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If your job has anything to do with IT and software development, you might have heard about Flutter. Despite the beliefs, Flutter is not one of the mobile development frameworks. It is not a library either. So, what is the Flutter definition? It’s an open-source, free tech for developing software of different types. Only one codebase is required. Flutter is a full software development kit (SDK).

Flutter has a community way narrower and younger than React Native or Ionic. There are plenty of options that make Flutter attractive for various development teams. Other platforms for developers lack features found in Flutter. The pros of this platform include:

• A comprehensive SDK;
• A full set of widgets;
• Architecture grounded on reactive programming;
• C++ rendering engine;
• Support of different operating systems.

Most often, SMEs and big brands benefit from using Flutter in their application development purposes. To create a nice application, it is better to hire a specialized Flutter developer who specializes in different mobile app development tools. This programming language is very specific, based on Dart as coding. Now, you may have often heard about Dart. These two are interrelated. However, they are still different. So, let’s talk about the difference between Dart and Flutter next.

Difference Between Dart and Flutter

Dart is the programming language used to code Flutter-based applications. This fact alone makes it different from Flutter. Dart was released a bit earlier than Flutter. Still, they are almost the same age. When you have a look at these two for the first time, they may seem difficult to understand. Those acquainted with React Native would find Dart rather cumbersome. However, it is not that difficult to find documents aimed to make it all simpler and clearer after moving from one programming language to another. You may also use Flutter application development services for your purposes.

Unlike Flutter, Dart may remind you of C. Those who love working with Java will not find this code all that difficult. Dart is an object-oriented language. Just recall everything you know about Java and C to succeed. As one thing is based on another, we can say that Flutter JavaScript is possible as Flutter apps are written in Dart.

Most often, developers turn to Dart to come up with original apps for various mobile devices and operating systems. Ecma has approved this programming language. Users who want to create anything on the internet or for desktop can use Dart for their purposes just like mobile application developers. You only need a different approach to the Flutter web app. The major difference is that it’s transpiled to JavaScript while being applied to web applications. You’ll need a virtual machine to run the .dart files. 

So, what about the connection between Dart and Flutter? In the first case, its native files are packaged into a binary file when used in Flutter software. It is not Dart that uses Flutter; it is vice versa. Dart can apply Just-in-Time compilation, meant to ease and speed up the development of Flutter apps. In the second case, developers can create software with the help of Visual or Android Studio, as well as IntelliJ IDEA. Flutter UI design is just brilliant in most cases. Flutter makes it possible to solve complicated problems with user interface thanks to 2D, APIs, gestures, etc. 

What Makes Flutter Future of the Web/Mobile Development?

The primary rule of UX is plenty of user examination. It’s necessary to avoid handing in a Figma file with a design that only looks good. In contrast, Google’s Flutter may be more effective for creating an app. It offers an expanded library of widgets that make it possible to implement rough ideas from designers without software that looks like a horrid prototype of a Windows 98 application. Applications stray away from the development of revolutionary interface elements.

Many call Flutter the future of any Flutter mobile app development company. Why?

• Easy Installation with Perfect Doc. Due to the fact Flutter is maintained by Google’s Material Design, it’s simple to set up and use. The attached documentation makes it easy to understand how to develop apps with Flutter.
• Minimum Coding Needed. Flutter allows using just one codebase for app development. It decreases time and effort.
• Custom UI Widgets. Customizable UI elements allow for a user-friendly interface. You’ll get access to all tools in one place.
• Quicker Development Process. Except for the speeded-up processes, Flutter allows debugging applications. It possesses low testing requirements. It’s possible to create two native mobile tools with just one framework.
• Reduced Expenses. The average price of building a mobile solution is roughly 30,000 USD. The upper threshold is usually 100,000 USD. Apart from development, consider server expenses, marketing costs, team building fees, etc.

Final Thoughts

Now that you know everything, from the Flutter definition to what makes it different from Dart, you can decide whether this platform suits you. To some developers, Flutter might seem simple, while to others it may look rather cumbersome. It depends on the initial knowledge of various programming languages and skills. 

You can also contact a Flutter mobile app development company at any time. They will help you find an application or web developer for your project. Master new codebases and create brilliant solutions today!

Many modern companies, when starting their business or changing their internal processes, resolve to choose a commercial software package as the safest option. Those are the ready-made tools anyone can buy, download, and use as-is. While they remain an excellent choice, if you want to receive customizable software that can be custom-fitted to your needs, you might want to take it up a notch and choose a custom software development.

What is Custom Software Development

Even in the era of customizing every service and product available, there are still some who don’t fully comprehend what is custom software development. It’s a process of creating an application precisely tailored to the requirements of a specific company or organization as opposed to common from-the-box tech solutions.

With custom development, you don’t have to search the market for software that will ideally satisfy all your demands. You’re lucky if you can find that one application that meets all your company’s conditions. Possibly, a couple of tools, if your needs are too diversified.

Custom software contains a set of hand-picked programs that are designed to work specifically for your business process. The developers take into account your industry, your clientele, your employees, your strategy, or the plans for the route your company is going to take in the future.

