GDPR compliance Testing

With the GDPR in force from 25 May 2018, companies must comply with new requirements for EU data protection. As digital business inflates and customers increase their online activities, privacy protection and security is more important than ever. Enterprises that can better respond to the requirements of GDPR, and can do this before their competitors, have an incredible opportunity to build more trust among customers and build a positive business reputation.

This new regulation also has a serious impact on the development and software testing of new systems, creating a roadblock in the process of digital transformation. Corresponding to this current situation, it is essential that software developers and testers have complete knowledge of what impact GDPR has on their business.

In this infographic, we have stated four key reasons why GDPR training is equally important for software developers and testers.

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Contents 1. Testing Point of sales(POS) Systems 2. Areas to Test in a Mobile POS System 3. Types of Testing Needed for POS(Point of Sale) 4. Conclusion

Testing Point of sales(POS) Systems

A point of sales (POS) system is at the hub of every retail business and is a large technology investment. An efficient POS software package increases productivity by reducing unnecessary work and managing the entire business. However, as technology is improvising day by day, POS systems are also evolving with technology.

As omnichannel initiatives are grabbing the attention, retailers are deploying shopping initiatives mobile POS, such as click-n-collect across mobile and other digital channels.

These are innovative ways to provide mobility and freedom to the customers and keep the cash register ticking. However, along with these demand creation opportunities with digital technologies, companies need to be wary of various application pitfalls like unpleasant customer experience, functional issues, payment fraud, security breaches, and server crashes, etc. This necessitates the need for continuous testing through quality assurance, performance management, and security.

Areas to Test in a Mobile POS System

Here are some focus areas that need focus in testing for a mobile POS system.

– Teller Activity: This includes transactions such as the entry of items, tender, Store Value Cards, discounts etc.

– Transactions: Return, exchange, regular sale, sale with credit/ debit/ gift card, loyalty member purchase, items, quantities, and prices.

– Store Server and Integration: Verification of POS interaction with store servers and back-office systems.

– Data of Loyalty Members: The system keeps track of what your customers are buying and who they are. It keeps track of what’s selling, at what times of day or week, to which types of customers and by which salespeople.

– Ability to Read all Cards: There are various types of cards in the industry today such as Magnetic Stripe, CAV, etc.

– Performance: Speed or the time taken to send a request (read) and receive a response and applying the transaction based rules like Rebates/Discounts/Tax etc.

– Negative Scenarios: Several transaction declined scenarios such as invalid card/PIN/expired Card etc.

Types of Testing Needed for POS(Point of Sale)

Here are some major types of software testing that must be implemented for effective omnichannel retailing initiatives:

1. Functional testing:

2. Mobile Testing:

3. Compatibility testing:

4. Load & Performance Testing:

5. Security testing:

6. Big Data/ Analytics Testing:

7. Test Automation:

Conclusion

In the age of digitally connected customers, superior customer experience is critical to the success of the retail industry. TestingXperts has wide industry experience and has been testing the Omnichannel initiatives of global clients from retail industry. Connect with us and identify how we can help you improve the performance and functionality of your mobile POS systems.

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Test data management (TDM) is a critical activity in the testing lifecycle. And this is undergoing continuous refinement with constant changes in the technology landscape and application development process.

Contents 1. Effective Test Data Management Strategy 2. Big Data 3. Service Virtualization 4. DevOps Practices 5. Agile Methodology 6. Conclusion

TDM is highly critical in the testing lifecycle, as the quantum of data generated while testing is massive. Automating the test data helps in minimizing the time spent on processing the data, generating reports faster. However, some key trends have been empowering the TDM strategy. These key trends must be considered while creating an effective test data strategy to reduce time-to-market and improve efficiency. Let’s discuss these trends.

Effective Test Data Management Strategy

Big Data

Big data is a growing technology-driven program, and its strategic significance is growing gradually. With the rapid increase in the adoption of big data, test data architects need continuous data privacy and security solutions. Due to rising breach cases, IT organizations need to expand their data privacy and regulatory compliance initiative by including development and testing environments into the scope. In the current scenario, testing a big data application has become a challenge due to lack of proven test frameworks and toolsets. To set this right, test architects must manage test data and regulatory compliance in their test data strategy.

Service Virtualization

In the world of agile and DevOps, testing the applications need accurate, reliable, and comprehensive test environments. While this can be challenging, testers must execute integration tests on the application with various code versions and test data combinations. Therefore, test data architects need solutions to virtualize application behavior with predefined test data combination. Various organizations are leveraging service virtualization with proper test data configuration as a technique to minimalize costs in the non-production environment.

