7 Reasons Why Software Testing is Important
There is no denying the fact that in software development, bugs can appear in any of the stages of the SDLC. In fact, there is a high possibility that even your final build that is ready to go live has errors of both types, i.e., design, and functionality. Furthermore, there have been numerous instances where the live demo failed miserably because no one thoroughly checked it before — oops! — now you are stressed out, and when that happens, it throws a huge blow in the entire process. That is why; each organization needs to ensure that software testing should be an integral part of the software development life cycle (SDLC). Here are the seven critical reasons, out of many reasons that make software testing important: Saves big bucks– When it comes to software testing, many companies do not see the need for it, or do not budget it properly, and at times, neglect the importance of a quality or testing process. It is always tougher to fix a mistake than to prevent it. Moreover, it is much more expensive. If a bug is discovered late in the game, then you are not just losing big bucks on the immediate cost of fixing the bug, but you are also losing money through lost prospective deals. If bugs are caught in the early stages, it costs much less to fix them and avoid any embarrassment later. Developing software without proper testing is a huge, risky bet. Onboarding testers who are technically sound and experienced is just like a smart investment that will reap us long-term benefits and it will far outweigh the cost of the service. To identify and correct mistakes– Regardless of how skilled and experienced developers we have, we all make mistakes, especially while developing an application that is huge and complex. Admit that there is no such application as a bug-free application. When a code is developed, it is important to test everything that we produce because there is always a possibility of glitches in the system and the only thing that can expose hidden errors, ensure that the system works as expected according to requirements, measure how well your software works before it is installed in a live operation, etc. is software testing. Boost Business– Making software testing an essential part of your software development life cycle lets you enhance the user experience and improves the final product outcome that ensures rock-solid brand presence, brand loyalty, and product recommendations. The well-tested product ensures that we send out the best version of our product into the market that speaks for itself, and word-of-mouth endorsement is priceless. This helps in retaining not only the existing clients but helps to onboard new clients as well. This makes software product testing even more vital. To ensure software security– One more headache that testing relieves is security. Software security is undoubtedly the most sensitive and yet most susceptible part. Cyber-attacks are quite common these days, and security is an important aspect that cannot be ignored at any cost. Notable instances have occurred where customers’ personal information has been stolen or hacked. Security testing of a product not only shields information from these hackers but also makes sure it is not lost or gets corrupted in any form. That is why we all look for trusted products that would bring confidentiality to share our personal information. Application security testing allows to identify and fix many vulnerabilities that ensure a secure product that in turn makes customers feel safe while using the product. With software security testing, we can deliver a trustworthy product to our clients that protects their critical information from Day 1. Validate the user experience– No matter the domain, the user experience is everything. The end purpose of developing any software should be to confer the best satisfaction to your users. Your application may function as required, but in the hands of the user, it could be baffling and inconvenient to know what feature is available where. Since software testing offers a prerequisite user experience, think of it as a trial run before you go live. There is nothing worse than an outraged user who paid for a product that does not work as expected. Fail to evaluate user experience, and your users will not fail to go to your competitor. If users of your application have a great user experience, they will tell their family and friends. And with the burst of social platforms such as Facebook, Instagram, Twitter, etc. positive as well as referrals can spread very quickly. Control Process– How do we know that the application works the way it is supposed to? How can we measure what all requirements are ready to deploy to production and that the quality meets expectations? How do we know how many critical issues are still open? Software development should be measured whether it goes against the requirements or not. The testing phase can help you to know the state of your product’s quality that certifies all features are ready for production. The sooner development teams receive feedback, the quicker they can address issues of both types, i.e., design, and functionality. Using this controlled process, we can build a formidable reputation and brand image, things that are important in the long term. Easy Transitions– Software applications released should be of superior quality and compatible with various OS, devices, platforms, etc. which can be achieved only if we do thorough testing. Even if we are adding a simple feature to our current application, checking compatibility is a good practice to ensure a seamless experience on the go. Ensuring this lets you maintain users and gives them a better experience without any loss in any convenience. This process enables the business to make its products stand out in the market. To Sum It Up: The benefits are noticeably clear. Any company, big or small, should test its system because achieving high quality is necessary. As stated above, software testing is an inseparable part
Make your first-party data work for you in advertising – Implementing identity solutions using cloud