Benefits of Custom Software Development

Custom software is a great option for companies whose requirements are much less mainstream to choose a standardized tool made for a broader audience. Here’s the list of some of the biggest benefits of custom software development:

• You can overlook the whole development process and testing, make numerous quick or more complex changes to it - add or exclude any features, customize the design, the layout, or any other software component;
• The development company doesn’t just sell you the software - it also helps deploy it and provides necessary scheduled or unexpected maintenance afterward;
• The quicker adjustment period and the smoother adoption of the software since the more familiar and tailored features and programs will require less training and disruption of the working process;
• More seamless integration with already existing applications and organizational infrastructure - no need for extra modifications, which saves you time and money. The new software’s language can also match your other programs.
• If paying a large sum of money at once is an issue, you can start with basic programs and then proceed with the layering - add more and more functionality over time, which will evenly distribute effort and costs.

How to Choose a Software Development Company

Here are our tips on how to choose a software development company. 

1. Expertise. Check all the certificates and credentials of the provider. Vet their background and industry qualifications - how many years of technical experience they have, the number of successful project implementations (in your domain), performance, and expansion history.
2. Development process. Research what practices and project management styles the company follows - the most popular ones are Agile, DevOps, Scrum, Kanban, Hybrid, Lean, etc. Each of those has pros and cons, and may not correspond with your values.
3. References. Many companies place their most cherished reviews on their websites - read those, but also go through the list of previous clients ( ask about if not already available) that had not left their testimonials. Call, email, or speak to them directly.
4. Maintenance and support. Aside from a guaranteed quality of the finished product, the software provider must deliver post-purchase maintenance and support. Ask if the company can ensure security as well since they will be dealing with sensitive or confidential data.
5. Flexible approach. Check if the company provider will be able to ensure a software integration with your programs that are already up and running. Refusing to adjust is a huge red flag.

Examples of Custom Software Development Companies

When selecting a custom software development company to partner with, there’s a lot of different software types directions to go, depending on the most suitable solutions for you at the moment. Here are some examples with a few helpful links:

• E-commerce platform - both desktop and mobile.
• Software-as-a-Service - cloud-hosted on a subscription basis.
• Enterprise Resource Planning (ERP) to manage most of the internal processes - accounting, PM, supply chains. The most popular systems are - Oracle, Microsoft Dynamics, Sage.
• CRM. Customer Relationship Management is essential when dealing with a customer database of any size.
• Cloud Applications for accessing a large number of programs through the cloud and decreasing the amount of physical data.
• Project Management Software type for better workflow automation.

Conclusion

Out of loads of custom software development companies currently on the market, choose the one that will understand your goals, as well as your employees’ and your clients’ needs. Use our tips above to make a list of pros, cons, and requirements.

If you have any questions or a particularly enticing idea you want to bring into existence, hit us up using this link.

What is a good web application? There is no universal answer to this question since various people dealing with it have their own requirements to cater to. A customer would like it to be a problem-solving product that is simple to use and attractive-looking. An entrepreneur wants it to find a proper market niche. A developer aims to create the one that will be functional, capable to operate under high traffic loads, and having scalability potential. To have all these aspects implemented in one product, software engineers can choose between several types of web application architecture.

In the digital world of the 21st century, many existing words have acquired new meanings. Clouds aren’t weather phenomena anymore, cookies have nothing to do with pastry, and the platform isn’t a thing to be looked for at a railway station. The same is true about architecture that has ceased to be related to the construction industry only. When we talk of web app architecture we mean an arrangement of various elements and their connection within this software product that guarantee its web experience. How does it happen?

When a user enters an URL into an address bar of a browser, the latter treats it like a request and asks for access from the site after locating it. The server where it is hosted asks the browser for some data. The browser in its turn translates it and displays it for the user to see as a website. Being quite simple to explain, this process is rather complicated in operating, as can be seen from the following web application architecture diagram.

What are the principal components of web applications?

• Database. As the name suggests, it is the storage of data for the application. Typically, it is kept on a database server. The most widely-used of them employ SQL and enable storage of high volumes of data in the form of tables and rows (as MySQL and PostgreSQL do) or making use of collections and documents (as is the case with MongoDB).  
• Server infrastructure. This is an entirety of resources (both physical and virtual) that  receive and process browsers’ requests providing data analysis along the way. Other responsibilities of the server infrastructure include running and processing business logic and storing data – both files and databases. The most popular infrastructure examples comprising hardware, software and networks are AWS, Azure, DigitalOcean, and some others.  
• Back-end. It is the code in the form of the procedures stored on the server whose responsibility lies in handling business logic. It is meant to react properly to HTTP requests and send the required data back to the client’s browser.
• Front-end. This aspect encompasses UI/UX elements that the end user sees and interacts with while operating the app. Such visual features include layouts, notifications, activity tracking, third-part services, etc.
• API. This is a bridge used for data transference between architecture components (back end, front end, and the server). Today, IT experts recommend two APIs as most efficient. RestAPI forwards a set of rules that developers follow to create their API. GraphQL is even better since it furnishes a comprehensive data description in the API you use, streamlines API evolvement over time, and empowers leveraging robust developer tools.
• Third-party services. These are services that aren’t provided by the app owners. Conventionally, such services are various marketing tools and social networks. Essential services for business apps comprise card payment gateways or video conferencing functionality.

