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January 16, 2018

Infosys Business Assurance Store - Fast Forward QA with the power of a Million

Author: Rajneesh Malviya, Vice President and Delivery Head, Infosys Validation Solutions

There is a famous psychological thriller where the protagonist - a patient with anterograde amnesia (short-term memory loss) - sets out on a journey to avenge the death of his beloved girlfriend. To overcome his condition, he uses photographs, notes and tattoos on his body to remind him of various events. I can't help but think that without these cues - these photographs, notes and tattoos - his mission was doomed to fail. So, he needed either his own memory to support him or the presence of some external system that captured memories in different forms. In this particular story, another individual helps him by scanning these notes/photographs to understand the background.

This brings me to the importance of knowledge. Knowledge has always played a pivotal role in any revolution. The success, or failure, of any organization depends on how well it integrates learning with organizational knowledge. Consider how the IT industry depends heavily on knowledge management as its core constituent. Today, artificial intelligence (AI) and machine learning platforms need knowledge to enable decision-making. Even software testing depends on the knowledge (and memory) of software testers for assurance activities.

Over the years, testing has come to rely heavily on business subject matter experts (SMEs). In fact, this is a problem that many of us are still trying to solve by capturing information in any form for future reference. A test case repository is one such knowledge asset that is created by testers and used extensively within and across projects. However, it has some limitations due to its size or variety as an asset as well as its access and reusability. This means that companies continue to depend on individual SMEs for proper testing.

We, at Infosys, with years of domain, technology and business process experience have built an unique solution - Infosys Business Assurance Store. This solution has the knowledge of more than 20,000 testers in Infosys Validation Solutions (IVS) captured in it in the form of test cases with certain mandatory metadata along with well-defined review processes that ensure relevance and quality. The test cases are of various domains, sub-domains, business processes, products, and various technologies that are a part of testing activities. I want to clarify that all the information captured is based purely on their experience and knowledge and this process has not violated any copyright laws. There are more than one million test cases in this solution, probably the first time in testing industry that any testing team has achieved this one million feat!

Infosys Business Assurance Store
The Infosys Business Assurance Store integrates with third-party solutions like HPE Application Lifecycle Management (ALM), MS SharePoint among others. The store helps clients drive greater operational efficiencies and accelerate business agility through improved test design. This solution uses machine learning tools for traceability, knowledge clustering and optimization. Our clients can access the solution through the Infosys Quality Assurance Workbench, an artificial intelligence based platform built for supporting all leading digital technologies such as Mobile, Internet of Things, and Cloud. This unique solution:
  • Fast Forwards the testing lifecycle across industries and specialized testing services
    • 10+ industry domains/verticals
    • 14+ Technology Types
    • 15+ products / packages (VisionPLUS, GPP, Calypso, Murex, Actimize (AML), ETRM, Facets, SAP modules, Oracle EBIS, SFDC, Manhattan WMS etc.)
    • Extensive coverage of risk, regulatory and compliance areas across industry domains viz., KYC, GDPR, FDA/ERES, HIPPA etc.
    • Machine learning tools for traceability, knowledge clustering and optimization
  • Offers extensive risk coverage and helps adhere to different regulatory and compliance standards
  • Integrates easily with third-party solutions and leverages in-built smart search engines
Do reach out to me or our team at marketing_ivs@infosys.com to understand how this unique solution can fast forward your QA.

January 2, 2018

Big data validation for a memorable digital customer experience

Naju D. Mohan, Delivery Manager, Data Services, Infosys Validation Solutions

I have often heard from my colleagues, sales team members and sometimes even clients on what and how exactly do you validate big data and data insights? This is not surprising to me, since big data and occasionally even the insights derived from it is a black box for most of them. For a whole lot of people, it is lots and lots of data which traverses across systems, gets churned by algorithms, which most of us have forgotten after our school years and finally displayed using fancy visualizations making it a mysterious world. Let me make a modest attempt to take you through the journey of big data for a common use case, which we have experienced in our daily lives. I shall take a pause at each step of data flow and explain what has to be tested and how we confirm on data quality. 

Testing to the rescue of big data problem in personalized marketing

At this point in time, when customer demands are changing too often and sky being the limit for customer expectations, those companies which capitalize on delivering personalized experience gets a competitive edge. All companies agree on the fact that success of personalization depends on the quality of data being used.

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 Test it before you ingest obsolete data into your big data system

The primary source of data for personalized marketing comes from the customer's social media activity, online product reviews, online navigation patterns, post purchase history etc. This data comes in huge volumes, at a very high rate and is most often unstructured or semi structured. Companies receive this data from diverse sources and very often struggle to make sense out of this data. The below activities are carried out as part of testing to ensure sanctity of ingested data.

·         Convert the ingested data which is unstructured or semi structured into a comprehensible format

·         Validate the converted data to ensure data completeness during ingestion

·         Validate the data for data truncation to ensure data integrity is preserved

·         Identify missing customer files and dropped customer records through statistical validation

·         Confirm the validity of customer data received from diverse source systems

Improve your big data processing through appropriate testing techniques

Customer data ingested from various sources has to be processed before analyzing it. This includes cleansing of data to get rid of unwanted details, enrichment of data from other systems like master data management, addition of finer details from transaction history etc. Companies sometimes end up sending personalized messages to unintended customers, choose the wrong channel for personal campaigns etc. These mistakes can be avoided by following the below testing approach.

·         Use combinatorial testing methods for optimized test coverage for handling huge data volume

·         Use match and merge validation techniques for data enrichment

·         Validate big data systems to avoid duplicity in records due to integration from various sources

·         Ensure the validity of data in big data environment by comparing it against source of truth

Manage data relevance through testing, while migrating big data

Higher conversion rates and long term revenue through improved customer retention comes with right insights into the customer data and apt slicing and dicing of data. Data is migrated from big data systems to datamarts or data warehouses to drive better results with customer data. The below points should be kept in mind while validating data migration.

·         Validate and remove outlier data to avoid skewed KPIs and incorrect personalized marketing campaigns

·         Validate the correctness of campaign data

·         Ensure the integrity of customer data from across channels while creating aggregates

·         Verify the conformance of available data for privacy and data compliance regulations

 

Test data insights and analytical models for retaining the business upper hand

It is evident that price point is no longer a major factor affecting a customer's purchase decision or buying pattern. Personalization is the key to success and when done across channels makes it all the more attractive. The final power of big data collection, processing and analysis lies in its ability to predict and communicate true and meaningful insights. A focus on the below areas during testing will take the quality of data insights to a new level.

·         Validate the visualization report with respect to all required dimensions

·         The format of data on reports and dashboards have to be validated to the minutest detail. A minor error in a decimal can lead to millions of dollars loss

·         Validate that the analytical models provide optimum predictions for the required scenarios

 

Conclusion

Most personalized marketing may not be 100% effective due to huge data management challenges. So it becomes all the more important to test data during its entire journey, from inception till insights to help companies retain their competitive edge.