The recent debates on digital privacy and several decisions by government and influential corporations have brought to focus how customer data is collected and used by companies. The broad trend is towards more transparency for users as to how their data is utilized and shared. Generally, users have shown more willingness to share data with the platforms they use. The direct use of that data for personalization and better engagement is a win-win situation for both parties. Such a scenario shifts the onus to the first-party platforms to use their consumer data judiciously, and any enrichment or extension of that data is only allowed with proper consent in place. This implies that the publishers have control over providing a meaningful and personalized advertising experience for their customers. Identity solutions built custom or otherwise are vital tools for publishers in such scenarios. What are identity solutions? Consumers can have multiple touchpoints with media companies. The service is accessed through a variety of devices, customer service interactions, social media interactions, content consumption, etc. Identity solutions assist in tying these various interactions together around a single user. Sometimes the connections between these interactions are obvious, such as a consumer’s ID and identity are easily established in this case. It isn’t always the case. Identity solutions are built around well-established databases, such as graph databases, which make indexing and searching easier. Moreover, it necessitates the execution of specialized algorithms, such as the connected component algorithm, which generates a consistent virtual ID for a user. End-to-end identity solutions include data collection from various sources and the creation of an identity database. This identity database serves as a downstream reference for developing multi-tiered use cases that provide end-user personalization. Identity Graph Use Cases in Advertising Identity serves as the foundation for the development of numerous use cases. It is extremely useful in maintaining a low latency profiling database that can be used to feed downstream solutions. Audience segments: Instead of third parties, publishers can create customer segments themselves using an identity solution. Business rules set up for different segments help in the classification of audiences. These audience segments get auto updated as they tend to change over a period. Personalization Engine: The identity graph captures the actions of users, with respect to interests and preferences not only explicitly but also implicitly. Since all actions are in one place, giving a 360-view, the personalization engine can feed off this information. Creative optimization: Not everybody gets the same advertisement as the information available about the history of the user enables advertisers to show personalized creatives. Brand safety: If the content being consumed does not match the ad shown, the reputation of the brand can be impacted. An identity graph can provide supplementary information regarding user preferences that can protect the brand. Campaign Analytics: The performance of campaigns can be measured against audience segments. These are key metrics on which advertising is bought and sold. Why cloud for Identity Graph implementations? Identity solutions map and unify billions of relationships and query customer data with millisecond latency. There are many purpose-built cloud databases made for identity solutions, for example: AWS Neptune, Neo4j, etc. Cloud solutions reduce the total cost of ownership by storing and querying billions of nodes and edges, with lower latency and lower costs for storage compared to other models. Usually, these solutions are quick to deploy and can be up and running without taking much time. Conclusion It has become imperative for media publishers to develop identity management solutions of their own as they ensure that first-party data is fully consolidated. Identity solutions can not only provide personalization for the publisher’s users, but also serve as data rooms for their advertisers. These solutions help publishers meet the privacy rules and also provide their users all the relevant content they require, including advertising.
From Legacy to Modernization: Connecting the Digital Dots in Underwriting
The rapid advancement of technology over the last few decades has transformed the consumer lending market, although the extent to which this transformation has occurred is widely debated. Fintech lenders have reduced the time required to process mortgage applications. Lenders have gradually moved from a traditional to a more digital lending environment. Three key drivers have led lenders to make this move: 1) The need for efficiency: Digital lending platforms can process loans in a fraction of the time it takes for loan officers to do so. This means that customers get their loans faster and at a much lower cost. 2) The need for innovation: Lenders are always looking for ways to enhance the customer experience and improve adoption rates. Digital lending offers them an opportunity to do so by providing tools such as instant approvals, online account management, and remote check deposit. 3) Evolving customer expectations: Customers want more than just a simple loan transaction. ‘Speed to decision’ is vital to customers. Driven by the need for efficiency, innovation, and evolving customer expectations, most lenders have been moving steadily toward greater digitization. Underwriting has been a key focus area. Most lenders have actively been upgrading their underwriting capabilities with more advanced digital technology and expanded data sources. Data mining and analytics are rapidly changing the lending landscape by enabling businesses to capture and process real-time data to their advantage. According to Insider Intelligence’s Online Mortgage Lending Report, automated underwriting processes is crucial for the success of modern lenders as it can significantly reduce loan processing times and interest rates. The Impact of Automated Mortgage Underwriting Across Various Lending Stages Manual underwriting entails interacting with disparate data sources, which results in extreme inefficiency in risk assessment. There is no central repository for data that can be gathered, segmented, stored, and accessed quickly. This results in underwriters missing critical information that could significantly affect a borrower’s risk profile. Using Artificial Intelligence, Machine Learning Algorithms, and other related technologies, automated underwriting software enables lenders to make underwriting decisions more quickly, with increased accuracy, and with minimal human intervention. It is accurate, faster, and more reliable than manual underwriting. In order to make an analysis report, the automated underwriting system automates the entire loan approval process, from extracting data from various underwriting documents to matching it with third-party data from other financial