On the surface, it appears that digital transformation has swept the globe. Automating repetitive tasks has freed up resources to concentrate on adding value to people’s lives, jobs, and organizations. This has been accomplished by integrating various interconnected devices and providing solutions that improve operations, effectiveness, and results.
Some of the key technologies that are transforming digital technologies are:
- Artificial Intelligence/Machine Learning
- Internet of Things
- Factors Driving the Need for Digital Assurance of Future Tech Applications
- Automated Quality Assurance with Modern Technologies
- Indium for Digital Assurance
- Its quality assurance stack includes:
Artificial Intelligence/Machine Learning
Artificial Intelligence (AI)/Machine Learning is at the heart of digital transformation and quite pervasive, powering many solutions, improving personalization, and enhancing user experiences. AI/ML systems run on natural language processing algorithms that convert unstructured data to structured data. This brings in an element of uncertainty and ensuring that they function as expected can be a big challenge as the algorithms are trained to learn based on user activity and evolve to enhance user experience, supporting human intelligence to improve outcomes.
Internet of Things
The Internet of Things devices are also becoming ubiquitous, empowering humans with smart devices that improve their efficiency and effectiveness. IoT devices contain embedded systems, controlled by an application, and connected to a network that allows data to be gathered and uploaded to the cloud. This data is further used for analytics and developing ML models.
Non-fungible tokens or NFTs have become popular for the easy money, or cryptocurrency, that people are making by selling art on the net. But that’s not the only use for NFTs. It is, in fact, a highly secure solution for digital assets and is also used for creating smart contracts based on blockchain technology. It leaves an audit trail of transactions, preventing fraud and improving traceability.
These and many such technologies have disrupted the way businesses run and enhance user experience. However, the extent of digital transformation through automation and resource reallocation is limited by the ability of different components to interact smoothly with each other. The digital ecosystem is continually evolving, and people and processes are becoming more interconnected through multiple channels like mobile, social, analytics, and cloud stack. This is creating a complex environment. And any lapse or lag in this environment will cause interruptions and disruptions. Performance can become an issue if the underlying engine or the data is not performing as expected or of the right quality. Managing these complexities associated with digital transformation is where digital assurance and quality testing come in.
Also read: The Role of IoT in Metaverse
Factors Driving the Need for Digital Assurance of Future Tech Applications
Complex Digital Ecosystem
The various components of digital transformation, including mobile, social, analytics, and cloud, need to be synchronized to deliver the desired objectives. This is very complex due to the varying levels of maturity of the solutions and the organizations embracing these technologies.
Greater Security Threats
As systems become more intelligent, so do the hackers and malicious elements. IoT devices also leave enterprise systems vulnerable due to the interconnection of applications across devices, especially at the edge. This has increased the need for tighter security solutions that are properly configured, constantly tested, and revised to meet evolving challenges.
Often, businesses with legacy systems continue to retain on-premises systems for a part of their operations. This requires digital solutions to be able to access legacy IT infrastructure without impacting core functionalities.
Enhancing Customer Experience
There is no predictability as to how a customer will access the services. Therefore, ensuring a uniform experience across the four pillars of the digital ecosystem becomes essential. Each component must deliver optimum performance throughout the business journey and enhance customer delight.
Agility and Shorter Time-to-Market
Shorter delivery cycles have become very critical to ensure agility in a highly dynamic digital environment. It requires not only faster development cycles but also quality assurance to keep pace.
A digital-first approach in the modern business world requires business models and customer strategies to match the fast-paced transition at every stage of the journey. Traditional testing and automation are not equipped to meet these challenges and ensure the required quality assurance, security, performance, and functionality needs are met. The traditional QA processes and infrastructure also need to match the new need and be powered by modern technologies. They require an AI-based testing framework to enable machine learning and continuous improvement of testing for new technologies such as AI and IoT.
Automated Quality Assurance with Modern Technologies
Test automation and quality assurance help meet several of the development goals. They accelerate testing, improve outcomes, and shorten the time to market.
Some of the key emerging technologies in digital quality assurance and testing are:
Shift-Left Approach to Testing
In the (traditional) waterfall approach, apps would be tested after the development is complete and before the production stage. But today, organizations use a Shift Left approach where the testing team gets involved right at the beginning of the software development process to identify and prevent defects early.
Codeless Test Automation
Codeless test automation involves no code. It enables the democratization of testing by empowering citizen testers to build test use cases with object, data, model, and keyword methods. User-friendly interfaces allow even the uninitiated to easily understand the scripted testing tools and use them effectively to debug at every stage of the development process.
Artificial intelligence and machine learning enable the prediction of the test script and write test cases appropriate to the requirements. These technologies help create multiple frameworks such as linear scripting, data-driven hybrid testing, modular testing and such. In keyword-driven codeless frameworks, a table format is used to define keywords or action words that execute the function. Behavior-driven framework allows tests to be written in plain, descriptive English. With NLP-driven frameworks, Natural Language can be used to write the test steps.
NLP and keyword-driven frameworks have gained popularity as they are easy to use, and allow test cases to be written seamlessly in a simple, natural language that can be easily interpreted and understood. They also help draw insights from unstructured data for improved decision-making.
Data Quality Assurance
Since data is at the core of all modern technologies, the quality of the data also becomes crucial. The data should be complete, deduplicated, have integrity, and be relevant. This requires data to be screened and cleansed of anomalies for achieving expected outcomes.
Indium for Digital Assurance
Indium Software has all-round experience in development, quality assurance, testing, and DevOps. This lethal combination enables it to leverage the latest technologies to create frameworks that can be easily customized to meet the varying digital assurance requirements of different enterprises. Indium has more than 22 years of QA experience and provides end-to-end assurance services that shorten delivery cycles and improve customer experience.
Its quality assurance stack includes:
Covers functional QA, performance assurance, test data management, smart test automation, and business value chain testing.
Covers CX testing, testing of API/microservices to QAOps, low-code platform testing, data assurance, and Smart Assisted Testing
Future Tech Digital Assurance
Covers QAOps and digital assurance for IoT-enabled apps, Non-Fungible Tokens (NFT), and Blockchain, and testing of AI engines and models
Test Advisory & Consulting
Helps clients with QA Maturity Assessment and develop the overall test and test automation strategy for DevOps and Agile environments.
To learn more about our test automation platform for testing IoT, AI, and other future-tech applications and our digital assurance services.
With digital assurance, the quality of the digital transformation projects is assured, and meeting business goals is made that much easier.