KEMBAR78
DWBI Testing and Analytics Testing Services | PPTX
Empowering your journey towards digital excellence
codetru.com
Visit Our Website
queries@codetru.com | +1-312-584-0489 - Ext: 339
350+
Head Count
50+
Active Clients
300+
Total Clients
4
Global Offices in US & UK
1
Delivery Center in India
2012
Codetru established
with exceptional
passion & broader
vision
2019
•Introduced Mobile and Web
Development offering.
•Opened a new Mobile
Application Testing Lab
2021
•Built Solutions for Large firms (Asian
Paints, Trustiphi & Innophos)
•Supported numerous Digital
Transformation Journeys success
fully.
2024
On track to achieve 6x
growth rate
2018
•Increased team to 50+.
•Setup a new office
location
2020
•Increased workforce by 60%
•Withstood the chaos of
Covid
2022
•Achieved 3x revenue generation
•Added more digital offerings
Insurance E-Commerce & Retail Banking & Finance Energy, Travel & Logistics
Healthcare Telecom, Hi Tech, ISV Education Entertainment & Media
Clientele
Service Offerings
• Mobile & Web
Development
• UI / UX Development
• Application Maintenance
& Support
• Application Modernization
& Migration
• Custom Application
Development
• Application Integration
• Cross-platform Support
Application
Development
QA & Software
Testing
DevOps &
Automation
Data
Analytics
AI-ML
Managed IT
Services
• Functional Testing
• Non-functional Testing
• Specialized Testing
• Testing Advisory
• CI / CD Delivery
• Configuration
Management
• Release Management
• Monitoring & Logging
• Process Automation
• Cloud Migration
• Analytics & BI
• Data Modernization
• Cloud Services
• BI Strategic Services
• Machine Learning and
Model Development
• Natural Language
Processing [NLP]
• AI Chatbots
• Data Preparation &
Management
• Model Deployment &
Integration
• AI Consulting
• Data Management
• Big Data
• Social BI
• Data Warehousing
• BI Strategic Services
• BI Application Services
• Server Automation
• Managed Hostings
• Virtualization Services
• End-user Computing
Quality Assurance & Software Testing
• ERP Testing
• Web & Mobile Testing
• IoT Testing
• Blockchain Testing
• AI-ML Testing
• Cloud Testing
• DWBI Testing
• Manual Testing
• Test Automation
• Performance Testing
• Security Testing
Functional Testing Non-functional Testing
Spcialized Testing
Core
Testing
Core Testing
Core
Testing
Functional
Regression
System
Integration
Test
Management
Consulting
Automation Testing
Automation
Plan
Framework
Design
Development
Execution
Acceptance
Maintenance
Automation
Testing
Tools & Technologies: Tools & Technologies:
QA Competency
Corporate growth
Mergers,
acquisitions, and
restructuring of
disparate
systems
Compliance
Validations against
regulations and
standards i.e. HIPAA,
PCI, SOX.
Data volume
Escalating
amounts of data
Data diversity
New data formats
like RFID, SMS, and
e-mail- increases
complexity.
Data decay
Data deterioration at a
rate of 10 percent to 25
percent per year
Data denial
Organizations
unaware of their
data quality
issues
Technical
advances
Proliferation of
new data devices
(IoT), platforms,
and operating
models
Economic
factors
Pressure to use data
for competitive
advantage
Drivers of Data Complexity
Following is the Architecture of a typical data warehouse specifying the source data, the target data warehouse and various
data marts.
Legacy
DB
CRM/ERP
DB
Finance
DB
Source Data ETL Process Target DW ETL Process Data Mart
BI
The architecture below depicts the various types of testing that can be performed for any data warehouse testing engagement
Functional Testing
Non – Functional
Testing
Data Validation Testing Report Testing Integration Testing Backup & Recovery Testing
Performance Testing Security Testing
Regression Testing
User Acceptance Testing
DWBI Testing
The complexity and criticality of data warehouse testing projects is growing rapidly each day. Data warehouses need to be
validated for functionality, quality, integrity, availability, scalability and security based on the defined business requirements by
an organization.
