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World®
’16
High	Performance	Masking	and	Test	
Data	Generation	for	IMS	and	DB2
Prashant	Pandey
CA	Technologies
MFX59E
MAINFRAME	AND	WORKLOAD	AUTOMATION
2 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
©	2016	CA.	All	rights	reserved.	All	trademarks	referenced	herein	belong	to	their	respective	companies.
The	content	provided	in	this CA	World	2016	presentation	is	intended	for	informational	purposes	only	and	does	not	form	any	type	of	
warranty. The information	provided	by	a	CA	partner	and/or	CA	customer	has	not	been	reviewed	for	accuracy	by	CA.	
For	Informational	Purposes	Only	
Terms	of	this	Presentation
3 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Abstract
With	fines	averaging	millions	of	dollars,	and	prohibitively	high	
infrastructure	costs,	masking	and	subsetting the	mainframe	is	a	must.	
This	session	will	cover	how	the	CA	Test	Data	Manager	architecture	
avoids	the	dire	security	and	performance	implications	of	moving	data	to	
and	from	z/OS.	
Prashant	
Pandey
CA	Technologies
Sr Principal	Consultant,	
Presales
4 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Test	Data	on	z/OS	(the	Bad	News)
§ z/OS	system	of	record	(70%	data	still	resides	here)
§ Many	organisations	rely	on	copies	of	Production	for	testing
§ Secure	and	reliable	in	production	– what	about	test?
§ What	and	Where	is	PII	data
§ Legislation	– GDPR,	demonstrate	compliance
§ Breach	Notification	– reputation	&	fines	risk
§ Cost	of	moving	test	data	to/from	platform
(the	Good	News)	Best	Practice	Test	Data	Management	already	addresses	this	impact
5 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
What	is	Test	Data	Management	(TDM)?
‘…	is	the	practice	of	applying	a	structured	and	centralized	approach	to	
the	management	of	test	data	at	an	enterprise	level,	in	order	to	reduce	cost	
whilst	increasing	efficiency	and	quality	in	development	and	testing’
6 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
CA-Test	Data	Manager	Deployment	&	Process
1. Centralize
2. Discover
3. Subset
4. Mask
5. Synthesize
6. Find	&	Reserve
7. Automate
Synthetic/Clone	Data
Masked
Subset
Created
Production
Development
Web		- SOA	Test	Harness
Virtualization
Data	Masking
Subsetting/Data	Slicing
Data	Profiling
Coverage	Metrics
Agile-Designer
Test	Design
Data	Design
Test	Data	on	Demand
UI	- Load	Test	Harness
Test	Mart
Find	and	Reserve
REQUEST/RESPONSE	POOLS
VERSION	CONTROLEXPECTED	RESULTS
REGRESSION	PACKS	
DATA	DRIVEN	TEST	PACKS
TEMPLATES
Agile-DataHP	ALM/QC
Automation
Data	Visualization
Javelin	–Data	Orchestration
7 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
CA-Test	Data	Manager	Deployment	&	Process
Adabas
z/Series
IMSDB2
VSAM
Unisys
DMSII
LUW
Informix
MSSQL
Oracle
Teradata
DB2/400 Flat	Files	
(CSV,	Excel,	
XML	etc.)
i/Series
Windows	UI
ODBC/JDBC
COBOL/JCL
JAVA
SQL
LUW
CA	– Test	Data	Manager
Register	&	Profile
Define	Test	Data
Engineering	Operation
Process	Run-time
Enable	as	
On-Demand	Request
Test	Data	
On-Demand
IMGR	&	Service	Layer
Oracle	or	SQL	
Server	
Repository
8 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Secure		
Masked	
Subsets	of	
Data
Mainframe	
Environment
DB2	z/OS
VSAM
IMS
non-indexed	flat	files
Other	DBs
Validation
Profiling
PII	Discovery
Data	Subset	Definition
Built-In	Masking	Functions
Synthetic	Data	Rules
Rules	and	
Definitions
Meta	Data
Secure	and	effective	test	data	engineering	on	Mainframe
CA	TDM
Windows	Workbench
Data	never	has	to	leave	the	Mainframe
Mainframe	
Batch	Operation
Rules
Repository	
(Rules	and	Meta	Store)
PDS	
JCL	&	CTL)
FTP
ODBC/Copybooks
9 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
End-End	Integrity
§ Across	multiple	source	(and	platforms!)