These components can be related in three basic ways.

Despite the seeming plethora of existing models, all of them can be classified into three broad categories.

1. Legacy HTML Web App

This is the most widespread type that is grounded on a user receiving the entire HTML on request. Known also as server-side or Web 1.0, this scheme requires the web page to reload to which page logic and general business logic react. Being extremely SEO-friendly, secure, and fast to develop, this model of web app organization has serious shortcomings as well, including low responsiveness, problematic offline functioning, and non-existent potential for conversion into mobile or desktop apps. Besides, this static pattern model can’t be used for building dynamic projects.

2. Widget Web App

Being more suitable for mobile apps, this type presents the next step in web app evolution since it doesn’t need a request to load a page. Instead, widgets employ AJAX queries to receive portions of data in JSON and HTML. It is more responsive and quicker in performance than the legacy type, yet its downsides are penetration vulnerability and a long time of development.

3. Single Page App

In this scheme often referred to as Web 2.0, some functionality is shifted to the customers, who employ it in creating such products as blogs and social networks, to name a few. In essence, it is a complex JavaScript-reliant application that reproduces the page’s HTML content. This type of organization logic generates excellent performance and responsiveness as well as offline work. Such web apps are easy to scale up and transform into other app types.

The successful functioning of a web app depends not only on its own architecture but on the architecture of the server as well.

The choice of the server architecture to be employed in app building is determined by the expected performance parameters (speed, storage, processing power, etc.). Having accumulated considerable experience in web app creation the specialists of Axisbits recommend the following server architecture types.

• PHP web application architecture. PHP is considered a web development language with universal acclaim. This popularity is conditioned by its simplicity and high functionality. Consequently, web apps built with it are secure, swift to develop, and simple to maintain. Besides, friendly support from a sizeable community guarantees timely assistance in case issues arise.
• Laravel web application architecture. The syntax of this PHP-based framework is graceful and expressive. Having the Model-View-Controller architecture at its core, it abounds in features making seamless and prompt development a breeze. The architecture of complex web applications with examples in Laravel PHP sports modular packaging scheme, improved authentication, sessions, and caching. Routing in Laravel deserves a special mentioning, since it enables building multiple routes whose names can be accessed via individual URLs. All of these allow developers to make the most of the web app performance and enhance traffic.
• Azure reference architecture web application. Introduced and supported by Microsoft, this architecture is devised to act as a bridge between good old tools and cloud solutions. Moreover, the specialized cloud platform by Azure makes use of the best web app practices as well.

As you see, the variety of web app architecture types (as well as the app server organization patterns) is so great that it is easy for a layman to get lost among them. If you want to receive a top-notch product, it is wise to address experts in the field. Our company can tackle any software development project, impressing you with the first-rate quality of the output and reasonable pricing policy.

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Flutter is a relatively young yet quite full of promise and functional allure platform. Due to its simplicity, similar to web apps development, and quick performance equal to native applications, this open-source framework has gained many dedicated users over the last few years, which resulted in quite a few Flutter apps.

To reach an even bigger amount of global customers and make sure anyone whose native language isn’t English can fully enjoy everything this tool has to offer, Flutter localization and internationalization for your apps are necessary. Let’s take a closer look at what that is and how it’s supposed to be done.

Introduction to Flutter Localization and Flutter Internationalization

User experience appropriately remains one of the top objectives and responsibilities among both designers and developers, which means accomodating a platform to the local or multilingual needs of your users has to be a priority. 

If you’re looking for an effective and user-friendly cross-platform solution, Flutter is arguably one of the best frameworks you can find on the market right now. This mobile, web, and desktop app development tool helps the result of your development work look and perform great on any device.

The Flutter in-app localization mechanism is slightly different from those of other native apps. Its native localization package contains multiple localization points for widgets. Check out this document for the list of currently supported locales.

To ensure an easier Flutter internationalization and localization processes, you need to pay attention to your layouts and text design while you are still writing your app’s original version. There are available classes and widgets for that, as well as already internationalized libraries. 

Differentiating Between Internationalization and Localization

Despite having seemingly similar connotations, internationalization and localization are not interchangeable terms. However, they are quite complementary in app development and are used one right after the other to ensure a smoother app adaptation. 

In computing, these two terms are also known as i18n and l10n, respectively. These abbreviations are made of the first and the last letter of the word, between which is the number that is actually the number of letters between them.

The main difference between internationalization and localization is that internationalization is done by developers and localization - by translators that know the linguistic and stylistic differences between chosen languages.

Internationalization is the preparatory process of customizing your code that is set up before localizing the app to make it susceptible to modifications. It consists of methodologies and strategic groundwork that helps avoid or solve such potential problems, as encoding difficulties, lack of hardware support in certain countries, or not enough space for alternatively sized text.  

Localization is a series of steps that help add support for different languages, regions, and scripts. It is the subsequent process of utilizing all the previous adjustments and adapting the app to cultural, stylistic, linguistic, structural, or even legal requirements of another language.