DevOps Practices

The implementation of DevOps practice promotes collaboration across teams involved in the software development lifecycle. The product, as well as test managers, deliver software in quick cycles and of high quality by continuous integration. A test data architect should leverage database virtualization in TDM for faster provisioning of non-production forms of databases virtually.

Agile Methodology

Agile delivery methods necessitate delivery within shorter delivery cycles with high quality. In every agile sprint, the test teams build, run, and automate tests for which the test data management teams execute data refresh and provide the test data needed to perform the tests. The ideal situation for a test data architect is to ensure optimal data sets with maximum test coverage. This solution helps in completing the testing on time.

Conclusion

Concisely, Test Data Management architects and consultants must be aware of the impact of these major trends on their existing test data strategy. Equipped with this information, they must modify their test data strategy with effective solutions, such as service virtualization, to integrate an ultramodern vision into their Test Data Management strategy. Test data is often generated using existing data. Therefore, the data must be kept confidential to protect the individual’s interest or business interests. Securing the test data is important based on the criticality of the application under test.

At TestingXperts, we have employed robust test data management practices for intricate enterprise platforms. Connect with our experts to improve test effectiveness by using accurate test data and institutionalizing the entire test data management process.

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With the growing demand for regulatory compliance, interoperability and the end-user technology compliance, the healthcare industry has witnessed major changes in the last few years. Technology has been the major transformation point in this industry, wherein applications are being created to deliver quick service anytime anywhere.

Contents 1. 4 major benefits of software testing in the healthcare industry 2. Testing Healthcare Applications Challenges 3. How TestingXperts Can Help!?

Digitalization, being one of the major revolutions seen by this industry, has been helping experts to deliver their services even from a distance. The growing number of healthcare products, such as wearables and the applications associated with them, have created a huge market and had a remarkable effect on the economy.

In fact, over the course of relatively few years, the healthcare and insurance markets have seen rapid, fundamental changes. Some of the changes have been listed below. Thus, healthcare products have the prerequisite to provide precision and accuracy, which has created the need for an extensive healthcare application testing. Software testing is a concept that covers all aspects that can individually impact the quality of the product.

4 major benefits of software testing in the healthcare industry:

Application Security

The sensitive data of patients, including their health info, requires a lot of protection. Healthcare application, if not given proper security, can lead to major breaches. In order to make the application secure and fail-safe, security testing is imperative. It helps in making the application sustainable and foolproof in all sorts of challenging situations.

Effective Execution and Expertise

In order to serve the patients better and effectively, expertise and efficiency are much needed in healthcare systems. Seeing the complex nature of the healthcare applications, it is important to ensure that they function smoothly without any disruptions. Software testing ensures that the application works seamlessly, providing a comprehensive experience to the users.

Big Data Handling

Healthcare industry comprises of a huge amount of data, containing extensive patient information and their respective health conditions. This data holds high importance to the healthcare institutions, as it helps in developing the right strategy and producing relevant products. Big data solutions help in providing informed decisions involving disease cure, research and development, and much more. It is imperative that this data gets tested for a flawless implementation – leading to expected outcomes.

Usability Testing

Usability Testing is crucial to building various user scenarios and features that are faced by the doctors and other staff during their working hours. In usability testing, the same instances are emulated and checked in real-time as well as virtually. These days, automation has made this task easier for testers as it simplifies the whole process. Usability testing also helps in enhancing the user interface and overall experience of the healthcare applications.

However, the new monitoring tools and approaches are posing unexpected challenges and making it more and more difficult to test the healthcare applications. Given below are some challenges that are regularly faced while testing healthcare applications.

Testing Healthcare Applications Challenges

1. Domain and System Understanding

Testers should have appropriate knowledge of the functionality, the clinical usage and the environment in which the software will be used while testing healthcare applications.

2. Security and Vulnerabilities

The healthcare application requires proper security to keep the patient’s records and other confidential data safe. The health app also contains financial data which needs proper security. Testers need to keep the data safe and secure to prevent any hack.

3. Cross Dependency of Software

Complex software has various layers and components. Any change in one component or layer can lead to cause side effects on the other. Testers must ensure that there are no side effects on the other layers whenever any change is made.

Testing in the healthcare industry requires agility and more experienced testers. They must be rigorous and experienced in regards to data integrity, data scrubbing and database queries. In addition, they must be able to leverage automation to generate data and AI to alleviate the risks associated with testing in the healthcare industry.