– z/Series:	DB2,	IMS,	VSAM	(KSDS,	ESDS,	etc.)	or	flat	files	(PS)	etc.
– i/Series	– AS400:	DB2/400
– Distributed:	Oracle,	SQL	Server,	DB2	UDB	etc.
– File	structures:	CSV,	Excel,	XML,	SOAP,	REST,	JSON	etc.
Maintaining	database,	business	and	logical	integrity
CustID Item# Order	Date
07221 80-25442 2015-01-25
07221 80-25442 2015-03-14
CustID Item# Order	Date
10002 80-25442 2015-02-15
10002 80-25442 2015-05-19
Data	retains	structure,	context	and	referential	integrity	but	does	not	contain	“real”	information.	
CustID Name SSN Street
08052 Andrew	Chapman 181-23-7171 87	Featherbed Lane
09112 Brian James 112-32-4435 12	Park	Lane
08052 Andrew	Chapman 181-23-7171 87	Featherbed Lane
07221 Tom	Angle	 771-11-8972 8	Boardwalk
CustID Name SSN Street
10000 Hikaru Sulu 545-95-1245 87	Featherbed Lane
10001 Nyota Uhura 802-41-3411 12	Park	Lane
10000 Hikaru Sulu 545-95-1245 87	Featherbed Lane
10002 Pavel	Chekov 325-74-6517 8	Boardwalk
10 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Project	and	Version	Centralized	Control
§ Re-usable	assets	in	a	Test	Data	
Warehouse
§ Provides	a	central	library	of	test	data	
engineering	operations	
§ Assets	can	be	upgraded	across	versions	
(releases)
§ Regression	packs	can	be	stored
CA	Test	Data	Manager	Test	Data	Warehouse	(Repository)
11 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Automatically	discover	sensitive	data	stored	enterprise-wide
§ Powerful,	mathematically-based	
algorithms	discover	and	tag	all	sensitive	
data,	enterprise-wide
§ Simple, easy	to	use	filtering	by	tag	when	
selecting	columns	or	tables	to	mask
§ Support	for	every	major	database	type,	
mainframe	platforms and	flat	files
CA	Test	Data	Manager	Data	Profiler
12 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Subsetting:	data	sets	are	extracted	based	on	exact	criteria
CA	Test	Data	Manager	Data	Subset
Referentially	intact	subsets	of	data
Production	Attributes
Scenario	Subset
Covered	Subset
Production	&	Enhanced	
Attributes
13 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
De-sensitize	millions	of	rows	of	referentially	intact	data	in	minutes
CA	Test	Data	Manager	Fast	Data	Masker
These	include	substitution,	randomization,	hashing	and	seed	
data.	Once	created,	masking	rules	can	be	stored	and	re-used	
from	a	central	repository.