Internationalization and Localization Examples

The most widespread Flutter localization example and method nowadays is the one using the official supplementary Intl translation package with Intl library from the Dart team. The most essential thing you have to do before internationalization is to set apart the source code from the bits of text you need to translate.

The internationalization framework will usually use the Application Resource Bundle file format based on JSON and the Localizations widget inside MaterialApp. The JSON file will later contain the translated strings. LocalizationsDelegate class will notify the MaterialApp and help you create a class containing dynamic string properties or functions for every translatable text of your app.

You should also prepare the design of the pages you’re about to edit and translate. The text may be shorter or longer than the original source, it may contain non-cyrillic letters, be right-to-left, or require contextual shaping. Other important elements to be aware of:

• Plural definitions and quantity names;
• Genders of both individuals, animate, and inanimate objects;
• Standart and phone numbers;
• Currency values;
• Date and time formats - different order of writing and separating time;
• Units of measurement - metric or imperial;

Here are also a few heavily code-based instructions and examples for you to choose from if you decide to internationalize and localize your Flutter app by yourself:

• Flutter internationalization example and guide by Flutter itself;
• This helpful tutorial from Localise;
• This guide that’s a part of a large Flutter development series;
• The guide from Phrase’s blog.

Conclusion

If you’re a Flutter app development company, then you definitely realize the importance of localizing and internationalizing your apps when you have users from different countries. Among all the distinct ways to do it that are currently circling the Internet, there should be a method or two that will better suit your needs. If you have any questions, don’t hesitate and click this link to contact us.

There are two popular definitions in the contemporary digital discourse: data science and business intelligence. Both are frequent when it comes to data management in the context of business processes and marketing. The indiscriminate use of both definitions leads to sorrowful misconceptions oftentimes. 

However, the difference in meaning between data science and business intelligence is not so fine to make them both interchangeable. The difference is similar to the one taking place between the words “data” and “information”. Of course, particular nuances are available as well.

It is worth knowing the nuances not to confuse the definitions. It allows dealing with both data science and business intelligence without expecting irrelevant outcomes that those practices can hardly deliver by default.

Let’s dive deeper into the distinctive features of data science and business intelligence to make things right.

What Stays Behind?

Both activities include data collection, modeling, and intelligence gathering in a broad sense. Probably, this is all that unites both technologies. Then, only differences follow. 

Business intelligence is specific for certain business-related issues such as price, profit, efficient use of resources, etc. In contrast, data science represents the ways how various factors (social, spatial, seasonal, etc) affect business as a whole. Data science brings data to processing algorithms while business intelligence has to use already available algorithms and technologies.

At first sight, both terms are interlinked tightly enough to be interchangeable. But in fact, this is not so. Different sorts of data stay behind the two technologies making their distinction drastic. But more on that later.

Historically, business intelligence has been known since the last decade of the 20th century. This is an applied-science discipline widely used in business management. Data science as a separate subject was formed in the 2010s approximately. To recognize the difference between data science and business intelligence it is, first of all, necessary to consider some basic notions related to both entities. 

Data, Information, and DLCM

If we take the word “data” as a term, it means the raw unprocessed flows of data coming from various sources capable of generating any data as such. When we speak about information, we mean processed data having a certain sense in one or another context. Classification of data types along with data lifecycle management (DLCM) is worth mentioning here as well.

DLCM implies numerous activities related to data processing. When we collect, classify, save, record, use, and delete data, the data lifecycle management takes place. Data classification implies the following types of data in the present digital environment:

Well-structured data. This type implies clear and visible data. Quite insignificant processing is needed to interpret such a type of data. This is what can be called information.

Semi-structured data. Not entirely random data is meant by this type: a kind of poor structuration is available to some extent. Some analysis is required to find data correlations.

Non-structured data. This is just random data that requires complicated processing to turn the data into something meaningful. 

When basic notions are defined, it is easier to understand what is what.

What is Data Science?

Data science is an interdisciplinary area that refers to decoding (and even demystification) massive amounts of data. This is about Big Data only. Mathematics, statistics, computing, machine learning, and other related research fields constitute data science in combination. The following five stages shape the workflow of data science: 

1. Data collection
2. Data retention
3. Data processing
4. Data analysis
5. Data reporting

Even though the stages reflect quite a generalized scope of activities, data science appears to be a complex scientific approach to what turns into information eventually.

What is Business Intelligence?

Business intelligence is a spectrum of technologies and practices that cover business-related information to be collected, compared, processed, and analyzed. Business intelligence is great at monitoring business efficiency to improve business planning. 

Business intelligence comes to a deep analysis of business processes at the end of the day. That’s why business analysts are the ones who practice business intelligence. They use various forms of quantitative analysis along with iterative algorithms of prognostic modeling to interpret business data. The statistics they use help understand what has been happening in the company's business activities to develop strategies for further growth. Business analysts solve complicated problems referred to both profitability and cost reduction.