institutions, like banks, creditors, lenders, and so on. FinDecision- A mortgage industry “one of a kind” product that exceeds customer expectations Tavant’s FinDecision is an AUS automation and underwriting platform that enables lenders and loan originators to achieve operational efficiency through optimized intelligent business processes and workflow orchestration. It is a core component of its straight-through processing and automated underwriting. It enables lenders to optimize loan fungibility and execution while maintaining operational efficiency. FinDecision leverages machine learning and process automation to submit loan data to automated underwriting systems with a single click, enabling lenders to see the full scope of operational benefits available to their borrowers and thereby improving the overall borrower experience. Through automation, lenders can reduce downtime and costs while improving loan quality. FinDecision compares investor guidelines, multi-AUS response, and loan data. It also provides a list of the most common questions and answers for first-time home buyers. The platform automates the underwriting process, powered by AI and machine learning algorithms. The platform eliminates human errors, keeps data up-to-date, and provides real-time insights to lenders. This revolutionary software provides a single view, side-by-side comparison of investor guideline responses and offers 360-degree insights on the various segments of loan data (Income, Asset, Collateral, Credit, Borrower). FinDecision automated data quality check (lender, investor, and origination channel-specific) enables the loan processor to prep the loan file instantly and review data inconsistency and quality checks. It automatically updates the loan data according to the investor’s requirements (data mapping and representation). FinDecision enhances loan quality and improves the overall borrower and lender experience. It offers an automated, one-click approach to achieving loan fungibility and pricing best execution on the one hand, and operational best execution on the other, during the loan’s processing, underwriting, and secondary market stages. It is a core product within Tavant’s Touchless Lending platform and is Loan Origination System (LOS)-agnostic. Wrapping up To remain competitive, lenders should speed up underwriting transformation. Automated underwriting evaluates risk and underwrites loans using a technology known as automated underwriting systems (AUS). It has the potential to accelerate and simplify the loan approval process for both lenders and borrowers—it is not an exaggeration to say that automated underwriting brings the mortgage process into the twenty-first century. Tavant’s AUS automation and underwriting platform, FinDecision provides an intuitive way to eliminate hard-coded legacy IT systems. It compiles findings to credit conditions and compares them (existing vs. new). What Next? Schedule a demo with Tavant today, visit us here or reach out to us at [email protected].
Cloud Service Providers Accelerate Public Cloud Maturity Across Vertical Industries
The State of Cloud Adoption 2022 – A survey-based research study by IDG Research and Tavant Tavant, in collaboration with IDG Research, conducted a comprehensive research study among 255 large enterprises’ CIOs, CTOs, and Senior VPs to identify cloud adoption trends. The study’s goal was to understand the cloud computing landscape in the United States across a wide range of industries. Automotive, discrete manufacturing, e-commerce, financial services, food and beverage, healthcare, process manufacturing, retail and wholesale, and travel were among the industries represented. Hurdles to Cloud Deployment Being Leap-Frogged Tavant and IDG Research found that businesses are increasingly embracing cloud tools, industry frameworks, and infrastructure automation tools to improve time to market and ROI. Security, legacy migration, cloud governance, and infrastructure maintenance are all common concerns that are now being addressed through improved practices such as outcome-based shared services models and industry-specific cloud-based solutions. Development, security, and operations processes (DevSecOps), which work with cloud tools, are becoming increasingly important in the development and management of cloud applications. The top cloud adoption barriers are security (52%), legacy IT infrastructure (29%), insufficient budget (28%), regulatory concerns (27%), and uncertainty about cloud benefits (27%). (23 percent ). Business agility is a key motivator for 93 percent of US organizations polled to adopt the public cloud. The secondary reasons are increasing revenue through innovation (81%) and lowering costs (8%). (77 percent ). Currently, 43 percent of respondents have a hybrid cloud or multi-cloud strategy in place. Nearly 40% of organizations use DevSecOps extensively across their entire technology footprint, while 37% use DevSecOps for specific programs. Industry Focus Makes Cloud Adoption Favorable Today’s cloud service providers continue to bring significant innovation to the banking, manufacturing, and hospitality industries, with cloud frameworks, tools, and best practices developed for specific industries. 53% of BFSI companies have a hybrid or multiple cloud strategy in place, and 58% plan to use CSPs extensively, mainly for new workloads Manufacturers are ahead of other industries in cloud adoption, with 75% having strategies in place. 78% of retail and wholesale firms and 59% of advertising, media, and entertainment businesses are actively developing their cloud strategy Cloud Innovation Becomes Industry Oriented Innovative cloud services, including, AI and analytics, are favored by hospitality, food and beverage, and travel Industries such as publishing, PR, advertising, media, entertainment, and broadcasting are banking on Cloud Data Services for expanding their end-user base and enhancing customer experience. The Agtech industry is actively looking at adopting IT service management for better business outcomes and a sustainable future. The Future is on the Cloud The advancement of business maturity in cloud implementation has resulted in a better understanding of the benefits, which include increased business agility, revenue through innovation, lower costs, and improved TCO. Click here to get your copy of the Research Report. Learn more about Tavant Evolvx, a high-touch offering that seamlessly intertwines standard data models, crosscloud connectors, workflows, APIs, and industry-specific components to meet your unique challenges.
