React’s suitability to develop Geospatial solutions

 

Introduction

 

Application development is a critical necessity for many firms that seek to create unique user experiences. This can range from a simple interface that provides relatively specialized access to data, such as data monetization, to a more comprehensive solution that supports complicated business decisions, such as site selection. According to 182 Pages Report, the worldwide geospatial solutions market is expected to reach USD 502.6 billion by 2024, up from USD 239.1 billion in 2019, at a CAGR of 13.2 percent over the forecast period. In this article, we will discuss the significance of react in geospatial solutions.

 

What exactly is geospatial data?

 

Geospatial data is information that describes things, events, or other characteristics that have a position on or near the earth’s surface. Geospatial data often combines location information typically coordinates on the earth and characteristic information (the traits of the entity, event, or phenomena in consideration) with temporal information such as life span during which the location and attributes exist. In the brief term, the reported location may be static, such as the location of a piece of equipment, an earthquake, or children living in poverty, or dynamic, such as a moving car or pedestrian, or the spread of an infectious disease.

 

Geospatial information systems (GIS)

 

GIS refers to the physical mapping of data inside a visual representation For example, you can see GIS in action when a hurricane map (which indicates position and time) is overlaid with another layer indicating possible regions for lightning strikes.

 

Geospatial data examples include

 

● Attributes and vectors: Points, lines, and polygons are examples of descriptive information about a location.

 

● Point clouds: are groups of co-located charted points that may be retextured into 3D objects.

 

● Satellite and raster imagery: High-resolution aerial photographs of our planet.

 

● Data from the census: Census data has been released that is related to specific geographic locations in order to evaluate community patterns.

 

● Cell phone data: Satellite-routed calls based on GPS locations.

 

● Drawn pictures: CAD images of buildings or other structures that provide both geographic and architectural data.

 

● Social media data: Posts on social media that data scientists may analyze to uncover new patterns.

 

The following are the advantages of using geospatial data

 

● Warnings in advance- Data anomalies in geospatial data may warn organizations to imminent events that will have an influence on their business.

 

● Greater Comprehension- Geospatial data may provide firms with evidence as to why and how some analytics solutions work well while others do not.

 

● Heightened efficiency- Organizations can increase the overall efficiency of their operations by utilizing the numerical precision afforded by geographical data.

 

Industry geospatial applications

 

Here are some examples of how different sectors are utilizing geospatial analytics:

 

Transportation Industry -

 

● Highway maintenance: With the emergence of geographic information systems in recent years, highway maintenance has become simple and cost-effective. Satellites can acquire real-time photographs of roadways, revealing the important regions that are suffering problems.

 

● Accident Analysis: Most cities and towns have CCTV, as well as satellite imaging services, which are simple to connect with GIS. Location addressing is used to alert accident emergency personnel to give assistance. In the case of an accident, GIS can serve as a source for a report.

 

HealthCare Industry -

 

● Recognizing Health Trends: GIS enables healthcare workers to spot health-related patterns and more precisely target healing efforts based on such findings. The University of Southern California’s Public Health Program, for example, uses geographic information systems in many of its many efforts, including the Cancer Surveillance Program.

 

● Enhancing Services: Finally, the use of GIS technology allows community leaders and developers to collaborate more closely with hospitals in order to take bigger strides toward solving national healthcare issues. The approach can assist in determining whether communities require more particular health services, such as rehab centers or elder care facilities.

 

Why React?

 

React is a cutting-edge technology that makes it simple to develop interactive user interfaces. You may use React to create basic views for each state of your application. When your data changes, React can properly update and render the appropriate components.

 

React allows iOS technology advocates to work on both web and iOS/Android applications. This is achievable owing to the simple code fundamentals and code similarities on both systems.

 

React is now one of the most popular online application frameworks. We are sure that the React framework, in conjunction with Redux, offers an unrivaled platform for developing Location Intelligence apps. It is very adaptable, declarative, scalable, straightforward, and quick.

 

Significance of React in Geospatial solutions

 

An open-source geographic data visualization tool for web application development can provide a low-cost approach to add geospatial visualizations into data solutions. One such example is Mapbox-GL, or, if you’re working in React, a wrapper of Mapbox-GL like Uber’s react-map-gl.

 

Mapbox-GL employs vector maps for speed and allows for simple customization of map visualizations like as choropleths, cluster markers, and even 3D maps, as well as customizable controls to modify zoom, compass heading, and elevation pitch of the map perspective.