Types of Business Analysis

Business intelligence is based on data-science technologies that can unlikely be understood by non-specs. Nonetheless, the available basic types of business analysis address quite simple questions that can be raised by any business person. In other words, each type of business analysis is determined by a corresponding question to be answered. Here they are:

• “What’s happened?”. The question reflects the descriptive business analytics that can be performed with quite simple tools (MS Excel, for example) via such methods as detailing and correlation;
• “Why did it go down the way it did?”. This is about diagnostics that rely on various analytical techniques based on data analysis;
• “What’s coming next?”. Predictive analytics come into play with both statistics and mathematics. This type of business analysis is the most complex one having the following sub-categories:
  - predictive modeling
  - root causes analysis (RCA)
  - identification and validation of data (Data Mining)
  - forecasting (what is to happen if the trend keeps going)
  - the Monte Carlo method (how it will go what is to go)
• “What does it need to be done?” The prescriptive analysis is a call-to-action from a business standpoint. This is when tactical recommendations in the style of “try so” appear to optimize business processes. 

Data Science vs Business Intelligence From a Managerial Perspective

Data science covers many interdisciplinary areas such as computing, mathematics, statistics, programming, AI, machine learning, and the like to address the challenges related to Big Data processing. In contrast, business intelligence serves to solve particular business issues in which analytics, planning, modeling, and predictions play critical roles. Formally speaking, business intelligence can be considered a branch of data science.

Nonetheless, the managerial challenges inherent in various business activities can reverse the relationship between data science and business intelligence. In many cases, it is hard to determine which of the two has a higher priority for business managers. It is worth compartmentalizing typical aspects inherent in business management to see how data science and business intelligence behave in each case.

Use of Data

Data science utilizes all three types of data (well-structured, semi-structured, and non-structured) that comprise the so-called Big Data. Business intelligence deals with well-structured data only (information) that requires no extra processing to be applied to analytics.

Required Skills

Data science engineers have to be savvy in computer sciences, statistics, mathematics, programming, and data analysis to be able to work with massive amounts of raw data. Besides, such advanced technologies as artificial intelligence, deep learning, and neurolinks should also be present among the skills of data science specs.

Business intelligence engineers should possess mathematics, statistics, modeling, and planning to be able to optimize business processes by using relevant information collected for analysis.

Scope of Application

The business-related scope of data science includes a complex analysis of numerous factors that may affect customer behavior. Data science allows identifying common trends as well as modeling behavioral patterns. 

Business intelligence provides various analytics on the ongoing business processes, profitability, cost reduction, sales forecasting, demand management, etc. In other words, the scope of business intelligence includes certain business tasks.

Typical Domains  

The sectors where data science is frequently used cover education, technologies, academic research, finance, and e-commerce.

Business intelligence ranks high in industries, marketing, retail, technologies, and finance.

Decision-Making

Since programming in a broad sense seems to be the main activity in data science, no critical decisions with regard to business processes can be drawn from findings of data science by managers.

The very results of the statistical analysis provided by business intelligence imply making critical business decisions at the end of the day.

Main Tools

Programming is the basic activity in data science. Various programming languages can be applied, but the most popular are Python and R. Many other technologies that belong to computer science such as AI, ML, Hadoop, TensorFlow, Spark, neurolinks, and the like constitute the toolkit of data science.

Statistical analysis is the main process in business intelligence. Such tools as MS Excel, databases (SQL, etc.), Power BI, Cognos, and highly-specialized packages of statistical software serve business intelligence specs.

Workflow

The working process inherent in data science includes a lot of studies and works on data extraction. The workflow is interdisciplinary by nature.

Routines with numerous iterations constitute the typical workflow in business intelligence. But in each case, business-specific activities take place.

Conclusion

Data science and business intelligence can overlap in many aspects once both activities imply the processing of various data. However, they differ in the scope of application and working routines. Besides, the types of processed data make data science more comprehensive and integral in comparison with business intelligence.

At the same time, business intelligence is focused on business-specific information to a greater extent than data science is. Hence, business intelligence seems to be more applicable to commerce activities from a managerial perspective.

Contact us today to determine which activity - data science or business intelligence can meet your business challenges best. But whatever choice may happen, our experts will assist you equally well in both domains. 

The evolution of the mobile technology industry is striding at lightning speed. And services of a well-established, qualified React Native app development company are in quite an intense demand right now. That’s why we decided to timely remind you about the potential of this technology in the market based on the famous React Native-based apps.

What is React Native?

React Native is a specialized mobile app creation framework which is based on an open-source JavaScript library. The platform is used to thoroughly support Android and iOS applications. This allows developers to leverage React along with the native capabilities of the common mobile OS’s.

React Native was initially introduced in 2015 by the software development team of Facebook. Due to its versatility and recognizable creators, the solution quickly gained popularity among developers, startups, and entrepreneurs alike.

Popular Apps Built with React Native

Let’s take a look at the brightest examples of apps built with React Native which you may be using right now.

Bloomberg

Bloomberg is a private financial, software, and media company based in New York. In 2016, the team introduced a new consumer mobile app for Android and iOS to the public. To design it, software engineers used a then-new technology created by Facebook - React Native. The space for concurrent development of cross-platform apps has inspired creators to take risks and rebuild their solutions, achieving more market versatility.

