7 Approaches to Legacy Application Modernization
When choosing the right approach for your organization, consider the return on investment. Let’s learn about seven common approaches to legacy application modernization.
10 Myths of Custom Software Product Development
Custom software product development can help businesses streamline their workflows and improve business operations. But without experience, some organizations might hear myths that perpetuate concerns about custom software—and miss out on the opportunities that it offers.
Make sure you have up-to-date information about custom software product development and offshore development—not just assumptions or perceptions. Let’s start by dispelling the 10 most common myths you’ll hear.
What Is Edge Computing? What Are the Opportunities and Challenges in Edge Computing?
Similar to the migration from on-premise servers to cloud computing, companies are investing in the next technological progression—edge computing. As the name suggests, edge computing brings the computational infrastructure closer to the data source (i.e., the edge of a network), where it enables faster and more reliable services, as well as improved flexibility. This network architecture helps to overcome some of the issues with cloud computing because nearby devices are used as servers to improve response times and reduce latency. Organizations from all industries are looking closely at edge computing as a component of their digital transformation strategies. What Is Edge Computing? In simple terms, edge computing brings the computational infrastructure closer to the data source, which can provide faster access to and analysis of that data. The proximity of the data source and the data computation addresses some of the limitations of cloud computing by improving bandwidth, reducing latency, and lowering costs. Edge computing is particularly useful in situations with limited bandwidth or unreliable networks because it doesn’t require an Internet connection. It’s also helpful with artificial intelligence or machine learning applications where a great deal of real-time data is produced and needs to be analyzed quickly. Additionally, multi-access edge computing refers to the edge of any network, while mobile edge computing refers to the edge of only the mobile network. How Does Edge Computing Support the Internet of Things (IoT) The objective of edge computing is that computing should happen in the proximity of data sources. As a result, edge computing is particularly beneficial for supporting the Internet of Things (IoT), sometimes called machine-to-machine (M2M) communications in the industrial world. Because the IoT generates a lot of data in a short time, edge computing offers improvements over other cloud computing infrastructures. The IoT gathers information directly from multiple devices, which can be almost anything with a sensor—including computers, vehicles, smartphones, appliances, building automation systems, and production equipment. Typically cloud computing is not efficient enough to handle the growing quantity of data generated by all those devices. Edge computing brings computation closer to IoT devices, improving response time, reducing latency, improving bandwidth, and lowering costs. What are the Benefits of Edge Computing? Edge computing extends cloud-based computing to geographically distributed locations, bringing computation closer to the devices that produce data. That offers benefits such as improvements in… Bandwidth Power consumption Response time Security Reliability Performance Latency Scalability Costs What are the Challenges of Edge Computing? Unlike cloud computing, where servers are located elsewhere, edge computing involves physical devices located in close locations. As a result, it requires professional IT services to set up and monitor the network. Like any technological innovation, challenges must be addressed before implementation. These challenges include… Stable power supply Hardware location Maintenance Security Edge computing is still a nascent technology, although the market is expected to expand rapidly. Many companies are looking at edge computing as part of their long-term digital transformation strategies because of its ability to streamline business processes. The appeal is the ability to extend conventional cloud computing with a distributed infrastructure where applications are closer to the sources where the data is captured. Contact InApp for more information about edge computing, and how it can help your organization.