GT	Fast	Data	Masker	will	only	display	suitable	masking	routines,	
based	on	the	selected	column	and	tables
Deterministic	masking	functions	and	built-in	cross-referencing	
ensure	consistency.	The	referentially	intact,	realistic	data,	can	be	
injected	into	multiple	systems	at	once
Number	of	Rows Time	to Mask
201,722,392 9	minutes, 42	seconds
453,877,152 11	minutes,	22	seconds
768,088,071 7	minutes,	57	seconds
17,422,541 1	minute
46,579,485 1	minute, 25	seconds
1,759,612 13	seconds
47,	895 5	seconds
GT	Fast	Data	Masker	uses	native	database	scripts	to	
produce	the	highest	possible	performance	when	masking	
Oracle,	MS	Server,	Teradata	and	mainframe	platforms
§ Mask	millions	of	rows	of	data in	
minutes	using	native	masking	engines
§ Over 80	built-in	data	masking	functions
§ Replacements	with	realistic,	
referentially	intact,	 applied	to	multiple	
systems
§ Demonstrate	Compliance	with	the	EU	
GDPR,	GLBA,	HIPAA,	PCI	DSS,	PIPEDA,	
and	more
14 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Generate	Required	Data	Scenarios
CA	Test	Data	Manager	Synthetic	Data	Generation
This	means	that	new	data	can	efficiently	and	quickly	
injected	into	existing	databases	for	exactly	the	
requirements	you	need	
§ Extensive	algorithms	for	Synthetic	data	applied	
in	a	Data	Painter	style
§ Use	Symbolic values,	combine functions,	
include conditional values	and	mine data	from	
other	sources	into	the	new	data
§ Publish	(inject/load)	single	data	object	as	
multiple/varied	new	rows	in	existing	database	
§ Store	data	objects	centrally,	as	re-usable	assets	
in	a	Test	Data	Warehouse
§ Data	can	be	re-used	across	versions	and	
releases,	with	versioned	regression	packs
15 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Find	&	Reserve	Existing	Data
CA	Test	Data	Manager	Test	Matching
SAP-1
Data	Attribute	
Mining
Data	Test	
Conditions
Datamaker	Test	Matching
DB-2
XML
Matched	Test
QTP	Scripts
16 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Combine	TDM	Operations	to	Provide	Comprehensive	Set	of	Data
Referential Integrity
Profiling
PII Discovery
Native DB Engines
Seed Replacement
Audit
CA	Test	Data	Manager
1 2 3
Secure	Data	
Subsets
Test/Dev	
Environments
Gold Copy
Subset
Seed
Tables
Built-in Masking
Functions
Cross
Referencing
Masked
Generated Scenarios
Find & Reserve Data
Synthetic	
Content
Synthetic	
Content
Production	data	sources	and	files
XML	Files
Excel	
Files
SQL	Files
CSV	Files Fixed	Definition	
Files
HTML	Files
VSAM/ISAMSwift
TXT	Files
Test	
Data
Warehouse
17 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Avoid	costly	mistakes	when	managing	z/OS	Test	Data
Avoid	use	of	raw	production	data	is	a	mandatory	operation	for	modern	organizations.	The	average	cost	per	
incident	of	data	breach	worldwide	is	$3.5m.	In	the	US,	the	risk	was	as	high	as	$5.85m1.	
In	as	many	as	59%	of	these	incidents,	the	risk	could	have	been	mitigated	by	implementing	Test	Data	
Management	best	practices
1
Ponemon Institute,	2014
CA	TDM	allows	users	to	apply	Test	Data	Management	practices	directly	on	the	mainframe reducing	the	
reliance	on	slow,	expensive	Extract,	Transform	and	reload	technologies	to	ensure compliance	and	take	
advantage	of	fit-for-purpose	test	data.	
Processing	data	directly	on	the	mainframe can	provide	teams	with	millions	of	rows	of	high	quality,	
meaningful,	referentially	intact	data,	in	a	short	period	of	time	and	at	less	risk	to	quality!
18 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Recommended	Sessions
SESSION	# TITLE DATE/TIME
MFX58EC	
CA	Testing	Tools	Educational	Session	(Part	3	of	3):	CA	
Mainframe	Application	Tuner	Demo	and	What's	New
11/15/2016	at	2:00	pm
MFX112S	 Mainframe	Application	Development	Portfolio	Review 11/16/2016	at	12:45	pm
MFT148S	
Achieve	DevOps	on	the	Mainframe	for	Faster	Time	to	
Market	
11/16/2016	at	4:30	pm
19 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Must	See	Demos
Continuous	Development	and	
Testing
Mainframe	Theater
Continuous	Delivery
Mainframe	Theater
20 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Questions?
21 ©	2016	CA.	ALL	RIGHTS	RESERVED.@CAWORLD				#CAWORLD
Thank	you.
Stay	connected	at	communities.ca.com
@CAWORLD					#CAWORLD ©	2016	CA.	All	RIGHTS	RESERVED.22 @CAWORLD					#CAWORLD
Mainframe	and	Workload	Automation
For	more	information	please	visit	ca.com/appdev
Prashant	Pandey
Sr Principal	Consultant,	Presales
prashant.pandey@ca.com

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Pre-Con Ed: High Performance Masking and Test Data Generation for IMS and DB2