Instagram

One of the most widely and actively used apps in the world. The platform is visited by billions of active users every month and about five hundred million every day. Thanks to React Native, the Instagram team managed to implement a sturdy functionality for Android and iOS at the same time in short terms. And it certainly stood the test of time.

Skype

The Skype creators initiated the development of a dedicated mobile application in 2017. The Android version introduced an improved version of Skype. Almost all parts of the application have changed, but these changes allowed for a smooth mobile experience that isn’t inferior a bit to the desktop functionality.

UberEats

An immensely popular food delivery app. To connect a multitude of popular food outlets, the Uber team has moved their existing app completely to React Native, thereby improving the Restaurants dashboard. The innovations did not keep us waiting long. This made the customer base grow while the UberEats app itself has become one of the most regularly used solutions in the United States.

Walmart

Perhaps the most famous chain of retail stores around the world. Thanks to React, Walmart built Android and iOS apps by hiring one team instead of two. Thus, the team has reduced not only the project development time but also costs. The time-to-market was accelerated as well, and Walmart beat the competition to meet mass consumer needs.

Tesla

The electric car maker also used React Native. Tesla mobile application has retained all the basic functions that bring hassle-free UX on both common platforms.

Facebook Ads

Built by the founders of the React Native framework, the platform is an integral part of FB commercial management tools.

Wix

A website building framework that used React to make a mobile app for building web solutions on the go. It has been freely available since last year.

Airbnb

The leading service in the field of housing search. It allows you to solve the housing issue from anywhere in the world. Thanks to React, Airbnb has accelerated mobile app development tenfold.

SoundCloud Pulse

Created to browse creators accounts. While developing the application, the SoundCloud mastermind found only React Native to be fit for the project.

Shine

Designed to help people cope with daily stress. It contains motivating articles, videos and audio recordings, most smoothly delivered through RN capabilities.

Townske

With this geo guide, you can find the most sought-after attractions in the largest cities in the world. And the performance is made seamless exactly via RN.

Gyroskope

This app lets you track your steps taken, heart rate, workout quality, and much more. React Native allows its creators to cover both essential market niches at once.

Pinterest

Inspires ideas for creativity, cooking, sports. Suggests ideas for decor, gifts, etc. You know what Pinterest is all about. And the sturdy capacities of React Native make browsing this endless database of images and photos seamlessly.

Salesforce

A great business management platform made available on your phone thanks to RN. You can schedule important events and meetings, as well as receive updates on accounts.

Hive

Designed to control devices in a smart home. With just one tap on the screen, you can control heating, water, light, etc. RN helps easily switch between interconnected devices.

Summary

These are not all mobile apps that have React Native as the foundation by far. This outstanding framework will help you create a product that will definitely find its audience in this day and age. We are your React Native app development company of choice when it comes to scalable solutions of any complexity and purpose. Contact us.

Quite regularly here and there the public mind keeps being exposed to informational injections about “mind-blowing inventions”, “revolutionary technologies”, and “disruptive innovations” potentially capable of digitizing any company and even transforming the entire economy. 

However, when key details of all those “marvelous” projects face a critical examination, a very poor understanding of the very term “digital transformation” happens to be inherent in many people who are talking about Digital. A huge number of both opponents and proponents of digitization seem to remain surrounded by myths and biases. 

A sacred duty of any reputable digital transformation agency is to dispel those myths and misconceptions however credible they might sound. If you can distinguish myths from facts you will unlikely become a victim of the spiraling hype about the seemingly total digitization of everything. 

We have selected the most popular five myths about digital transformation that can prevent your project from success. Let’s apply common logic and true knowledge to separate church and state.

Myth 1: Every Company Must Be Digitized

Reality suggests that not every organization, process, or business model needs to be digitally transformed. At least right now. Digitization is about neither updated software nor improved supply chains. This is a well-prepared digital strike on the existing infrastructures that, probably, work quite well so far. Before moving towards digital transformation, any company should forecast what business effects the upcoming changes can result in. Programs for business-model prototyping can help in it.

The first question to be addressed is: can your company create digital models that imitate the existing business processes? And there is nothing terrible if not. It simply means that you will face certain hurdles when trying to translate your workflows into a digital format.

However, digital transformation may appear unfeasible even for those organizations that are capable of modeling their business processes in every detail. It is worth remembering that benefits from any initiative are determined by the growing market share, income, and profit. Besides, if the existing business model with all its workflows and processes is flawless, the effort and expenses to get your business digitized can simply make no sense. 

Of course, nothing lasts forever and the efficiency of any existing business model can go down over time. If you feel that your business is approaching the threshold after which the already digitized rivals can take a bite of your market share, it is time to go digital. Nonetheless, digital transformation should never be a goal in itself. Thorough calculations are always worth making to stay confident about your digitized workflows going to be simpler and cheaper. 

Myth 2: Digital Transformation Always Runs Under Disruptive Technologies     

Reality suggests that the best effect from digitization is brought by well-tested “traditional” technologies rather than by the fanciest (virtual reality) or most promising (machine learning) ones. Good old networks and databases along with time-honored CRM and ERP can boost a non-digitized business almost certainly.