Testing the Data warehouse basically includes testing of the following:
 Conceptual Schema
 Logical Schema
 ETL Procedures
 Database
 Front-end
The following is the mapping of testing types and the areas of to be tested:
Conceptual
Schema
Logical
Schema
ETL
Procedures
Database Front-end
Functional Testing    
Usability   
Performance    
Back-up & Recovery  
Security   
Regression     
Data Warehouse Testing
Key Points for BI Testing:
1. Complexity of the data is the major challenge as large number of data sources are involved.
2. BI reports use flash and other technologies that create problems for traditional test automation.
3. It is difficult to use traditional testing tools to automate the testing of BI applications built using tools such as OBIEE, Cognos
and Business Objects
4. BI testing can be done using tools like Motio CI, BI Validator, etc.
5. These tools helps to diagnose problems faster by eliminating manual tests and also reducing development costs
BI Application Testing
Data Validation
Testing
 Data
Completeness
 Data Quality
 Data Cleanness
 Field to Field
Testing
 Constraint Testing
 Source to Target
Testing
 Business Rules
Checks
 Granularity
 Aggregation
 Data Refinement
Report Testing
 Standards,
Prompts, Drill
Down, Summary,
Look & Feel,
Graphs / Charts,
Measures /
Dimensions
 Verify report data
with the data
source
 Create SQL queries
to verify
source/target
data
Backup & Recovery
 Data Recovery
 Data Backup
 E-mail functionality
 Audit Logs Standards
User Acceptance
Testing
 End User
Representative
 Validate Usability
Integration Testing
 ETL Modules
Integration
 DB-Report
Integration
 Verify the initial
load of records and
the incremental
loading of records
on data warehouse
 Test error log
generation
Data Warehouse / BI Functional Testing
Functional Testing of Data Warehouse / BI includes
The objective of this testing to ensure that System meets the security and performance expectations of the business users. It
aims to prove that the entire system operates effectively in a production environment and that the system successfully supports
the business processes from a user's perspective.
Performance Testing Security Testing
Load the database with peak expected production
volumes to ensure that this volume of data can be loaded
by the ETL process within the agreed-upon window
Compare these ETL loading times to loads performed
with a smaller amount of data to anticipate scalability
issues. Compare the ETL processing times component
by component to point out any areas of weakness
Monitor the timing of the reject process and consider
how large volumes of rejected data will be handled
Perform simple &multiple join queries to validate
query performance on large database volumes.
Work with business users to develop sample queries
and acceptable performance criteria for each query
ETL Security Checks
• The front-end applications must not be accessible from
outside company network
• Data entry points of the warehouse needs to be secure
Database Security Checks
• Sensitive data is accessible only by certain people
• Data movement needs to be monitored
Reports Security Checks
• User must access Reporting and OLAP with only specific
credentials
Data Warehouse / BI Functional Testing
Level 1
Sampling
Sampling a % of
data by visually
comparing
data sets. Not
repeatable.
Excel,
Ad Hoc Reporting
Level 2
Using Excel or other
homegrown method.
Ad hoc reporting.
Level 3
Utilizing SQL editor &
minus queries to test
data. More detailed
reporting.
Data Test
Automation
Level 4
Queries
Fully repeatable
test automation,
centralized
reporting.
Data Quality
Optimizing
Level 5
Full automation, tracking of
ROI, predictive data issues,
auditable history & results.
Business value is fully
understood/supported by
management.