 

Web-facing geospatial visualizations produced using open-source JavaScript packages may also be integrated with a browser-based user interface to adjust the configuration of map visualizations, allowing a data team to explore multiple geographic visualizations without having to rewrite code. Connecting geospatial visualizations to a cloud storage lake in the backend can provide scalable, value storage with an API for standardized query capability, allowing geographical data to be loaded on the map in the front end.

 

React-based browser-based geospatial visualization components have been developed by software suppliers. These components can be deployed, altered, and integrated with clients’ in-house cloud applications or included in Software-as-a-Service solutions for commercialization. They have linked these components with other data visualization dashboards and can assist companies in developing data lakes and APIs to store and analyze geographic data at scale.

 

Several React Geo-Spatial Libraries

 

● Using a declarative API, create beautiful React SVG maps using d3-geo and topoJSON.

 

● Based on Google Maps, the React geolocation component

 

● Bridge React Native module to convert address to geo coordinates.

 

● A bundle of geo-related libraries for React, Ant Design, and OpenLayers.

 

Conclusion

 

The development of the online application, as well as the iOS and Android applications, was faster and smoother with React. This increased the application’s productivity and stability in geographical solutions. React offers several advantages, and it is currently generally acknowledged in the industry. The greatest tool for geospatial solutions will be a combination of online APIs, maps, and a strong, clean, and pleasant mobile or one-page application created using React.

 

Like other businesses, if you too are looking to develop solutions with React, Mindfire Solutions can be your partner of choice. We have deep expertise in React Capabilities. With a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years.

 

Content  Source: Medium

Digital Transformation Shaping Future of Retail Industry

 

 

Retail industry, one of the most fundamental industries of any economy was at cross-roads in 2019. 2017 had seen bankruptcy of household names like Toys R Us, while the same year Walmart posted record sales. During the same time, Amazon was becoming a bigger behemoth with each passing year, while traditional retail was still the leader in market. Digital transformation of the industry was inevitable in all aspects, but there were retail firms dwelling on it.

In early 2020, COVID-19 virus infection spread across the world and entire world was caught in a never experienced before lockdown. Retail emerged as both one of the biggest victims and at the same time one of the winners in the ensuing 2 years. As the world is still trying to adapt to the post-pandemic new normal, the crossroads of retail is no more there. The writing is on the wall — “Digitalize the Supply Chain or Perish”. It is clear in 2022, that for retail business to go into the next era, have to leverage technology and rethink their business model.

Primary learnings in retail digitalization:

• Technology adoption speed: Retailers with a system to quickly experiment with new technology and adopt it across the value chain are more likely to succeed in the digitalization journey. The two areas which have emerged as critical for the next decade are following:
• Adoption of Artificial Intelligence (AI): Even though digital transformation of retail has been ongoing for the past 3 decades, the almost infinite ability of AI and Machine Learning in predicting demand, inventory management and customer behavior analysis has enabled the digitalization possibilities tremendously.
• Adoption of cloud servers and technologies: Cloud based technology allows retailers to achieve scalability and flexibility of operations without the costs and responsibilities of local infrastructure
• Consumer experience: Consumer experience, both in online and offline retail is greatly enriched with new technologies. Technologies like Internet of Things (IoT), Beacons, High Speed Connectivity, Robotics etc. are giving consumers improved check out experience, browsing experience, personalized sales and marketing offers and compressing delivery mediums.
• Better asset and security management: Technology like IoT using RFID and sensors can help in locating assets and inventory management. AI and ML based behavioral analysis combined with sensor technologies at the exit and checkout counters can effectively put an end to theft or suspicious activities.

Key technologies leading digital transformation in retail:

Sales & Marketing improvements:

1. Enabling Multi-channel strategies

Customer expectations fuelled by internet, are changing at a very fast pace. They do not care about the source and process involved in the back end. They are also likely to use multiple channels for shopping and it is imperative for a true retail player to be present in multiple channels and look at delivering high quality customer experience at each level. However, the experience in each channel has to be backed by central promise and consistent across channels. Multi-channel digital strategy must focus on data insights generated using ML to build a cohesive view of customer’s buying behavior. Harvard Business Review, has analyzed customer spends and come to a conclusion that shoppers using 4 or more channels for purchase are likely to spend more than customers who use 1 channel.

2. AI powered customer service

Customer service has seen a sea change in recent years with the advent of 24/7 chatbots. What we have seen actually delivering the best results is a hybrid combination of chatbots and human intervention if the chatbots are not able to solve customer query. Hybrid combination has improved resolution time and decrease cost significantly. Chatbots are AI powered, which means that with time and more data, they will be solve more customer queries in future and in faster time.

