You can watch the replay for this Geek Sync webcast, Avoid the Seven Mistakes Data Modelers Make in Aiding Data Governance, in the IDERA Resource Center, http://ow.ly/nCrq50A4q8G. Data privacy, protection, and compliance legislation is becoming ever more important. In that context, organizations have been looking towards their data governance teams to make sure that they understand their data, know how it is classified, and where it resides. In this session, join Karen Lopez in discussing the mistakes that data modelers make in supporting data governance programs — and that you should avoid! These mistakes include collaboration errors, data model security fails, data stewarding missteps, data model integrity harms, and more. Newer compliance regulations can make these mistakes costly and difficult to recover from. Karen wants you to love your data — and your data model! Speaker: Karen Lopez has more than 20 years of database design experience. She specializes in the practical application of design approaches, balancing development time frames with the need to deliver solutions that will support business agility and data quality needs. She’s known for her fun and engaging speaking and teaching style. She tweets about data, space exploration and her travel experiences at @datachick. Karen blogs at www.datamodel.com.

1. Avoid the Seven Mistakes Data Model
ers Make in Aiding Data Governance
Karen Lopez, Data Evangelist
InfoAdvisors
www.datamodel.com

2. Karen Lopez
• 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 be
#TeamData®

4. Why this
topic?
Data Modeling + Data Governance = WIN
Buzz
More focus on compliance
Governance + Data Models
Teamwork FTW

5. Failing to Leverage Data
Catalogs/Portals
Data Inventory is a business need

7. Data Model
Portal + Data
Catalog
Model diagrams
Model content
Glossaries
Cross model searches
Commentary/engagement

8. © 2016 IDERA, Inc. All rights reserved. Proprietary and confidential.© 2020 IDERA, Inc. All rights reserved. 8

9. © 2016 IDERA, Inc. All rights reserved. Proprietary and confidential.© 2020 IDERA, Inc. All rights reserved. 9

10. © 2016 IDERA, Inc. All rights reserved. Proprietary and confidential.© 2020 IDERA, Inc. All rights reserved. 10

11. © 2016 IDERA, Inc. All rights reserved. Proprietary and confidential.© 2020 IDERA, Inc. All rights reserved. 11

12. Portals and Data Catalogs

13. Commentary in Data Models

14. Tips
• Leverage Portals and Catalogs
• Feed/Subscribe to other catalogs
• Encourage commentary
• Encourage engagement

15. Not Understanding Data
Compliance Impacts
Data Compliance is a business need

17. DATA SENSITIVITY
CLASSIFICATION
Identifying sensitive
data
Attribute/Column
Names
Data profiling
Data definition
Labeling data
Financial
PII
GDPR/CCPA
Sharing data with
its label
First Name (PII)
Credit Card Number
(Financial)
Special Meal Request
(HIPAA)

20. Data
Protection
Security is a business
requirement
Business requirements
in LDM
Implementation in PDM

21. Tips
• Use tools to classify your data
• Analyze data
• Update LDM
• Update PDM

22. Assuming Data Modeling is About
Databases Only
Data Understanding is a business need

24. Purposes of a Data Model
Recording
Recording decisions
Explaining
Explaining concepts
Establishing
Establishing
requirements
Designing
Designing for data
Implementing
Implementing for data

25. Data Models
Need to be targeted to:
• Audience
• Purpose
• Project* status
• Review goals

26. “Other” Uses
SOLUTIONS
EVALUATION
TRAINING ONBOARDING INTEGRATION
MODELS
ART

27. Tips
• Present tailored data models
• Make them highly available (paper and
online)
• Use them…

28. Ignorning Data Security & Privacy
Requirements
Data Security is a business need

30. Data Security Requirements
• Encryption
• Masking
• Row Level/Column
Level
• Access (CRUD)
• Lifecycle

31. Encryption
• Storage/file level
• Column level
• Database level
• Database + network +
client

32. Data Masking
Applying a
pattern to a
column to mask
that data
Karen Kxxxxxx
1234 5678 9999 1234 **** **** **** 1234
15 April 2020 1 January 1990
$125,000.00 $0.00
karen@infoadvisors.com K******@*******.com

34. Row Level Security
Restricts
access to
certain rows
or columns
in a table
Doctors should only be able to see
data (rows) or patients to which
they are assigned
Salespeople should see only data
for the region to which they are
based
Non-HR people should not see
salary amounts

35. Access Levels & Lifecycles
• Role-based access
• User-based access
• CRUD

36. Tips
• Collaborate with security groups
• Get business requirements
• Add to LDM
• Add to PDM
• Collaborate with DBAs and Devs

37. Making the Logical Data Model
Technically Intimidating
Data Modeling is a business need

40. Add Callouts

42. Tips
• Use Text Boxes
• Use Hover Tips
• Limit content
• Have multiple layouts
• Use tool features to manage

43. Making the Data Model Difficult to
Review
Data Clarity is a business need

44. Let’s just look at some examples…

45. Pain Points
• Handwriting fonts
• Difficult fonts
• Difficult fonts
• Too small fonts
• Ugly fonts
• Low Contrast Colors

51. Scaling
 Save paper, yes
 Fit-to-Page is nice
 But…it’s not always a good thing
 Scale for readability first

52. Tips
 Use Templates
 Require Templates
 Get graphics designer help
 Standardize fonts
 Sample models are problematic 

53. Data Models Go Unused
Data Collaboration is a business need

54. Reasons Unused Data Models
• Silo-based organization
• “Agile”
• Availability
• Hard to use
• Not model-driven development

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

56. How?
Forward Engineering
Reverse Engineering
Round Trip Engineering
Validation Checks
Repository Collaboration
Measure Compliance
Reuse

57. Repository Collaboration

58. Tips
 Data Model Driven Development
 Data governance at each phase
 Use Repository for collaboration
 Use Team Server for collaboration
 Use data models for collaboration

59. What does this
mean to a Data
Modeler/Architect?
Use Data Models for several
purposes, with multiple presenations
Understanding when to use where to
manage meta data: Data Modeling
Tools or Data Governance tools
Understanding the difference
between Data Governance and Data
Policing

60. White Paper

61. 61

62. Karen Lopez
DataModel.com