Data Testing Maturity
Consulting & Strategy
Automation
Feasibility
Strategy
ROI
Assessment
Tool
Evaluation
POC
Test Lifecycle
Initiate
• Requirement Review
• GAP Analysis
• Test Strategy Creation
• Traceability Matrix
• High-level Test Plan
Plan
• Test Case Writing
• Set-up Test Environment
• Set-up / Plan Test Tools
• Set-up Defects
Management Process
• Detail Test Plan
Execute
• Execute Test Cases
• Report Defects & Re-testing
• Automation Designing & Scripting
• Automation Script Execution
Report
• Defect Logs
• Test Summary Reports
• Defect Trends
• QA Metrics
• Improvement Process Initiation
Approach
Dynamic & Flexible Staffing
• Dynamic Flexible Staffing
• Access to Field Experts
• Ramping Up and Down of
Resources
• Access to Missing Skills
Consultancy Services
• On-going Professional Support
• Access to talent pool
• QA Efficiency and & Effectiveness
Improvement
• End-to-end Needs Management
• Dedicated Testing Team
• Continuous Asset Building
Managed Testing Services
Fixed Term Services
• Set-term Outsourcing
• Project-based Agreement
• Resource Availability
at Key Milestones
1 2
3 4
QA Engagement Model
Mobile Web J2EE
QA and Testing Ecommerce Cloud & Data
Skillset
Why Codetru
Experience & Expertise
Quality of Service
Innovative Approach
Strong Market Sense Competitive Pricing
Faster Resource Turnaround
60+ Successful Projects
30% Less Testing Cost
9+ Industries Served
50+ Automation Testers 30+ Key Clients
100+ Total Testers
Codetru Highlights
Success Stories
codetru.com
Visit Our Website
Problem Statement
The client, a leading technology company, was developing an innovative
solution to automate their existing manual process. The solution was
intended to simplify the process and improve productivity. They wanted
to ensure that the product was thoroughly tested and bug-free before
launching it in the market. Our team was responsible for providing QA and
testing services to the client, including test planning, test execution, and
test reporting.
Our team faced several challenges during the project. Firstly, the client's
team was working on an Agile development process, which meant that
the requirements were continuously evolving, and we had to be flexible in
our testing approach. Secondly, the client had a tight timeline, and we
had to ensure that we delivered the project within the given timeframe.
Thirdly, the application was complex, and there were several integration
points that required thorough testing.
Solution :
To address the challenges, we adopted a comprehensive testing
approach that involved the following:
• Test Planning: Our team worked closely with the client to understand
the requirements and developed a test plan that aligned with their
needs.
• Test Design: Based on the requirements, our team developed test
cases, test scenarios, and test scripts that covered all aspects of the
application.
• Test Execution: We conducted functional, integration, and regression
testing to ensure that the application worked as expected.
• Test Reporting: We provided regular test reports that highlighted the
progress of testing, identified defects, and suggested corrective
actions.
• Deploying the Python Utility: Once the utility was tested and verified,
the team deployed it on a Windows server and scheduled it to run at
regular intervals using the Windows Scheduler.
Result :
Our team successfully delivered the project within the given timeline,
and the client was satisfied with the quality of our work. We identified
several defects during the testing phase, which we resolved promptly.
Our approach helped the client improve the overall quality of their
product, and they were able to launch it in the market successfully.
Technologies Used:
Tools: Selenium, JMeter, Appium, TestComplete
Coding Language: Python
Success Story #1
THANK YOU
codetru.com
Visit Our Website
+1 312 584 0489 Ext. 339 | +919505013139
queries@codetru.com | codetru.com

DWBI Testing and Analytics Testing Services

  • 1.
    Empowering your journeytowards digital excellence codetru.com Visit Our Website queries@codetru.com | +1-312-584-0489 - Ext: 339
  • 2.
    350+ Head Count 50+ Active Clients 300+ TotalClients 4 Global Offices in US & UK 1 Delivery Center in India 2012 Codetru established with exceptional passion & broader vision 2019 •Introduced Mobile and Web Development offering. •Opened a new Mobile Application Testing Lab 2021 •Built Solutions for Large firms (Asian Paints, Trustiphi & Innophos) •Supported numerous Digital Transformation Journeys success fully. 2024 On track to achieve 6x growth rate 2018 •Increased team to 50+. •Setup a new office location 2020 •Increased workforce by 60% •Withstood the chaos of Covid 2022 •Achieved 3x revenue generation •Added more digital offerings
  • 3.
    Insurance E-Commerce &Retail Banking & Finance Energy, Travel & Logistics Healthcare Telecom, Hi Tech, ISV Education Entertainment & Media Clientele
  • 4.
    Service Offerings • Mobile& Web Development • UI / UX Development • Application Maintenance & Support • Application Modernization & Migration • Custom Application Development • Application Integration • Cross-platform Support Application Development QA & Software Testing DevOps & Automation Data Analytics AI-ML Managed IT Services • Functional Testing • Non-functional Testing • Specialized Testing • Testing Advisory • CI / CD Delivery • Configuration Management • Release Management • Monitoring & Logging • Process Automation • Cloud Migration • Analytics & BI • Data Modernization • Cloud Services • BI Strategic Services • Machine Learning and Model Development • Natural Language Processing [NLP] • AI Chatbots • Data Preparation & Management • Model Deployment & Integration • AI Consulting • Data Management • Big Data • Social BI • Data Warehousing • BI Strategic Services • BI Application Services • Server Automation • Managed Hostings • Virtualization Services • End-user Computing
  • 5.