Unlocking the Ability to Adapt with Digital Lending Solution
Long queues. Tons of paperwork. Mortgage and too much hassle. The traditional lending ecosystem is fraught with inconveniences in a world where instant gratification in consumer delivery is the new normal. It lacks agility and flexibility to meet the needs of the new consumer. Fintech organizations are far more technology-enabled. They utilize advanced technology to deliver efficient, fast, and flexible financial services to consumers. No wonder fintech is fast disrupting traditional service providers and growing at an unprecedented rate of 9.2% to nearly $158,014.3 million by 2023. The changing landscape of lending Traditionally, when borrowers in need of capital approach lenders, they are provided standard options–a folio of one-size-fits-all loan products. Without deep insights into consumer needs, these loan products cannot meet each potential borrower’s specific and unique credit needs. There is no differentiation in loan products, and all traditional lending entities are fighting for the same piece of the pie. Add to this the often-prohibitive service cost – making loans economically unviable for many borrowers in the market. Furthermore, the approval process is too time-consuming and complex, undermining the needs of credit seekers who require the loan immediately. Naturally, easy access to credit is one of the biggest challenges in the global lending ecosystem. This is where digital lenders come with an advantage. Digital lenders have a competitive advantage over traditional lenders as they have new-age technology and data capabilities that make lending far more quick, efficient, and data-driven than ever before. Paving the path to an equitable financial ecosystem Digital lending creates a more inclusive financial ecosystem and delivers loan products and services to underserved and previously excluded individuals and businesses. New-age technologies and data drive innovation in digital lending. Simultaneously, data analytics is also ensuring less risk in the digital lending space. Even policymakers are encouraging the development of new and agile loan products to serve the businesses. Fintechs, often equipped with digital lending capabilities, have changed the game for borrowers. They give remote access to credit in a brief time. Additionally, underwriting is easier and more data-enabled than ever before. This efficiency of digital lending is a game-changer in the global lending landscape, opening new routes to ease access to credit for all borrowers, irrespective of their creditworthiness in the traditional sense of the term. A wider circle – Correlation of data opening new revenue opportunities for digital lenders Digital lenders no longer rely on manual underwriting processes. Instead, they use financial transactions and FICO® credit scores to identify risk factors. There are also new and innovative risk repayment methods, from real-time payment deductions to standard mortgage paid conveniently via apps. These digital methods enable fintech organizations to collect and analyze additional data about their customers for customer-centric decisions. These include determining credit limits, holistically understanding their ‘customers’ financial needs, and delivering new and innovative financial products that serve the unique needs of each digital-savvy customer. The Way Forward Digital lending is redefining the dynamics of the credit ecosystem. With lower costs and improved reach, financial institutions can do more with less. However, digital lending also requires a robust long-term strategy to be truly safe and risk-free. The lending journey does not end with disbursement; loans also need to be collected, serviced, even restructured, and renewed as time passes. With so many moving parts, digital lending requires careful planning to avoid the risk of a false start for financial institutions. Process automation, new and intelligent technologies such as AI and ML, and intelligent data analytics are at the heart of a wholesome digital lending strategy. What next? Tavant can help lenders diversify how they do business and effectively unlock savings with next-gen technologies. To learn more, you can reach out to us at [email protected] or visit here. FAQs – Tavant Solutions How does Tavant help lenders adapt their digital lending capabilities?Flexible, modular platforms with API-first architecture, configurable workflows, and scalable infrastructure for rapid adaptation to regulations and market demands. What adaptation capabilities does Tavant offer for digital lending transformation?Rapid deployment, customizable UI, integration options, configurable business rules, real-time analytics, and continuous optimization. Why is adaptability important in digital lending?Rapid regulatory, customer, market, and tech changes require flexible systems for quick response and innovation. What makes a digital lending solution adaptable?Modular architecture, configurable workflows, API-first, cloud-native, real-time analytics, and easy third-party integration. How long does it take to implement digital lending solutions?3-6 months for basic, 12-18 months for fully-customized systems; cloud solutions deploy faster, some basic setups in weeks.
