Analytics QA

The success of your business is based on Accurate business intelligence. Any discrepancies in your data can lead to wrong decisions. Even your Analytical tools need to undergo Quality Assurance like any other software system. Indium software with its expertise in both Analytics and QA ensures your analytical application is of the highest quality.

Unlike the traditional QA process, Analytics QA requires specific experience with data. Indium Software’s experienced data engineers know how to handle your raw data and turn them into analytics output that helps you make informed business decisions.

Our Analytics QA team possesses expertise in advanced analytics algorithms, modelling, numerical computing, commercial and open source packages for analytics and data science, and deployment of systems embedding advanced analytics.

Data To Insights Through Rigorous Testing

Analytics QA Process

Indium software’s QA for analytics helps guide implementation and identify bugs that could turn your judiciously gathered business intelligence into a chaotic mass of unusable data. It also requires experience in the nuances of not only what can go wrong with collecting data but also how data can be incorrectly interpreted into a wholly misleading assessment. Our Quality engineers engage directly with your development teams and operate seamlessly to provide the analytics output that helps get your product to market on time.

data-collection

Data Collection

data-mining

Data Mining

data-segregation

Data Segregation

data-manipulation

Data Manipulation

data-aggregation

Data Aggregation

data-validation

Data Validation

Test Approach

Service Offerings

Our service offerings ensure that our testing expertise bridges the gap in your analytics process. The following are our capabilities in functional and non-functional testing services.

Functional Testing

data-validation-Analytics_qa

Data Validation

[Extraction | Aggregation | Bussiness Rules]

  • Data Model Analysis
  • Boundary Value Analysis
  • Static and Dynamic Value Simulations
  • Data Types (Consistency & Relevance)
common-features-analytics-qa

Common Features

[Navigation | Search | Sort and Filter | Paging]

  • Role Based View
  • Navigation Flow
  • Schedulers / Timeliness
  • User Interactivity
  • Response time and Authenticity
  • Sequence of Feature Actions
  • Configurations
regression-testing-analytics-qa

Regression Testing

  • Component Dependent Matrix
  • Requirement Traceability

Non-Functional Testing

ui-testing-analytics-qa

UI Testing

  • Design and Alignments
  • Responsiveness (Dynamic Resizing During Run Time Scenarios)
  • UI Adaptability Scenarios
usability-testing-analytics-qa

Usability Testing

  • Design Conventions
  • Navigation Tools, Readability and Hygiene Components
  • Accessibility Testing
compactability-testing-analytics-qa

Compactibility Testing

  • Data Source Compactability
  • Browser Compactability
  • Platform Compactability
  • Device Compactability
specialized-qa

Specialized QA

  • Performance / Stress Testing
  • Scalability
  • Integration Testing
  • Security Testing
  • Migration Testing

Why Indium?

Seasoned QA Experts

Experts who have loads of industry knowledge and can understand the domain.

Process Oriented

Define a dynamic process depending on the fluctuating requirement

Engaging the right people

Our team is a mix of QA analyst and Data Engineers.

Efficiency through Automation

Our QA team can design custom validators that ease data validation task and improves data accuracy