    Quality Assurance &Software Testing • ERP Testing • Web & Mobile Testing • IoT Testing • Blockchain Testing • AI-ML Testing • Cloud Testing • DWBI Testing • Manual Testing • Test Automation • Performance Testing • Security Testing Functional Testing Non-functional Testing Spcialized Testing
  • 6.
  • 7.
    Corporate growth Mergers, acquisitions, and restructuringof disparate systems Compliance Validations against regulations and standards i.e. HIPAA, PCI, SOX. Data volume Escalating amounts of data Data diversity New data formats like RFID, SMS, and e-mail- increases complexity. Data decay Data deterioration at a rate of 10 percent to 25 percent per year Data denial Organizations unaware of their data quality issues Technical advances Proliferation of new data devices (IoT), platforms, and operating models Economic factors Pressure to use data for competitive advantage Drivers of Data Complexity
  • 8.
    Following is theArchitecture of a typical data warehouse specifying the source data, the target data warehouse and various data marts. Legacy DB CRM/ERP DB Finance DB Source Data ETL Process Target DW ETL Process Data Mart BI The architecture below depicts the various types of testing that can be performed for any data warehouse testing engagement Functional Testing Non – Functional Testing Data Validation Testing Report Testing Integration Testing Backup & Recovery Testing Performance Testing Security Testing Regression Testing User Acceptance Testing DWBI Testing
  • 9.
    The complexity andcriticality of data warehouse testing projects is growing rapidly each day. Data warehouses need to be validated for functionality, quality, integrity, availability, scalability and security based on the defined business requirements by an organization. Testing the Data warehouse basically includes testing of the following:  Conceptual Schema  Logical Schema  ETL Procedures  Database  Front-end The following is the mapping of testing types and the areas of to be tested: Conceptual Schema Logical Schema ETL Procedures Database Front-end Functional Testing     Usability    Performance     Back-up & Recovery   Security    Regression      Data Warehouse Testing
  • 10.
    Key Points forBI Testing: 1. Complexity of the data is the major challenge as large number of data sources are involved. 2. BI reports use flash and other technologies that create problems for traditional test automation. 3. It is difficult to use traditional testing tools to automate the testing of BI applications built using tools such as OBIEE, Cognos and Business Objects 4. BI testing can be done using tools like Motio CI, BI Validator, etc. 5. These tools helps to diagnose problems faster by eliminating manual tests and also reducing development costs BI Application Testing
  • 11.
    Data Validation Testing  Data Completeness Data Quality  Data Cleanness  Field to Field Testing  Constraint Testing  Source to Target Testing  Business Rules Checks  Granularity  Aggregation  Data Refinement Report Testing  Standards, Prompts, Drill Down, Summary, Look & Feel, Graphs / Charts, Measures / Dimensions  Verify report data with the data source  Create SQL queries to verify source/target data Backup & Recovery  Data Recovery  Data Backup  E-mail functionality  Audit Logs Standards User Acceptance Testing  End User Representative  Validate Usability Integration Testing  ETL Modules Integration  DB-Report Integration  Verify the initial load of records and the incremental loading of records on data warehouse  Test error log generation Data Warehouse / BI Functional Testing Functional Testing of Data Warehouse / BI includes
  • 12.
    The objective ofthis testing to ensure that System meets the security and performance expectations of the business users. It aims to prove that the entire system operates effectively in a production environment and that the system successfully supports the business processes from a user's perspective. Performance Testing Security Testing Load the database with peak expected production volumes to ensure that this volume of data can be loaded by the ETL process within the agreed-upon window Compare these ETL loading times to loads performed with a smaller amount of data to anticipate scalability issues. Compare the ETL processing times component by component to point out any areas of weakness Monitor the timing of the reject process and consider how large volumes of rejected data will be handled Perform simple &multiple join queries to validate query performance on large database volumes. Work with business users to develop sample queries and acceptable performance criteria for each query ETL Security Checks • The front-end applications must not be accessible from outside company network • Data entry points of the warehouse needs to be secure Database Security Checks • Sensitive data is accessible only by certain people • Data movement needs to be monitored Reports Security Checks • User must access Reporting and OLAP with only specific credentials Data Warehouse / BI Functional Testing
  • 13.