Going Up! Industry Clouds have arrived
Recent historical events have shifted global business priorities, speeding up the digital transformation process. Remote work across continents and stronger collaboration with all stakeholders, including customers and employees, have spurred innovation and value-driven cloud technology offerings. While organizations were figuring out the best cloud technology applications and their implications, a new and efficient cloud solution emerged. It’s called the industry cloud. WHAT IS AN INDUSTRY CLOUD? An industry cloud provides cloud computing services tailored to a specific industry or business model. Industry clouds are highly curated environments that stack cloud technologies. THE DRIVE FOR INDUSTRY CLOUDS AND ROLE OF CLOUD SERVICE PROVIDERS (CSPs) Initial adoption of cloud technology was driven by cost, storage, or processing support. But as more enterprises moved to the cloud, many found that deployment and usage were often erratic or inconsistent. The need for an industry cloud arose when certain industries realized they needed a more tailored IT solution for security and compliance. And the Industry cloud was born. According to Gartner, Industry cloud ecosystems and data services are driven by increasing geopolitical regulatory fragmentation and industry compliance. Businesses today expect the same level of customization in the cloud as they do on-premises. To enable this, cloud service providers (CSPs) now offer a hybrid strategy that includes industry-specific solutions and cloud infrastructure maintenance. INDUSTRY CLOUDS… SOME EXAMPLES Today, cloud hyperscalers are partnering with industry-oriented cloud service providers to build specialized environments. Microsoft, for example, has worked with partners to develop supply chain solutions for the industrial industry through Microsoft Azure Cloud. Similarly, Microsoft Azure has now built industry clouds for financial services, retail, and other industry verticals. In the construction and real estate industries, industry clouds can comprise solutions for model management, collaboration, estimate, scheduling, site management, and more. This level of industry cloud specialization allows firms to focus more on their core business while still being able to derive the benefits of cloud computing. Salesforce introduced the ‘Revenue Cloud’ this year. The industry cloud is aimed at businesses that need to consolidate customer transactions. The revenue Industry cloud combines CPQ, billing, B2B commerce, and channel software products to offer everything from renewal to revenue recognition (PRM). BENEFITS OF THE INDUSTRY CLOUD Businesses prefer industry cloud computing over a “one-size-fits-all” cloud model for a more specialized environment. Besides niche data security, organizations want to closely align with customer priorities, for example, Banking as a Service (BaaS), Agtech Cloud (AgTech), and Health Cloud (Health Cloud). With the rise of mobile devices, the cloud market needs new and efficient apps. Customizable Offerings Industry cloud solutions are custom-built beyond security and compliance to address individual business outcomes. These solutions are also critical when integrating public cloud computing with on-premises resources in hybrid architectures. Product-Centric Approach Organizations today are becoming product-centric, agile in operations with better time to market, and composable architectures with a pay-per-use model. Leaner Footprint Industry cloud solutions are popular for SaaS deployments. As a result, many legacy IT providers can benefit from leaner data center footprints. Improved Functionality Industry-specific applications enable higher levels of technological efficiency, functionality, and performance. An industry cloud product for healthcare, for example, could securely manage electronic health records or parse medical images. Advanced Security Businesses are increasingly concerned about data security online. Industry clouds offer superior levels of security and compliance over traditional cloud offerings, allowing CIOs to rest easy. INDUSTRY CLOUDS AND THE FUTURE The future of industry clouds depends upon the cloud vendors’ ability to customize cloud technologies by business needs. According to Techaisle’s research, SMB and mid-market cloud adoption will increase by 121% increase in the US over the year. Industry clouds are ready to help organizations leapfrog their digital transformation journey and accelerate technology transformation where it is most needed. A new generation of industry cloud providers will help businesses innovate faster by providing customized applications and services.