Impact and Examples of Digital Transformation on the Business World
Digital transformation helps companies future-proof their technology landscape by implementing a modern digital backbone. But it requires more than just technology. It also serves as a business transformation — a way to rethink how an organization uses technology to fundamentally improve business performance. It should affect all areas of an organization, changing the way it operates and the way it offers value to its customers. What digital transformation means for business? Digital transformation integrates specific technologies that improve operations. It helps companies boost their technology initiative, which can result in the ability to increase revenue, cut costs, improve security, and streamline business processes. Business areas where digital transformation can significantly improve business functions include… Decreased operating costs: Digital transformation decreases operating costs by reducing the time needed for workflows, eliminating manual tasks, and incorporating new functionalities. Increased revenue: Digital innovation can improve the sales process, increasing market research and finding new customers for businesses of all sizes. Mining customer data: Customer data can provide a wealth of business information, revealing new possibilities and insight once that data is centralized and analyzed. Streamlined workflows: Digital innovation can improve collaboration, remove or reduce bottlenecks in processes, and speed up workflows. Improved customer satisfaction: Service operations can be streamlined and improved, strengthening the relationship with customers. How do you digitally transform a business? While digital transformation will look different based on a company’s needs, some of the major components remain the same. Key steps include… Develop a digital business strategy: Outline a transformation strategy that shows what the business wants to achieve using technology. Define customer needs: Review the needs of customers and identify how to align products and services to meet those requirements. Outline process improvements: Identify bottlenecks, tasks, and workflows that play a significant role in business operations, and find ways for improvement. Identify tools and technology: Evaluate digital tools and disruptive technologies that offer opportunities to improve processes and workflows. Make data-driven decisions: Use data and analytics to provide actionable insights that help in evidence-based decision-making. Examples of Digital Transformation in the Business World InApp has helped our clients drive a digital change agenda and future-proof their technology landscape by implementing a modern digital backbone. Learn how these InApp customers have used digital transformation to streamline business processes. Investments in Modern Technology Digital transformation works for more than just private businesses. The Trivandrum and Calicut Airports were one of the first to use computers for handling cargo. As part of the modernization process, the Government of India decided to refresh and replace conventional messaging systems in all airports. The new design had to communicate with other government systems. InApp replaced the system with a modern web-based and communications-enabled system, thereby making it possible to work with users like forwarding agents, statutory government agencies, and global airports. We developed a cargo management system to interact with related government systems and integrated functions like import/export cargo and warehousing operations. Data-Driven Decision Making An InApp client in the pharmaceutical industry used several automated systems for most of its business and administrative areas of operation, not all of which communicated with each other. With data existing in multiple locations, the client had trouble getting a clear view of their business and was struggling with reporting and budgeting. The challenge was to connect all these disparate systems and deliver improved business intelligence. InApp created an end-to-end, scalable integrated system that captured and stored data from different sources, empowering users to deliver and act on meaningful analytics throughout the enterprise. The result was improved trend analysis, forecasting, and business performance management. Streamlined Operations As a large manufacturer, our customers provided aerospace parts for global enterprises like Boeing, Bombardier, Rolls Royce, GE, and more. Separate applications were used for different businesses such as production, supply chain management, and accounting. The client hired InApp as a long-term partner to migrate their legacy application to a more efficient web-based model. InApp’s dedicated offshore team developed an upgraded web-based version of the company’s Enterprise Resource Planning (ERP) application. The result was an all-in-one secure and effective ERP tool that was capable of handling the overall tasks and functionalities. For example, the new functionality significantly improved inventory management and order tracking mechanism, achieving more than 95% accuracy. An improved revenue tracking and billing system also eradicated errors that existed in the older version of the application. For more than 20 years, InApp’s digital transformation experts have helped companies invest in the best technologies to boost their digital strategy, increase revenue, cut costs, improve security, and streamline business processes. Contact us to learn more about how we can help your organization.
A Detailed Write Up on Software Product Development Methodologies and Steps
Software product development enables companies to create custom solutions that meet specific business requirements. For example, your business can optimize internal business processes and automate logistical functions by developing a custom solution.
Let’s discuss the phases of software product development, and common methodologies used in the process.
25 Different Types and 7 Principles of Software Testing Services
Independent software testing holds a critical role in the development process. The testing team should be completely separate from the product development team and the end-users, making them truly independent. Let’s learn more about the types and the principles of independent testing.
The Ultimate Guide to Mobile App Maintenance
Once your customers can start downloading and using your mobile app, you’ll probably feel like taking a deep breath and enjoying the moment. But the hard work isn’t over yet.
Software development includes creating, designing, deploying, and supporting software. That last step – support – often gets overlooked. But maintenance can make or break an app’s success. If you don’t take care of your app with regular maintenance after it’s deployed, your hard work will result in failure.
The Future of Blockchain Technology in Business Operations
Blockchain technology offers benefits for a wide range of industries. Learn how it will alter business operations in the near future.
Artificial Intelligence and Machine Learning Trends you Should Never Miss
Artificial intelligence (AI) and machine learning (ML) will continue to hold a place at the forefront of the technology sector in 2022. Rapid changes in the field hold great promise for even more significant breakthroughs.
Various factors such as growth of data-based AI, advancements in deep learning, and push for robotic autonomy to stay competitive in a global market are expected to drive the adoption of the AI solutions and services.
Here are the trends to watch.
Top Artificial Intelligence Frameworks and their Pros and Cons
When it comes to AI, you can choose from many different deep learning frameworks, depending on your needs. We’ll discuss some of the major ones in this blog, and outline each framework’s pros and cons.