBC generic
connectivity
•ODBC-JDBC
•Others
Import-Export
•MetaIntegration
•XML
•..hacks…
•Excel
•Macros

14. Requirements
Data Model
Database*
More
requirements
/ changes /
tuning /
whims
+ Non Model Stuff
Data Model
Driven
Data Model Driven

15. Graph Databases
CREATE (matrix1:Movie { title : 'The Matrix', year : '1999-03-31' })
CREATE (matrix2:Movie { title : 'The Matrix Reloaded', year : '2003-05-07' })
CREATE (matrix3:Movie { title : 'The Matrix Revolutions', year : '2003-10-27' })
CREATE (keanu:Actor { name:'Keanu Reeves' })
CREATE (laurence:Actor { name:'Laurence Fishburne' })
CREATE (carrieanne:Actor { name:'Carrie-Anne Moss' })
CREATE (keanu)-[:ACTS_IN { role : 'Neo' }]->(matrix1)
CREATE (keanu)-[:ACTS_IN { role : 'Neo' }]->(matrix2)
CREATE (keanu)-[:ACTS_IN { role : 'Neo' }]->(matrix3)
CREATE (laurence)-[:ACTS_IN { role : 'Morpheus' }]->(matrix1)
CREATE (laurence)-[:ACTS_IN { role : 'Morpheus' }]->(matrix2)
CREATE (laurence)-[:ACTS_IN { role : 'Morpheus' }]->(matrix3)
CREATE (carrieanne)-[:ACTS_IN { role : 'Trinity' }]->(matrix1)
CREATE (carrieanne)-[:ACTS_IN { role : 'Trinity' }]->(matrix2)
CREATE (carrieanne)-[:ACTS_IN { role : 'Trinity' }]->(matrix3)
http://neo4j.com/docs/stable/cypherdoc-movie-database.html

16. Tools and Graph Databases
•No native supportERwin
•No native supportER/Studio
•No native supportPowerDesigner
“the data model
is the database”
“the database is
the data model”
ODBC / JDBC connectively for
querying.

17. Key Value Pair
http://www.dummies.com/how-to/content/keyvalue-pair-databases-in-a-big-data-environment.html

18. Key Value Pair
Database
Table: PriceCompare
LocationID ProductBySellerID ProductProperties
123 013803204131 {Seller:“Camera Superstore”,
Price:425.99, PriceDate:2014-11-06,
SellerType:”Online”}
Row Key PropertiesPartition Key

19. Tools and Key Value DBs
•No native supportERwin
•No native supportER/Studio
•No native supportPowerDesigner
I’m thinking that
“our” data models
fit best as data
stories/polices/meta
data for now.

20. Columnar Data Storage
Enhancements to SQL Server Column Stores, Per-Åke Larson, et al,
SIGMOD

21. Fn Ln AreaCode Phone StNum StName StType City State
A Disney 661872-4547 111Wilson Dr Bakersfield CA
Al Disney 530778-3737 222Main St Lewiston CA
Amy Disney 209577-5824 410Park Av Santa Rosa CA
Anita Disney 559642-4472 89Ahwahnee St San Diego CA
Anita Disney 209966-4472 781Mariposa Dr Napa CA
Ann Disney 949830-1883 3Amato Ct Yountville CA
Original Table
Fn
A
Al
Amy
Anita
Anita
Ann
Ln
Disney
Disney
Disney
Disney
Disney
Disney
AreaCode
661
530
209
559
209
949
Phone
872-4547
778-3737
577-5824
642-4472
966-4472
830-1883
StNum
111
222
410
89
781
3
StName
Wilson
Main
Park
Ahwahnee
Mariposa
Amato
StType
Dr
St
Av
St
Dr
Ct
City
Bakersfield
Lewiston
Santa Rosa
San Diego
Napa
Yountville
State
CA
CA
CA
CA
CA
CA
Split in Columns
Fn
A
*l
*my
*nita
*****
***
Ln
Disney
******
******
******
******
******
AreaCode
661
530
2*9
***
***
*4*
Phone
872-4547
***-3*3*
***-****
6**-****
9**-****
**0-1***
StNum
111
222
4*0
89
7**
3
StName
Wilson
Ma**
P*rk
*hw***e*
***i****
***t*
StType
Dr
St
Av
**
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C*
City
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L*wi*ton
S**** ****
*** Diego
Napa
Yountville
State
CA
**
**
**
**
**
Encoded and Compressed

22. Tools and Columnar & Column Family
•No native supportERwin
•No native supportER/Studio
•SAP HANAPowerDesigner
I was able to reverse HP
Vertica, mostly, using all
three tools via ODBC
connection.
Meta Integration
Bridget helps
import/export

23. Document Databases

24. Tools and Document DBs
•No native supportERwin
•MongoDBER/Studio
•No native supportPowerDesigner

25. MongoDB with Native Connection, Rev Eng

26. Hive
SQL-like query language
Abstraction on top of MapReduce
Metastructure on top of HDFS

27. Tools and Hive
•Hive, many flavorsERwin
•Hive, genericER/Studio
•Hive, genericPowerDesigner
Since Hive was
developed
based on ANSI
SQL standards, it
make sense that
SQL-focused
tools support it.

28. Hive SQL

29. Question Break
IF Question(You) THEN Answers(Datachick)
END IF

30. Let’s look at some tools…

31. CA ERwin Data Modeler

32. SAP PowerDesigner

33. Embarcadero ER/Studio

34. Question Break
IF Question(You) THEN Answers(Datachick)
END IF

35. So let’s summarize:
The more SQL-like features available for NoSQL databases,
the more likely a data modeling tool is to support it.
Modeling tool vendors will support features that users ask
for cause them to win deals. This is not a bad thing.
Serious NoSQL vendors* understand that hybrid is the
enterprise data story. They want us to find a way.
Our data models have value, even if the NoSQL solution
doesn’t require a lot of constraints.

36. Community.embarcadero.com

37. ERwin.com

38. Erwin-knowledgebase.com

39. scn.sap.com/community/powerdesigner

40. sybase.public.powerdesigner.general

41. 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.

42. And it’s FREE!
GraphDatabases.com

43. 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.

44. PostgreSQL
Riak
Hbase
MongoDB
Neo4J
CouchDB
Redis

45. nosql2015.dataversity.net

46. nosql2015.dataversity.net

47. Modern Data Modeler Involvement
Project Initiation
Architecture and
Infrastructure
Design
SW
Requirements
Development
Deployment

48. “Every design decision
should include cost,
benefit and risk”
- Karen Lopez

49. It’s fun
Database technologies aren’t YES/NO decisions
It’s inexpensive to learn
It’s fast to spin up a learning environment
A data professional needs to knows more than one tool
Using the right tool for the right job is key
It’s fun
7 Reasons to Go Explore

50. MicrosoftAzure.com
•MSDN Subscription
Benefit
•Trial Accounts
Go Explore!

51. Thank you, you were great.
Let’s do this next month!
Karen Lopez @datachick
#heartdata