Six IoT Testing Challenges for Testing Experts
Introduction The Internet of Things (IoT) refers to physical objects embedded with sensors and software that can exchange and collect data over a wireless network. The Internet of Things brings many consumer benefits, like simple remote control, automation, etc. It also brings added software complexity and security risks that require significantly more testing than in the past. IoT devices have evolved to look more like traditional cloud applications, with code that runs in the device itself, as well as an array of dependencies that interact with the outside sources of data such as time or weather. These dependencies can make devices expensive, difficult, and time-consuming to test as it involves real-time sharing of data and collaboration. A study says that more than 6.4 billion Internet of Things (IoT) devices were in use by 2016, and that number will grow to more than 20 billion by 2026, which means that our planet will soon have more connected devices than the human population. Testing these IoT devices becomes quite challenging because of the variety and volume of data this system generates, the heterogeneity of the working environment, and the complexity of the number of working components involved. Challenges in IoT Testing One of the tough challenges for manufacturers and integrators is testing these devices. Let us discuss some challenges associated with the testing of IoT devices: Communication Protocol: IoT devices use various communication protocols such as MQTT (Message Queuing Telemetry Transport), XMPP (Extensible Messaging and Presence Protocol), etc. These protocols aid in the establishment of a connection between devices and servers. Tools/Tech that the testing team is planning to use should support these communication protocols so that APIs written on top of these protocols can be effectively validated which interacts with these devices. Multiple IoT cloud platforms – Azure IoT, IBM Watson, and AWS are the most used cloud IoT platforms that help connect different components of IoT devices. These devices need to be tested across the cloud platforms to ensure their effective usability. In a cloud platform, we have different IoT devices with different capabilities, these devices generate data that can be structured or unstructured and will be sent to a cloud platform.When more devices are deployed on the cloud platform, it becomes difficult to replicate a real-time environment for testing, since there can be a lot of devices that need to be tested on different platforms. IoT security and privacy threats – IoT devices are the most vulnerable to cyber-attacks. Most users think that it’s a manufacturer’s responsibility to secure their devices and, therefore, do nothing to protect them. Cyber-attacks are very common across IoT devices, and security is an important aspect today. Wired systems are much less accessible than non-wired systems. Therefore, one challenge to moving into IoT solutions is that companies open themselves potentially to more risks unless they have a perfect security strategy in place. Beside functional and performance testing, special attention should be paid to the device password policy, data protection, data encryption, regular firmware, or software upgrade testing. Device Diversity – With so many brands, models, versions of the OS, Screen size, etc., it is a challenge to test an IoT application that works perfectly across all devices for all possible combinations that are not practical. Each IoT device has unique capabilities and may perform better in some environments and platforms than others. As a result, they must be tested across platforms for effective usage, and it is critical that we have good test coverage across dozens of devices. There is also a challenge with the version upgrade for the IoT devices along with their software and firmware updates. It becomes critical to test the devices across the IoT platforms with their latest software to ensure all the components are working efficiently after the update. Network Availability (Always online) – Network configuration essentially affects the performance of an IoT device because IoT is all about rapid communication and that too consistently all the time. Though, at times devices experience troubles with network configurations like unreliable internet connections, hindering channels, etc., which poses a challenge of how to test it in all possible network conditions. Data Volume, Data Variety, and Data Velocity (Real-time data testing) – Sensors on all devices simultaneously generate massive data (this data is significantly intricate and unstructured that involves appropriate cleaning of it for the end processing). IoT will be dealing with that data and different varieties of data that cause significant challenges. Gathering, organizing, and evaluating this disintegrated data is not easy as the volume of data can be boosted at any time. Conclusion: There are numerous other challenges to consider in addition to the ones mentioned above. Hardware quality and safety concerns are among other challenges that the testing team faces while testing IoT applications. Building stable and quality IOT applications might seem overpowering and a huge task, but it can be made simpler by proper planning, splitting it down into separate sub-tasks, and setting up a rock-solid test environment to manage cloud and virtualization strategies.
Top Blogs and Webinars from 2021-Connected Service and Warranty
As we close the year 2021 (and what an incredible year it was), here is a list of our most popular blogs and webinars from this year – the ones our customers showed the most love to, and that answered the most pressing questions. Enjoy! Blogs 1) From Cost Center to a Competitive Advantage: Warranty Management in Manufacturing Today Once considered a cost center, warranty management is taking the front seat in creating seamless aftermarket service experience. 2) Electric Vehicles and their Impact on Automotive Warranty Management The transition to smarter electric vehicles and the potential phasing out of combustion engines is likely to be a game-changer for many. 3) Futuristic Tech: Turning the Wheels of Manufacturing Learn about the advancements in the manufacturing industry with Drones, AR/VR, IoT, and much more for better processes, performance, and protection. 4) Data Analytics: A Catalyst for Change in Service Life-cycle Management Today AI and analytics is critical in addressing service life-cycle challenges, increasing transparency, and creating a rich aftermarket experience. 5) Making Warranty Management Profitable for Manufacturers Traditionally manufacturers offered warranties to buyers to assure them of the quality and longevity of products or services. The industry has progressed a long way. Webinars 6) Connected Service Life-cycle – The Flywheel Effect Opening session at WCM Experience by ‘Women in Manufacturing’ from Tavant, on how smart and simple changes in after-service processes like customer support, service request, service planning, service execution and field service, spare parts management, warranty management, and recalls can create exponential value and set the flywheel to spin faster. 7) Panel Discussion: Service Analytics – Make that Data Work for You! Smart learning models are getting more accurate and changing the way service analytics is driving decision-making. This session explores the decisions that impact machine uptime, service parts pricing, equipment failure, and maintenance demands. 8) Panel Discussion: Service and Sustainability – Reduce, Recycle, Reuse! Timely Service data and insights can impact the bottom line in three ways – fiscal, societal, and environmental. In this session, the speakers from varied Manufacturing backgrounds discuss how service data can benefit sustainability. 9) Connected Warranty and Service in Automotive Industry A discussion on the Automotive warranty trends, the impact of innovative technologies and connected data, and how the Automotive industry is redefining service through connected and optimized service platforms. 10) The Learning machine: Transforming Customer Experience Using Data, Warranty, and Service Contracts Opening keynote by Bob Roberts, Customer solutions leader, Trane Technologies at WCM Conference. Service excellence in a manufacturing and aftermarket industry dictates decisions be made using near-real-time information. To provide a rich and seamless experience to their customers, manufacturers need to improve data visibility, the backbone for delivering cutting-edge services.