3. Beacons

Apple introduced beacons in 2013 and since been a leader in beacon technology use in retail. As per beacon technology, the customers will have beacon enabled wearables or mobile phones and upon agreeing to marketing offers will receive personalized marketing and promotional offers. Retail outlets have beacon sensors which identify customers using beacons and provide personalized offers as per the analytics of each customer. Beacons are expected to reach a market size of $25bn by 2024.

Assets and logistics management:

1. Use of IoT in inventory management

RFID tag enabled smart shelves have been developed by Amazon which directly interact with AI applications based on the cloud. This enables real-time analysis and predictive inventory management

2. Use of Blockchain in better visibility and security of the logistics chain

Blockchain enables visibility of the supply chain without compromising on the security. As Blockchain Technology is almost impossible to be breached, it will also provide better clarity and transparency of processes.

3. Cloud computing networks to provide flexibility, scalability and sustainability

High speed data connectivity has enabled Cloud Computing to become the choice for all future application development. Logistics in supply chain requires remote access and seamless data flow. Cloud computing is the best and cheapest way to achieve that. It also reduces fixed cost by eliminating server investments. Cloud computing also reduces retail industry’s carbon footprint as the industry tries to score better on rising consumer demands of sustainable growth.

Process improvements using power of data analytics:

1. Machine learning powered retail analytics

High number of transactions in a retail environment also generate massive amounts of data at all levels of the value chain. Data analytics has shown to directly improve revenue by an estimated of 8–9%. Machine learning allows much faster processing of big data and throw insights which can be directly implemented. In combination with AI models, the insights generated from data analytics using ML, performance can be tested across processes in logistics, marketing, design etc. and implemented.

2. Process mining

Process mining is used when a deep dive is required to understand any particular process and make improvements. The data and insights churned by ML is used in various algorithms and applied to processes and simulations are conducted. Then the conditions are tested in real time against test parameters provide process improvement actionable strategies. Process mining is best used in measurement of value creation using digitization actions as it identifies root causes and provides potential solution, even in real-time environment.

Operational Automation

3. Automation at an enterprise level

Any process or system that can reduce human impact and at the same time increases overall productivity of the system can be considered as automation. Automation helps inf reduction of operational costs, errors and processing time. Primary enterprise level automation in the retail industry are as follows:

a. Inventory/supply chain management using IoT and cloud technology

b. Cloud based ERP technology

4. Automation at store level

Application of robotics in combination with IoT, cloud-based applications and robotics has enabled Self-checkout systems to make rapid progress in the last few years. Apple, Amazon, Walmart and Microsoft are betting big on the self-checkout automation process. Consumers can use RFID or tag readers and their payment details can be stored on a Blockchain enabled secure cloud location. The checkout is largely automated due to smart tagging using RFID and payment is settled at the click of a button by the consumer. This has resulted in higher revenue per session, shorter cues and improved checkout experience

In Conclusion:

Retail industry is poised to get on a new journey of digital transformation starting in 2022. Along with the exponential growth expected in e-commerce, conventional retail is also expected to continue to exist in somewhat of a hybrid format. It is an imperative for the industry to not only adopt digital technology but also work with IT firms to develop innovative digital solutions.

Supply chain innovations like AI powered smart transportation, robotics to eliminate human error and predictive analysis of demand are all going to grow at an explosive pace. Retail players are needed to be more agile and updated now than ever before in the fast-changing post COVID-19 pandemic world.

Like other businesses, if you too are looking to develop retail solutions, Mindfire Solutions can be your partner of choice. We have a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years.

Here are a few interesting projects we have done in Retail Industry.

Content Source: Medium

How to solve critical business challenges with API Testing

 

Application Programming Interfaces (APIs) are sets of functions that allow your software application to trace data and interact with external software systems or components.

Some instances of APIs include logging into an application using a social media profile, paying online via PayPal or accessing local weather snippets on search engines.

What Is API Testing?

API testing is the way to verify the health of every API within the software system. This API testing approach ensures that all APIs’ functionality, security, reliability, and performance stay intact.

Unlike UI testing, QA teams run API test cases without interacting with the software product’s user interface. Instead, QA engineers pay attention to testing the business logic layer of the API framework.

Surpassing the user’s experience in testing your application, the QA team needs to resolve many challenges in manual testing by running API tests.

There is a need to implement custom solutions. However, these are some common challenges everyone runs into.

Value of API in business

APIs enable businesses to :

· Connect with customers:

An effective API can give potential customers additional reasons to interact and connect with their business on a personal level.