Take the two business giants of nowadays Uber and Airbnb as an illustrative use case: they both rely on operational innovations, not on technological ones. None of the “breakthrough” digital technologies has helped them edge out competitors in the booming sharing economy. Instead, they used “trivial” smartphones, mobile apps, and responsive websites optimized for instant transactions and precise geolocation. 

In other words, the best business effects of digital transformation should be expected from the well-known widespread digital technologies when they are applied to innovative business strategies. 

Even though the thesis is obvious, many business owners refuse to accept the simplicity of the approach. They believe the newest possible technology should be implemented to provide some business advantages. This is how myths about digital transformation appear.  

Myth 3: Just Profitable Companies Tend To Implement Digitized Projects

Reality suggests that if a business goes well (both employees and shareholders feel good with their wealth and property), the possibility of significant transformations approaches zero in such a company. 

Companies having tough times, on the contrary, would dare go digital more likely just because they have to change something (if not everything) in their business models. Successful organizations, especially public ones, are quite reluctant to make any structural changes: the perfect is the enemy of the good. Try to remember any successful company that has drastically changed its business model with no market pressure. 

Fundamental transformations (digitization is the one, like it or leave it) are always labor-consuming and oftentimes painful. The outcomes are not always predictable. Whatever various business bestsellers and pundits can claim, the truth is that people resist any digital transformation if they feel comfortable with the existing business model. Of course, If a company starts facing problems the resistance can rapidly fade away. But before difficulties happen, pushing people to accept digital transformation is almost impossible: don’t try to repair what works well, as they say.

Which organizations have the lowest possible resistance to digital transformation? Companies that are losing clients and money, on the one hand, and startups that are not very sensitive to expenses funded through abundant investments, on the other hand, constitute the spectrum of organizations easily prone to digitization. Sufficient resources along with a well-grounded tolerance to risks usually belong to a company that is one click from digital transformation. 

Myth 4: We Must Disrupt Our Segment Earlier Than Anybody Else

Reality suggests that segment leaders rarely incentivize disruptive transformations since their business models are sustainable due to years of tedious labor. Besides, any digital innovation as such does not guarantee that all market players can accept and follow a new disruptive business model. This is rather a brave startup that can afford to experiment with any sort of digital transformation once it has not too much to lose. Any disruptive project always takes the risk to remain the odd man out. 

Successful examples of disruptive digital transformations that revolutionize the whole segment are quite rare and ambivalent. Digital streaming video from Netflix is still existing in parallel  with conventional TV channels and cinema. The disruptive car-sharing model from Uber has not buried the traditional taxi service completely. Amazon and Alibaba are spearheading the booming eCommerce while brick-&-mortar retailers are unlikely going to leave the stage. 

No one doubts that any segment leader can get ahead due to a self-disruptive strategy. Numerous digital technologies are here to help. But it is worth remembering that the moment of glory does not imply far-reaching positive outcomes for your business. Thoroughly assess your position on the market before jumping into digitization with disruptive innovations.

Myth 5: Requalification Of Staff Is Necessary To Go Digital

Reality suggests that the digital literacy of the majority of modern employees appears sufficient for implementing digital innovations with little to no training. This is a misconception to link compulsory requalification of staff with digital transformation. 

Various studies and expert forecasts add fuel to fire. They predict that 80% of operational skills have to be reprioritized to implement digital transformations by 2022. But such forecasts should be approached with a critical eye. The staff adaptation to digital workflows is worth arranging through a bottom-up model.

In other words, companies shouldn’t focus on the most up-to-date technological achievements and wait around until employees acquire the skills needed to deal with the innovations. It is much better to implement the technologies already familiar to staff. The market offers a lot of tools and systems that facilitate digital transformation beginning from programming languages and up to cloud services. 

Organizations can organically engage employees in innovative workflows through investing time and money in digital technologies that do not require the requalification of staff. Such a seamless integration brings much bigger value to any business than authoritarian management practices that force people to master excessively complex systems.

Conclusion

This is obvious that digital transformation is not another marketing hype. This is the trend that is here to stay. It should be apparent as well that taking on digitization requires meticulous planning and fearless experimenting. 

Digital transformation is not an insurmountable barrier as it might seem at first sight - such understanding will eventually come. Skepticism is redundant when digitization seems to be too expensive and time-consuming. Stop following ridiculous myths about digital transformation - they are just chimeric creations of tabloids mostly.

Accept digitization as a useful toolkit capable of improving your workflows. Successful digital transformation does not depend on the size of a company since a different aspect is crucial in it. Strengthening effective interactions between a business and its customers is what provides both a premise and an outcome of properly arranged digitization. 

Have no idea where to start? That’s alright: the professional digital transformation agency is here to help. Contact us today to develop your individual digitization strategy: our experts are immune to myths and misconceptions and able to make your business adopt digital transformation with no stress.

People have a wonderful property that has led them onto the road of advancement more than once. They believe that everything can be beneficial. Even during such serious crises as the COVID-19 pandemic, humanity is looking for ways to make life easier and more robust.

The telemedicine vs telehealthcare comparison we are discussing here is one such example. Telemedicine was in use before COVID-19, though not as widespread as it is now. The pandemic has accelerated the development of remote communication methods that facilitate commuting with the patient while they stay at home.