    Level 1 Sampling Sampling a% of data by visually comparing data sets. Not repeatable. Excel, Ad Hoc Reporting Level 2 Using Excel or other homegrown method. Ad hoc reporting. Level 3 Utilizing SQL editor & minus queries to test data. More detailed reporting. Data Test Automation Level 4 Queries Fully repeatable test automation, centralized reporting. Data Quality Optimizing Level 5 Full automation, tracking of ROI, predictive data issues, auditable history & results. Business value is fully understood/supported by management. Data Testing Maturity
  • 14.
    Consulting & Strategy Automation Feasibility Strategy ROI Assessment Tool Evaluation POC TestLifecycle Initiate • Requirement Review • GAP Analysis • Test Strategy Creation • Traceability Matrix • High-level Test Plan Plan • Test Case Writing • Set-up Test Environment • Set-up / Plan Test Tools • Set-up Defects Management Process • Detail Test Plan Execute • Execute Test Cases • Report Defects & Re-testing • Automation Designing & Scripting • Automation Script Execution Report • Defect Logs • Test Summary Reports • Defect Trends • QA Metrics • Improvement Process Initiation Approach
  • 15.
    Dynamic & FlexibleStaffing • Dynamic Flexible Staffing • Access to Field Experts • Ramping Up and Down of Resources • Access to Missing Skills Consultancy Services • On-going Professional Support • Access to talent pool • QA Efficiency and & Effectiveness Improvement • End-to-end Needs Management • Dedicated Testing Team • Continuous Asset Building Managed Testing Services Fixed Term Services • Set-term Outsourcing • Project-based Agreement • Resource Availability at Key Milestones 1 2 3 4 QA Engagement Model
  • 16.
    Mobile Web J2EE QAand Testing Ecommerce Cloud & Data Skillset
  • 17.
    Why Codetru Experience &Expertise Quality of Service Innovative Approach Strong Market Sense Competitive Pricing Faster Resource Turnaround 60+ Successful Projects 30% Less Testing Cost 9+ Industries Served 50+ Automation Testers 30+ Key Clients 100+ Total Testers Codetru Highlights
  • 18.
  • 19.
    Problem Statement The client,a leading technology company, was developing an innovative solution to automate their existing manual process. The solution was intended to simplify the process and improve productivity. They wanted to ensure that the product was thoroughly tested and bug-free before launching it in the market. Our team was responsible for providing QA and testing services to the client, including test planning, test execution, and test reporting. Our team faced several challenges during the project. Firstly, the client's team was working on an Agile development process, which meant that the requirements were continuously evolving, and we had to be flexible in our testing approach. Secondly, the client had a tight timeline, and we had to ensure that we delivered the project within the given timeframe. Thirdly, the application was complex, and there were several integration points that required thorough testing. Solution : To address the challenges, we adopted a comprehensive testing approach that involved the following: • Test Planning: Our team worked closely with the client to understand the requirements and developed a test plan that aligned with their needs. • Test Design: Based on the requirements, our team developed test cases, test scenarios, and test scripts that covered all aspects of the application. • Test Execution: We conducted functional, integration, and regression testing to ensure that the application worked as expected. • Test Reporting: We provided regular test reports that highlighted the progress of testing, identified defects, and suggested corrective actions. • Deploying the Python Utility: Once the utility was tested and verified, the team deployed it on a Windows server and scheduled it to run at regular intervals using the Windows Scheduler. Result : Our team successfully delivered the project within the given timeline, and the client was satisfied with the quality of our work. We identified several defects during the testing phase, which we resolved promptly. Our approach helped the client improve the overall quality of their product, and they were able to launch it in the market successfully. Technologies Used: Tools: Selenium, JMeter, Appium, TestComplete Coding Language: Python Success Story #1
  • 20.
    THANK YOU codetru.com Visit OurWebsite +1 312 584 0489 Ext. 339 | +919505013139 queries@codetru.com | codetru.com