· Streamline operations:

The insurance company could develop private APIs to be used by its employees — for instance, to give accurate information to the sales team that can help them calculate quotes more efficiently, even if they are on the road, through mobile apps.

How to Overcome Challenges in API Testing

Unlike the challenges in manual testing that occur in the user interface, QA teams must tackle API issues in the API framework and business logic layer.

This API testing approach often prevents IU issues before manual testing. The dashboard shows its own set of obstacles by executing API test cases before interacting with your product.

Luckily, you can reduce the challenges faced in API testing by implementing the best practices:

1. API Testing Setup

Manual testing makes sure what works and what do not. However, automated testing is also necessary with API to determine how well they can work under pressure. The most challenging part of the process is to set up the testing infrastructure and run it.

Solution:

To win over the testing challenges, you need to figure out how your APIs look in the design phase to have the APIs 100% uptime.

2. Updating API Schema

Working with an ever-changing API helps facilitate demand in today’s API economy. Although, when APIs update, the data formatting handling requests and responses must also be updated. Else, it can lead to a slowing down of the whole process.

Solution:

To avoid the downtime challenges, thoroughly test the API in alpha and beta environments. The chances of issues go down to 90 percent if you do so.

3. Sequencing API Calls

In many cases, API calls require appearing in a specific order to work accurately. This generates a sequencing challenge for the testing team. For instance, if a call to return a user’s profile information goes through before the profile is even created; the request will return an error. This becomes more complicated when more applications are involved.

Solution:

We suggest making a flowchart to visualize the API calls. This helps developers build API calls and integrate them quickly without causing issues.

4. Tracking Systems Integration

It’s essential to make sure the API testing system is functioning correctly with the data tracking system. This helps bring back correct responses on whether a call is working correctly.

Also, it’s used to monitor API performance passively. To dodge any challenges here, rethink your application in the design phase or how it will integrate.

Solution:

Ensure you aren’t causing any applications failure by testing in parallel with critical integration systems. This can be done by implementing and involving load testing in your continuous delivery.

5. Testing All Possible Parameter Request Combinations

APIs handle communication systems by forwarding data values to parameters & transiting the parameters through data needs. It is important to test all the essential parameter blending in the API to check for flaws in specific configurations.

A significant project could end up assigning two varied values to similar limits or creating instances where numerical values are at the pace of text values. The addition of an extra parameter increases the no. of likely combinations exponentially.

Solution:

Pick applications that are simple for everyday operations. This way, you can see how the API is being used, plus if any configuration modifications are required to have a GA (general availability) release.

6. Validating Parameters by Testing Team

Validating the parameters is one of the important things, but challenging sometimes. It must showcase how fast you are serving those parameters. The team must be sure that every crucial parameter data uses the appropriate string or numerical data type fits within length limitations, an assigned value range, and passes another validation criterion.

Solution:

It can be resolved by having continuous synthetic API tracking and monitoring to grab the issues early on. Furthermore, it must be combined with an APM solution to have a complete 360-degree view.

7. Allow Time for Familiarity with APIs

While most QA testers are familiar with manual testing challenges, they may not be as versed in API testing. To your knowledge, many peers on your QA team might not be familiar with an API framework or even comfortable running API test cases. A solid API testing strategy doesn’t thrive when your team doesn’t have the skillset for testing APIs.

Solution:

Give comprehensive training that explains your APIs and the business logic layer of your product. Review with your team the rules dictating the usage of your APIs, right from copyright policies, rate limits to storage policies, and display policies.

If possible, hire QA engineers for your team having extensive API testing knowledge and experience with the challenges faced in API testing.

8. Ensure the Framework Is Suitable for APIs

Any upgrade to your product or within the API can drastically alter how your framework supports APIs. Also, validating the parameters within your API framework is a daunting task, especially when your APIs need specific restrictions and validation criteria.

Solution:

Continuous APIs testing throughout the development cycle also catches defects early, letting developers resolve the issues sooner.

Regular review of the framework ensures your framework is suitable for testing APIs. And when in doubt, ask yourself these questions during inspection:

● Does your framework allow integrations with GUI tests?

● Will the framework supports GUI tests?

● Can the framework use API libraries and build management tools?

Conclusion

API testing is an important part of application development in the modern business environment. Letting it slide can be a big mistake and cost you big bucks. It’s better to be careful and alert with the system and follow a routine check-up to make sure everything is in place.

If you are looking for custom API Testing Services, we can be your partner of choice. Mindfire Solutions has a team of highly skilled 650+ certified software development and testing professionals, who have been serving global clients for over 20+ years.

Content Source: Medium