How TestingXperts Can Help!?

The healthcare industry has entered the dynamic era of new regulations and therapies that require a change in the line of work. TestingXperts, with its excellent domain knowledge, assures clients of one-stop testing services. Our strong QA and test automation capabilities, ideal for testing their enterprise applications and technology infrastructure, is helping our clients in producing world-class health applications.

Our in-house test labs have the necessary talent and infrastructure capable of performing multifaceted and complex testing activities, including R&D software testing, healthcare billing software testing and necessary IT improvements for clinical systems. We are carrying out global healthcare software testing, supporting regulatory requirements and reducing testing costs across the world.

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Business enterprises across the globe are facing common challenges of unpredictability in their business environment, augmented client expectations, technology upgrades. As the business grows, a company’s QA needs do not grow in the same linear fashion. There are peaks and valleys in staffing needs. Businesses that try to manage these needs with internal staffing solutions encounter  challenges such as

– Overstaffing during the valleys – resulting in wasted cost – Understaffing during the peak – longer time to market, resulting in lost opportunity – Pulling non-QA resources into to QA – resulting in opportunity cost (i.e. not doing the other work) and a dip in quality as they are not professional testers – Trying to manage with contractors – resulting in higher training costs and brain drain because as soon as you invest in training someone, the contract ends.  On the next peak, you end up with a different resource, resulting in the need to train a new resource.

Core-Flex Model: The Solution

An independent software testing provider helps clients solve the above challenges with a Core-Flex model. A Core-flex model consists of a dedicated core team that provides business knowledge and process continuity and flex teams that enable rapid scalability to support real-world business dynamics. Implementing a Core-Flex model with an independent QA partner allows companies to maximize productivity of QA and optimize QA expenditures.  In addition, the client can “plug and play” resources with niche skills (performance, big data, API, accessibility, multi-lingual) when needed and roll those resources off when they are not.

TestingXperts’ Core-Flex Model

TestingXperts’ Core-Flex model provides a mechanism to ramp up and down resources to match your needs quickly. In this model, we train an initial team (core team) and additional resources to the address peak team size and specialized skills that may be required (Flex team). On a week by week basis, we coordinate with our clients to ramp up and down the team to match their testing needs. Our clients have the advantage to only pay for resources that they have actually used. The benefits of TestingXperts’ core-flex model include:

– Elasticity in staffing – No brain-drain from resources – Costs aligned with business need – Access to niche testing skills when needed

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Technology trends and digital disruption is transforming the insurance industry immensely. Thus, insurers have been feeling distressed and pressurized to digitize their workflow, and also streamline business processes. These disruptions have been challenging the traditional ways by which the insurance agents and brokers have done business in the past.

Contents 1. Top Technology Trends Transforming the Insurance Industry 2. Cloud-based Infrastructure 3. Leveraging Big Data and Analytics 4. Use of Artificial Intelligence (AI) 5. Conclusion

The insurance industry is executing a modernized workflow, which demands a considerable expansion in the use of technology and that can only be managed by means of hybrid and on-premise cloud infrastructure. The cloud-based infrastructure is guaranteeing flexibility to clients. Besides, it is also helping the insurance sector to comply with the evolving regulatory standards within the industry.

The current application driven economy is all about data. Insurance is an industry that is data-driven which produces huge amounts of structured and unstructured data. Thus, insurance companies are relying on the Internet of Things (IOT) to gather more and more data relating to the behavior of their clients. On the other hand, Big Data and Analytics help insurers take important decisions based on the analysis of gathered data.

Gartner, Inc. forecasts that “8.4 billion connected things will be in use worldwide in 2017, up 31 percent from 2016, and will reach 20.4 billion by 2020. Total spending on endpoints and services will reach almost $2 trillion in 2017.

Regionally, Greater China, North America and Western Europe are driving the use of connected things and the three regions together will represent 67 percent of the overall Internet of Things (IoT) installed base in 2017”

AI has been helping insurance companies develop systems that require manual processing and human intelligence. The advent of Artificial Intelligence in the insurance industry has made it easier for insurance agents to deliver efficient and flawless automation of existing claim processes. In the upcoming days, Artificial Intelligence will be more disruptive and will be used to evaluate and recognize emerging risks.

Gartner predicts that by 2020, AI will be a top five investment priority for more than 30 percent of CIOs.

