NPQS provides data engineering testing services including: - Testing of data integration, ETL processes, data warehouses, OLAP cubes, and reports across various database, ETL and reporting tools. - A team of 70+ ISTQB certified QA engineers with extensive experience testing complex data warehouse architectures and over 10 BI products. - Well defined testing methodologies and the use of test automation tools to test all phases from data integration and ETL to data warehousing to OLAP and reporting.

1. NPQS (Nitor’s Product Quality Services)
Data Engineering Testing

2. Testing Credibility in Data Engineering space
Tested 10+ BI
products
Extensive
experience in
testing complex
DW architecture
Testing across
Database, ETL and
reporting tools
70+ ISTQB
Certified QA
engineers team
Well defined
testing
methodology
Test Automation
Tools

3. Data Engineering Testing Services
Data Integrity
Testing
ETL testing
Data Validation
Testing
OLAP /OLTP
Testing
Data Completeness
Testing
Batch Execution
Testing Report Testing Interface Testing
UI Testing
Performance
Testing Security Testing
Functional
Testing
Test Data
Generation
Data masking
Test Automation

4. Testing in phases
• ODS Data Model
• Field mapping
• Data type constraints
• Integrity constraints
• Parent-Child relationship
• Record counts
• Random record comparison
• Surrogate keys
• Error and Audit logging
• Rejected Record
• Integrated ETL packages
Data source to
Operational Data
Store
• DW Data Model
• Integrity Constraints
• Data type constraints
• Hierarchy Level Integrity
• Derived Columns
• Calculated Columns
• Record Counts
• Null records
• Field to Field Test
• Data Transformation
• Compare transformed data
with expected transformation
• Data Aggregation
• Reversibility of data from DW
to DS
• Data Load confirmation
• Initial Load Test
• Incremental Load Test
• Historical data archival
• Connection Strings
Operational Data
Store to Data
Warehouse • OLAP Design
• Calculated Members
• Irregular Hierarchies
• Aggregations
• Correct Data Filters
• Reversibility of Data
Data Warehouse to
OLAP
• Reports comply with
requirement specification
• Report check (font, color, &
format)
• Graph check (type, color,
legends & labels)
• Report Export in other formats
• Column headings
• Report’s Drill down, Drill Up
and Drill through
• Correct data displayed on
Reports
• Trace data back to the Source
• Response time for Queries
,Users
• Authorized user access
• User friendliness
Data
WarehouseOLAP to
Reports

5. Test Approach
• Validate DW after it is populated
• Identify data related issues at ETL
and Reports
• Identify performance bottleneck
• Data Validation
• Data Integrity
• Data Modeling Testing
• Performance Testing
• Review mapping documents
• Review logs generated by ETL
tools
• Validate data in the DW and
reports
• Accept Logical data model
• Verify physical data model
• Verify DW structure after all
objects are created
• Verify sample data populated in
DW using ETL
• Refresh all reports
• Review data required for each
reports
• Validate new reports against
existing reports
• Conduct end to end testing
• Thoroughly validate key data
elements identified by business
Acceptance
Testing
Integration
Testing
System
Testing
Database
Testing

6. Benefits to Our Partner’s Customer
Accurate data for
decision making
Reduction in the
support cost by
Test Automation
Increase in the
customer
referrals and
there by improve
the revenue
channels
Flawless product
leading to
customer
satisfaction
Test Data
Generation
Engine
Skilled and
certified
dedicated BI
testing team
Functional and
Business
excellence