Transforming IoT Data into Actionable Insights with Time Series Insights
Time Series Insights for IoT data: Generally, IoT data typically consist of time series data, which makes sense when observed over a period of time, like a sensor’s behavioral change, etc. Billions of data is getting generated from IoT these days, and it needs to be stored in a repository. But it’s challenging to store this data in a way, where you want to use it in near real-time to be processed to derive meaningful insights when needed in machine-critical situations. So, we need to store this data in a way that it makes sense. This calls for a service that can scale massively and help operators find insights quickly, Azure Time Series Insights. Introduction to Azure Time Series Insights: Azure Time Series Insights is a serverless, fully managed data analytics solution (PaaS), that users can use to integrate with their constantly changing data like data from several sensors or machines, data from airlines, satellites, etc. Any data that can be generated on a large scale and needs to be analyzed can be used through Azure Time Series Insights. Azure Time Series Insights architecture: The above figure shows a high-level architecture of how Azure TSI can be implemented in a real-life scenario. Time series real time data can be generated by various sources like satellites, mobile devices, medical devices, sensors, etc. Azure IoT Hub or Event hubs can be used to fetch the data from these devices into the Azure environment. Further, this data can be processed using services such as Stream analytics, Logic apps and Azure functions and computed signals from the processing pipeline are pushed to Azure Time Series Insights for storing and analytics. Once in the Time series insights platform, the data can be used for visualization. The data can also be queried and aggregated accordingly. In additional, customers can also leverage existing analytics and machine learning capabilities on top of the data available in Time Series Insights platform. Data from Time Series insights can be further processed using Databricks and pre-trained machine learning (ML) models can be applied to offer predictions in real time. Components of Azure Time Series Insights: Integration: Time Series Insights provides easy integration for the data generated by IoT devices by allowing connection between the cloud gateways like IoT hub and Event hubs. Data from these can be easily consumed in JSON structures, cleaned and stored in columnar store. Storage: Azure TSI also takes care of the data that is to be retained in the system for querying and visualizing the data. By default, data is stored on solid state drives (SSDs) for fast retrieval and can be retained for upto 400 days. Data visualization: Another component of Azure TSI, data visualization helps data fetched from multiple data sources and stored in the columnar stores, to be visualized in the form of line charts or heat maps. Query Service: Time Series Insights also provides a query service using which you can integrate Time Series Insights into your custom applications. Conclusion: Azure Time Series Insights helps you to easily connect to billions of events in Azure IoT hub or Event hubs, visualize and analyze those events to spot the anomalies and discover hidden trends in your data. It can both store as well as visualize the data. Alternatively, one can also have the capabilities to run queries against this data and obtain more simplified results.