Source: Gartner, Press Release “Gartner Says AI Technologies Will Be in Almost Every New Software Product by 2020” July 18, 2017

The key to moving towards a digital environment and improving customer service is to automate workflows where required. While standard direct interaction may not be so common between insurance entities, however, their relationship with the client is as important. Intrinsically, insurers need more time to interact with their clients and less time scrolling down documents and sorting papers. This is where automation of workflows helps.

To implement these technology initiatives in the existing and continuously growing technology environment, software testing is imperative.  To be able to cope with the cumulative intricacies of systems and applications, insurance companies need a reliable testing partner.

Conclusion

TestingXperts (Tx) is extensively helping global insurers in their digital transformation and helping them deliver improved customer experience and gain competitive advantage. Tx’s testing services portfolio and unparalleled track record have proved it as a preferred technology partner for the Insurance clients. Connect with us to know more about our testing services specific to the insurance industry.

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Over the last few decades, the world has experienced extensive availability of data, and this exponential growth has been described as ‘Big Data.’ It is a term used to broadly classify the complex and large data sets where data processing applications are considered insufficient.

The evolution of big data has been extraordinary, but it has led to the rise of bad data as well. In this infographic, we will discuss the importance of Big Data Testing in 2017.

Significance of Big Data Testing

The post Significance of Big Data Testing in 2017 first appeared on TestingXperts.

Providing new insights into various industries, Big Data is no longer confined to just being a technology and rather is becoming a business enabler. The insights gleaned from Big Data are playing an integral part in providing solutions to the longstanding challenges of the insurance industry.

Contents 1. Insurance Big Data & Analytics 2. Major areas where Big Data and analytics can make a huge difference 3. The Bottom Line

Insurance Big Data & Analytics

Insurance firms undergo a process of evaluating risks of insuring a person and consequently setting up the premium for the policy. They hold great quantities of data that helps them get acquainted with the existing customers and reach new customers as well. While the industry has made immense progress by analyzing and capturing structured data, the unstructured and untapped data like social media, real-time news feeds, and other channels etc. are also considered as valuable.

In order to succeed in the ever-changing and competitive insurance industry, it’s a no-brainer that insurers must leverage Big Data and analytics. Algorithms based on Big Data can help insurance companies to meet compliance changes, minimize losses and reduce costs.

Five major areas where Big Data and analytics can make a huge difference:

1. Fraud Detection: One of the significant reasons why insurers go through each and every page of the data is to detect fraudulent claims. This process is not only carried out when the claims are registered but also at the onset and at the revival of the lapsed policies. The overburdened job of the insurers makes it difficult for them to manually gather information and sort each one of them. Predictive analysis through big data can help insurers spot the fraudulent material quickly. Methodologies in data analytics like database searches, modeling, text mining & exception reporting can be used in order to identify fraudulent claims.

2. Proper Fund Balancing: There are huge funds maintained by the insurers against potential claims. It is nearly impossible to predict the size of claims or forecast when a claim will arise. Optimization of the reserve fund is, therefore, a huge task that entails a relentless assessment of risk. Insurers, though, spend a decent amount of time in these tasks, predictive and trending analytic tools can release the pressure of this herculean task from the insurers, helping them make correct judgments about optimization and fund balancing.

3. Customer Segmentation: Calculations of the premiums are based on the claim experience of the group of customers. Usually, customers are grouped by the similar age, sex and the term of insurance. Within a particular group, it is possible that customers are present with varying levels of risk. If there is same premium for the whole group, it is possible that customers with low-risk compensate for customers with high-risk. Big data analysis, therefore, can help insurers group their customers better and calculate customized risk-based premiums.

4. Underwriting: Underwriting insurance policies is a huge task for the insurers as it requires assessing a large amount of data. Obtaining the data in the digital form from the proposer can eliminate human errors and also provide greater authenticity in the data. Analysis and processing of the data can also be automated using BI tools and presented in a suitable format to the underwriter. This process significantly accelerates the process of underwriting, further making it error free.

5. Settlement: Complex claims are the ones that take most of the time and it makes sense in putting the most experienced adjuster on that claim. Usually, claims are settled based on various factors such as age, sex, history of the applicant, duration of the insurance etc. Analyzing all factors associated with the insurance and providing claim to the customer becomes a humongous task for the adjuster. Settlement needs a fast-track process that can settle the claims quickly by analyzing the claim histories. Using data analytics, insurers can fast-track the process of claims and garner superior customer satisfaction.

Interesting #blog: 5 Key Areas in the #Insurance Industry where #BigData can make a huge Impact https://t.co/q7AqSWG79L

— TestingXperts (@TestingXperts) September 6, 2016

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