{"id":11969,"date":"2020-12-11T10:44:56","date_gmt":"2020-12-11T05:14:56","guid":{"rendered":"https:\/\/cigniti.com\/blog\/?p=11969"},"modified":"2021-04-07T16:42:11","modified_gmt":"2021-04-07T11:12:11","slug":"software-testing-world-big-data-ai-smart-machines-iot-robotics","status":"publish","type":"post","link":"https:\/\/www.cigniti.com\/blog\/software-testing-world-big-data-ai-smart-machines-iot-robotics\/","title":{"rendered":"Software Testing in the world of Big Data, AI, Smart Machines, IoT, 5G, & Robotics"},"content":{"rendered":"
By the e<\/span>nd of 2024, 75% of organizations will shift from piloting to operationalizing AI<\/span>, predicts Gartner. Rita Sallam, distinguished research vice president at Gartner says, \u201c<\/span>To innovate their way beyond a post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts<\/span>\u201d.<\/span>\u00a0<\/span><\/p>\n Next-gen technologies are proving monumental in accelerating enterprise digital transformation and enabling organizations to facilitate process excellence. At the same time, software testing and QA is also playing a pivotal role in ensuring the tri-factor benefit of speed, value, and quality.<\/span>\u00a0<\/span><\/p>\n Now, this can be massive, and in many ways AI will be implemented for conducting a range of activities including interaction with the end users\/consumers. This holds true for almost every technology that has been gaining popularity and enabling businesses \u2013 Big Data, Smart Machines, IoT, and Robotics. While it is important for enterprises to leverage these technologies, it is also necessary for them to adopt it with full confidence and ensure its relevance for their business. New technologies will work for a business only when they are mapped against its business goals.<\/span>\u00a0<\/span><\/p>\n Quality Assurance and Software Testing help enterprises to adopt technologies with an objective to bring business value. In this context, organizations evaluate how Agile\u00a0<\/span>development\u00a0<\/span>can help them with their digital transformation efforts, why implementing DevOps is becoming a top priority, and how it can enable them to understand their consumers better and address their requirements.<\/span>\u00a0<\/span><\/p>\n AI in the\u00a0<\/span><\/b>land\u00a0<\/span><\/b>of Software Testing<\/span><\/b>\u00a0<\/span><\/p>\n AI is definitely gaining momentum and is being implemented across diverse industries. AI helps systems to perform tasks that would traditionally need human intellect. A computer can be fed with huge amount of data sets, which then adds logic and patterns to come up with relevant inferences. QA and\u00a0<\/span>testing\u00a0<\/span>are very much required for establishing a valid connection between similar input and output pairs.<\/span>\u00a0<\/span><\/p>\n Automation Testing<\/a> is needed to ensure that the results derived are relevant and in line with the business objectives. For instance, AI bots can now successfully communicate by giving human inputs and\u00a0<\/span>perform<\/span>\u00a0a whole range of activities. However, its performance will totally depend on the input of right dat<\/span>a and its effective processing.<\/span>\u00a0<\/span><\/p>\n Growing need for Big Data Testing<\/span><\/b>\u00a0<\/span><\/p>\n Gartner<\/span>\u00a0estimate<\/span>s<\/span>, \u2018<\/span>b<\/span>y 2023, more than 33% of large organizations will have analysts practicing decision intelligence, including decision modeling. Decision intelligence brings together several disciplines, including decision management and decision support. It provides a framework to help data and analytics leaders design, model, align, execute, monitor and tune decision models and processes in the context of\u00a0<\/span>business outcomes and behavior.\u2019<\/span>\u00a0<\/span><\/p>\n Gartner\u00a0<\/span>has\u00a0<\/span>coined the term \u201cX analytics\u201d to be an umbrella term, where X is the data variable for a range of different structured and unstructured content such as text analytics, video analytics, audio analytics, etc.<\/span>\u00a0<\/span><\/p>\n The core objective of Big Data testing is to ensure data completeness, enable data transformation, confirm quality of data, and automate analytical activities. The overall technology movement and effectiveness depends massively on the exchange of data. Whether it is robotics, machine learning, smart devices, or Internet of Things (IoT), Big Data is at the core of it.<\/span>\u00a0<\/span>Moreover, Big Data testing ensures that the data derived from diverse data sets bring business value and profitability in the long run. For instance, marketing teams will need quick analysis of consumer data to substantiate their claims and understand the consumer much better.<\/span>\u00a0<\/span><\/p>\n Robotics and the changing dynamics<\/span><\/b>\u00a0<\/span><\/p>\n Robotic process automation (or RPA) is implemented to help employees of an organization to configure computer software or a robot for processing a transaction, working on the data, prompting responses, or computing other systems. This is one of the many examples where robotics is being implemented for easing human efforts and automating mundane tasks.<\/span>\u00a0<\/span>In an environment such as this, performance and functionality can be ensured only when the expected results are tested rigorously and authenticated under varying conditions.\u00a0<\/span>\u00a0<\/span><\/p>\n Dependability on IoT<\/span><\/b>\u00a0<\/span><\/p>\n Today, consumer brands and industries functioning across various domains are leveraging the capabilities of IoT to innovate and offer new experiences. The overall functioning of IoT totally depends on how effectively the data is exchanged and applied in real environment. IoT systems need to be checked for security, performance, functionality, and availability across the consumer lifecycle. QA and Testing has been enabling enterprises to ensure this under varying pressures and conditions. This helps\u00a0<\/span>overall in increasing the dependability of businesses on IoT devices for delivering desired consumer experience.<\/span>\u00a0<\/span><\/p>\n 5G<\/span><\/b>\u00a0<\/span><\/p>\n As per the top digital transformation trends for 2021, 5G is all set to become mainstream. Leading telecom companies and Communications Services Providers (CSPs) are actively building up their 5G capabilities by investing in the required infrastructure.<\/span>\u00a0<\/span><\/p>\n The remote lifestyle in the pandemic has highlighted the need for a robust, continuous, and reliable network. This has led to the surge in 5G development and adoption. With more and more sectors embracing 5G, software testing will also become critical for ensuring a seamless implementation.<\/span>\u00a0<\/span><\/p>\n To sum up<\/span><\/b>\u00a0<\/span><\/p>\n The consumer market is dynamic, and businesses need to experiment and innovate to hit the right chord with the end-user\/consumer. This can be done with conviction only when these technologies are well-tested against numerous odds and under various conditions. QA and testing can be an absolute enabler in this context.<\/span>\u00a0<\/span><\/p>\n Cigniti offers independent\u00a0<\/span>quality engineering<\/span><\/a>\u00a0and a wide range of\u00a0<\/span>software testing services<\/span><\/a>\u00a0and solutions for the next generation enterprises and ISVs across the globe. Our experienced and deep-skilled quality assurance professionals have a hands-on, end-to-end understanding of the challenges faced by enterprises while on the path of digital transformation.<\/span>\u00a0<\/span><\/p>\n We implement the best possible software testing methodologies and applications, a\u00a0<\/span>Testing Center of Excellence<\/span><\/a>, and world-class software testing Labs to deliver on our promise of Quality Engineering, Quality A<\/span>ssurance, and\u00a0<\/span>Digital Assurance<\/span><\/a>.<\/span>\u00a0<\/span><\/p>\n