Test Data Management - Keytorc Approach

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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.com

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Test Data Management - Keytorc Approach

  1. 1. Test Data Management Approach
  2. 2. 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,
  3. 3. Test Data Management - Challenges 1 1. 2. 3. 4. 5. 6. 7. 8. Generic Challenges Big Data Time-to-Market Project Costs Maintaining & Logistics Application Complexity Database Complexity Security Regulations & Laws & Compliance 2 Test Specific 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
  4. 4. Test Data Management - Process Dev. DB Extract Extract Medium Load Production DB Test DB UAT DB De-sensitize Customer Data  Masking Reduce Quantity  Sub-setting Software Solutions
  5. 5. Test Data Management - Lifecycle TD Planning Create/ Modify Application TD Analysis TD Design Create Test Environment Subset TD Execution Test Data Preparation TD Prep. Insert/Edit TD Use TD Maintenance Mask Test Execution Refresh Test Data Check Test Results Extract Compare Script Update Data Update Go LIVE!
  6. 6. 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?
  7. 7. 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
  8. 8. Test Data Management - Test Types/Levels
  9. 9. + More than 350 corporate clients… Testing Center of Excellence Test Automation Services Performance Testing Services Test Maturity Assessments (TMMi, TPI, customized) Value-added Outsourcing Service Level Agreements ISTQB Certified Test Engineers ISTQB Foundation Level ISTQB Advanced Level Test Analyst Technical Test Analyst Test Manager Test Automation Course Performance Testing Course Mobile Testing Course Usability Testing Course
  10. 10. + + Turkey Software Quality Report http://turkishtestingboard.org/turkish/tsqr.htm
  11. 11. + TestIstanbul Conferences http://www.testistanbul.org/
  12. 12. Contact Bize Ulaşın info@keytorc.com blogs.keytorc.com tr.linkedin.com/in/keytorc www.twitter.com/Keytorc Keytorc Software Testing Services

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