McKinsey's study shows that 50-175 times more patients were using telecommunication technologies during the quarantine than before. More than 40% of surveyed patients displayed the desire to continue using remote medical services.

Remote Healthcare VS Telemedicine

The terms "telehealthcare" and "telemedicine" seemingly are synonymous. Nevertheless, these are different conceptions. Let us discuss in more detail what these mean and what is the difference.

Telehealthcare

Telehealth is a comprehensive concept that includes a vast number of services carried out using remote communication technologies. These may consist of prevention, diagnosis, and treatment of diseases, medical education for students and doctors, public health education, and more.

What elements does telehealth include?

Telehealthcare consists of several essential components, including the ability to conduct video consulting in real-time.

One of the most critical telehealth elements is remote monitoring of a patient's state (blood pressure, pulse, heart rhythm, temperature, etc.). This type of service allows the doctor to observe the health of a recently discharged or critical patient closely, make recommendations in the postoperative period, and reduces the risk of sudden deterioration.

Continuous collection and storage of data about the patient, performed treatments and administered medicines is another vital feature. Besides accumulating years of information, such storage can be made available across various clinics and healthcare establishments. The transfer of data takes place through secure electronic channels.

Next, we should mention mobile healthcare. It assumes providing patient support using smartphones or tablets and monitoring the parameters through sensors inherent to mobile gadgets. Mobile apps can deliver the latest news about your health, provide preventive advice, supervise the availability of medicines in nearest drug stores, remind you to take pills on time or consult with a doctor.

Distant care systems are essential for the elderly and patients with disabilities living at home. These are usually also outfitted by remote monitoring devices and sensors to help provide the necessary support to the patient and inform the doctor about any abnormalities.

Telemedicine

Telemedicine employs modern communication technologies to provide remote clinical treatment of patients with the help of on-site and distant medical personnel and diagnostic equipment.

What are the typical examples of telemedicine?

The most vivid example of telemedicine is when a patient turns to a doctor using video conferencing software for consultation, diagnosis, or advice on the treatment of a disease. Most such apps also allow sending photos of an injury, rash, medical test, or drug prescription.

Lately, news of successful surgeries where remote specialists control the medical robot or take charge of the surgical brigade started to appear.

Significant Difference between Two Concepts

At first glance, these two concepts are very similar. Let us review the difference between telehealth and telemedicine in more detail.

Telemedicine deals only with personal clinical treatment, diagnosis, and prevention with innovative communication means. Typically, family therapists use telemedicine to observe contractual patients.

In turn, telehealthcare covers a wide range of services, including telemedicine. These may also incorporate open studies, training of medical personnel, dissemination of research results, medicinal insurance, etc. Unlike telemedicine, services can be provided by all health professionals. Upon need, telehealth even allows holding an international online conference discussing some complex cases.

Perspective Innovations in Remote Healthcare

Without a doubt, the future of telehealth is auspicious. With the help of wideband telecommunications, it becomes possible to reduce the waiting time for an appointment with a doctor. Year by year, virtual medical services are becoming more affordable, qualitative, and responsive.

Betterment of medical education is a crucial part of telehealth. Government bodies and IT companies apply a lot of effort to its development. During the pandemic, medical students were attracted to remote patient inspections and VR training, which helped them learn and allowed them to acquire skills and experience safely.

Telemedicine is very suitable for people living in remote areas who find it challenging to reach populated areas with well-equipped hospitals. It is also an excellent solution for patients who are seriously ill and therefore cannot move freely.

The future of telemedicine technology lies in the introduction and combination of promising cutting-edge research to ensure unrestricted interaction between all the related parties and increase the quality and efficiency of medical treatments. In particular, VR, AR, AI, big data, blockchain, machine learning, gene therapy, personalized drugs, and other wonderful innovations are either being tested or introduced into telehealthcare already.

Medical software

The development of telemedicine and telehealth is linked inextricably with the modernization of equipment and software.

The use of telehealth software helps to solve many pressing problems, for example, such as:

• Access to a patient in an emergency, even if they are non-transportable;
• Remote monitoring of drugs' action to a person, both in clinical trials and in practice, and so on.

Telemedicine software products are used successfully in such specialties as radiology, treatment of chronic diseases, psychiatry, pediatrics, dermatology, etc.

Telemedicine software cost depends on various factors, among which hosting and/or hardware will have the most significant impact. The cheapest will be cloud hosting, where all apps and information are stored in the datacenter. The following considerable factors are the number of users of the application and the breadth of its functionality.

There is a lot of already released open source telehealth software, and new ones are released weekly. This leads to the development of the healthcare industry as a whole because such applications are usually free. At the same time, many contain quite a lot of valuable functions. Open source telemedicine software allows providing patients with secure remote support.

Final Thoughts

Telemedicine is steadily becoming an essential part of healthcare for the foreseeable future. In this, it is helped by an innovative way of developing digital technologies in telehealth. By combining information communication technology and medicine, telehealth confidently enters our lives.

Artificial intelligence, immersive reality, and devices that help record the patient's round-the-clock condition are aimed at ensuring that the patient receives highly qualified and timely medical care.