test data management - keytorc approach
DESCRIPTION
While the companies are making the use of information oceans and derive profits from the data they store; at the same time they suffer from it. It is obvious that no company can cope with data growth by just increasing their hardware capacity. Companies need to find out smart solutions for this inevitable growth. When we degrade the subject into testing, we observe that IT organizations are deeply focusing on the collection and organization of data for their testing processes. The ability to control this process and use test data has become the key competitive advantage for these organizations because benefits of such mechanisms will worth against their tradeoffs. Ultimately, test data management plays a vital role in any software development project and unstructured processes may lead organizations to; •Do inadequate testing (poor quality of product) •Be unresponsive (increased time-to-market) •Do redundant operations and rework (increased costs) •Be non-compliant with regulatory norms (especially on data confidentiality and usage) No matter which approach you choose to eliminate the challenges of this important subject, test data management; basic requirements for you to be successful are; combination of good test cases and test data, along with the proper usage of tools to help you automating extraction, transformation and governance of the data being used. Test Veri Yönetimi Yazılım testlerinin etkinliğini belirleyen en önemli unsurlardan bir tanesi kullanılan test veri setidir. Testlerin dar bir test veri setiyle yapılması: - test kapsamının düşmesine - testlerin yanlış sonuçlar vermesine - canlıda beklenmeyen hataların çıkmasına neden olmaktadır. Test veri setlerinin optimum seviyede doğru verilerle oluşturulabilmesi için iki kritik başarı faktörü bulunmaktadır. 1-Milyonlarca test verisi içerisinden test kapsamını belli seviyede sağlayak test veri kümesinin oluşturulabilmesi için uluslararası test tekniklerinin kullanılması - Denklik sınıfı test tekniği (equivalance partitioning test technique) - Sınır değer test tekniği (boundary value test technique) - Pairwise test tekniği - Combinatorial test tekniği - …. 2- Doğru test veri yönetimi aracının seçilmesi - Canlı ortamdaki verileri maskeleyerek test verisi oluşturan araçlar - Girilen veri tiplerine uygun rastgele test verisi yaratan araçlar Test veri yönetimi ile ilgili daha fazla bilgi almak için: Test veri yönetimi ile ilgili yaklaşımımızı içeren sunumu görmek için tıklayınız: http://www.slideshare.net/keytorc Keytorc’un test veri yönetimi konusunda uzman ekibiyle iletişime geçmek için:www.keytorc.com ya da blogs.keytorc.comTRANSCRIPT
Test Data ManagementApproach
Test Data Insights
Testing determines the quality of any product,
Test data determines the quality of testing,
Testing accounts up to 60% of development lifecycle,
Data-related tasks occupy about 60% of Application Development and Testing time.
Test Data Preparation accounts about 50% of total test effort,
Over 50% of business data can be considered confidential,
Test Data Management - Challenges
1. Quality of Testing
2. Data Preparation
Efforts
3. Control of Multiple
Test Environments
4. Test Data Consistency
5. End-to-end traceability
of test data
6. Invalid Defects due to
test data anomalies
7. TDM Tool Selection &
Utilization
8. Skilled TDM Specialists
1. Big Data
2. Time-to-Market
3. Project Costs
4. Maintaining & Logistics
5. Application Complexity
6. Database Complexity
7. Security
8. Regulations & Laws &
Compliance
Generic
Challenges1 Test Specific
Challenges2
Test Data Management - Process
De-sensitize Customer Data Masking
Reduce Quantity Sub-setting
Dev.
DB
Extract
Medium
Production
DB
ExtractTest
DB
Software
Solutions
UAT
DB
Load
Test Data Management - Lifecycle
Compare
Check Test
Results
Test Data
Preparation
Create Test
Environment
Create/ Modify
Application
Test
Execution
Go LIVE!Refresh Test Data
Extract
Subset
Insert/Edit
Mask
TD Planning
TD Execution
TD Maintenance
TD Analysis
TD Design
TD Prep.
TD Use
Script Update
Data Update
Test Data Management - Data Requirements
What kind of data is needed?
How much data is needed?
When is the data needed?
Who will need the data?
Where will the data be loaded?
What are the dependencies?
What type of testing will the data be used for?
How will the data be secured/de-sensitized?
How will the data be managed?
How will the data be updated/refreshed?
Test Data Management - Objectives
In order to be efficiently used for any test activity, Test Data should
possess the following characteristics;
Reliable
Accessible
Complete
Consistent
Integral
Error-Free
Secure
Relevant
Timely
Test Data Management - Test Types/Levels
ISTQB Foundation LevelISTQB Advanced Level
Test AnalystTechnical Test AnalystTest Manager
Test Automation CoursePerformance Testing CourseMobile Testing CourseUsability Testing Course
Value-added OutsourcingService Level AgreementsISTQB Certified Test Engineers
Testing Center of ExcellenceTest Automation Services Performance Testing ServicesTest Maturity Assessments
(TMMi, TPI, customized)
More than 350 corporate clients…+
+Turkey Software Quality Report+
http://turkishtestingboard.org/turkish/tsqr.htm
TestIstanbul Conferences+
http://www.testistanbul.org/
Bize Ulaşın
www.twitter.com/Keytorc
blogs.keytorc.com
tr.linkedin.com/in/keytorc
Contact
Keytorc Software Testing Services