Decoding the Future of Fintech Lending
It’s 2005, and Linda is all set to purchase her first home, her “starter home.” She knows finding that perfect home won’t be easy. On top of that she knows closing on her mortgage is going to be a time-consuming process. She is exasperated and dreading the thought of going through many cumbersome manual processes and tiresome paperwork. There is nothing much she can do but patiently wait for the process to play itself out. Fast forward. It’s 2021. The pandemic has reshaped how we work, and the world is adapting to a new era of remote working. Amid the upheaval, like many others, Linda decides to move from her ‘starter’ home to her ‘forever’ home with a backyard and home office. She found the perfect home by searching Real Estate sites on her mobile phone, yes, she found her home on her iPhone. Next step is the dreadful mortgage, but thanks to her lender’s digitalized application and closing processes, the entire home-buying process is now simplified and much quicker; Linda is pleasingly astounded by how much mortgage lending has evolved over the years. Reaching the New Wave of Borrowers With Digital Mortgage Capabilities Today’s mortgage industry is on the cusp of digital re-imagination. Driven partly by the need to meet the growing demand from tech-savvy borrowers for a quick and seamless process and partially by the pressure to cut costs and enhance efficiencies. Lenders are looking to digitize their end-to-end mortgage process. That’s the dream state for a lender. Thus far, most of them have focused on the lending process’s front end, enabling digital loan applications and consumer portals. As competition intensifies, they shift to the next stage of digital transformation by turning to Fintech lending solutions that boost efficiencies in loan production and enhance the servicing experience. Fintech Lending- The Digital Focus of New-age Lenders According to the report titled ‘The Role of Technology in Mortgage Lending,’ fintech lenders have the ability to process loan applications about 20 percent faster than other lenders. Fintech lenders process mortgages faster than traditional lenders, measured by total days from submitting a mortgage application until the closing, the report indicated. However, switching traditional mindsets and operating models to deliver digital journeys at an accelerated pace is no easy feat for a financial behemoth. But modernizing the borrower experience is the need of the moment for all lenders. Fintech is playing an increasing role in shaping financial landscapes. A fintech mortgage provides faster, more accurate, safer, and more affordable options than traditional mortgage lenders. It enables lenders to create a better relationship with borrowers with quicker and more seamless, personalized experiences. It accelerates data gathering, helps borrowers with superior communication, and reduces avoidable steps along the way. Seizing the Benefits of Fintech Mortgage Lending Enhanced efficiency: Efficiencies produced by fintech lending solutions allow lenders to close on mortgage loans faster. Automating numerous back-office operations and centralized data solutions also enable lenders to leverage customer information more efficiently than ever before. It speeds up otherwise time-consuming operations and further helps in closing the loan process faster. Delightful customer experiences: A more agile, streamlined application process indicates customers may be more likely to perform a given task that serves the lender in terms of the number of applications closed and funded. No more fragmentation: Fintech mortgages replace the fragmented siloed solutions of traditional lending with an integrated, end-to-end digital solution. It leads to greater efficiency and productivity, along with quicker loan cycle times and faster closures. To the Future: Let’s fast-forward to 2030. Linda is in the process of refinancing her ‘forever’ home. She’s astonished by the impressive advancements in cycle times and service levels compared to her 2021 experience. Her lender leverages next-gen digital interfaces that allow her to have contextual chats in real-time. Her appraisal is done same day, by a drone. Her lender uses AI-based applications to drive intelligent decisions based to ensure that Linda meets specific credit requirements, saving her significant time and effort. Not just that, the blockchain technology is there to provide a single source of verified data such as her tax information, income, assets, property valuations, and so on, improving accuracy as well as fast-tracking the loan fulfillment process. The outcome: Linda e-closes her refinance in a couple of days, or perhaps even in a few hours, thanks to an integrated digital ecosystem. It truly is a “one-click” refinance. Are you ready for the digital future? As digitally connected millennials and Gen Z borrowers coming into the marketplace expect hyper-personalization and faster closings. Lenders seeking future-proof success have only one choice – move from a tactical to a strategic mindset, modernize processes, and embrace intelligent automation. Learn how Tavant can help you lay the foundation for an end-to-end digital mortgage; reach out to us at [email protected] or visit us here. FAQs – Tavant Solutions What future fintech lending innovations is Tavant developing?Tavant is advancing embedded lending solutions, API-first architectures, real-time decision engines, and predictive analytics for market trends. They’re building platforms that enable instant lending integration across various digital channels and ecosystems. How does Tavant prepare lenders for future fintech disruption?Tavant provides scalable cloud-native platforms, open API frameworks, and continuous innovation programs that help traditional lenders compete with fintech companies while maintaining regulatory compliance and operational excellence. What trends will shape the future of fintech lending?Key trends include embedded finance, buy-now-pay-later expansion, cryptocurrency lending, AI-driven personalization, regulatory technology integration, and the rise of neobanks offering specialized lending products. How will fintech change traditional banking?Fintech will push traditional banks toward digital transformation, force innovation in customer experience, create new partnership models, and require banks to become more agile and customer-centric in their lending approaches. What is embedded lending?Embedded lending integrates loan products directly into non-financial platforms like e-commerce sites, software applications, or marketplaces, allowing customers to access credit at the point of need without leaving the platform.