Machine Learning: Benefits to Business — Charter Global

Every industry and sector benefits differently from machine learning algorithms. The impact of machine learning depends largely on the type and amount of data that gets fed into each unique ML tool. Some sectors may also be more suited to ML than others: those that collect massive volumes of data are able to achieve greater accuracy in identifying patterns and predicting consumer behavior.

 

There are several key industries that we believe have the potential to be the biggest winners from predictive modeling.

 

Healthcare. The proliferation of wearable sensors and devices that monitor everything from pulse rates and steps walked to oxygen and sugar levels and even sleeping patterns have generated a significant volume of data that enables doctors to assess their patient's health in real-time. One new machine learning algorithm detects cancerous tumors on mammograms; another identifies skin cancer; a third can analyze retinal images to diagnose diabetic retinopathy.

 

Government. Systems that use machine learning enable government officials to use data to predict potential future scenarios and adapt to rapidly changing situations. Machine learning can help to improve cybersecurity and cyber intelligence, support counterterrorism efforts, optimize operational preparedness, logistics management, and predictive maintenance, and reduce failure rates.

 

Marketing and Sales. Machine learning is even revolutionizing the marketing sector as many companies have successfully implemented artificial intelligence (AI) and machine learning to increase and enhance customer satisfaction by over 10%. In fact, according to Forbes, “57% of enterprise executives believe that the most important growth benefit of AI and machine learning will be improving customer experiences and support.

 

E-commerce and social media sites use machine learning to analyze your buying and search history—and make recommendations on other items to purchase, based on your past habits. Many experts theorize that the future of retail will be driven by AI and machine learning as deep learning business applications become even more adept at capturing, analyzing, and using data to personalize individuals’ shopping experiences and develop customized targeted marketing campaigns.

 

Transportation. Efficiency and accuracy are key to profitability within this sector; so is the ability to predict and mitigate potential problems. Machine learning’s data analysis and modeling functions dovetail perfectly with businesses within the delivery, public transportation, and freight transport sectors. Machine learning uses algorithms to find factors that positively and negatively impact a supply chain’s success, making machine learning a critical component within supply chain management.

 

Within logistics, machine learning facilitates the ability of schedulers to optimize carrier selection, rating, routing, and QC processes, which saves money and improves efficiency. Machine learning’s ability to analyze thousands of data points simultaneously and apply algorithms more quickly than any human enables machine learning to solve problems that people haven’t yet identified.

 

Financial Services. The insights provided by machine learning in this industry allow investors to identify new opportunities or know when to trade. Data mining pinpoints high-risk clients and informs cyber surveillance to find and mitigate signs of fraud. Machine learning can help calibrate financial portfolios or assess risk for loans and insurance underwriting.

 

Manufacturing. Machine learning is no stranger to the vast manufacturing industry, either. Machine learning applications in manufacturing are about accomplishing the goal of improving operations from conceptualization to final delivery, significantly reducing error rates, improving predictive maintenance, and increasing inventory turn.

 

Not unlike the transportation industry, machine learning has helped companies improve logistical solutions that include assets, supply chain, and inventory management. Machine learning also plays a key role in enhancing overall equipment effectiveness (OEE) by measuring the availability, performance, and quality of assembly equipment.

 

Why Charter Global?

The Charter Global development team is highly experienced in creating customized machine learning solutions that locate and identify hidden patterns within your data to help you to gain vital insights into the behaviors of your customers. Rather than guessing at what really drives your business’s profits, you’ll know exactly what’s transpiring with real projects and identifying trends you never would have known about otherwise. Instead of creating a one-size-fits-all machine learning solution, you always know you’ll receive a custom algorithm to fit your business model perfectly.

 

Data can be easily overwhelming for any business but not when machine learning is introduced. Let Charter Global take the hard work out of analyzing your big data! Contact us today to talk about our machine learning development services and how it can expand your business in 2021.

 

What is Full-Stack Development?

 

What is Full Stack Development, Definition?

Full-stack development refers to the development of both front-end and back-end portions of an application. This web development process involves all three-layer- The presentation layer (front end part that deals with the user interface), Business Logic Layer (back end part that deals with data validation), and the Database Layer. It takes care of all the steps from the conception of an idea to the actual finished product.

Having a specialist work on each of the different subsystems of the web development process proves quite complex and expensive. Companies are demanding full-stack developers who are proficient in working across multiple stacks.

Read More: What to Choose between Native or Hybrid Development

What is a full-stack developer?

A Full-Stack Web Developer is a web developer or engineer who works on both the front-end and back-end of a website or application — meaning they can tackle projects that involve databases, building user-facing websites, or even work with clients during the planning phase of projects. Being a Full-Stack Developer doesn’t mean that you have necessarily mastered everything required to work with the front-end or back-end, but it means that you are able to work on both sides and understand what is going on when building an application.

In fact, “full-stack” refers to the collection of a series of technologies needed to complete a project. “Stack” refers to a collection of sub-modules. These software sub-modules or components combined together to achieve the established function while without the need for other modules.

Technology related to full-stack development:

There are some essential technologies that you must learn in order to call yourself a full-stack developer. Here is a quick guide to what technologies you must learn.

HTML and CSS-

To begin your career in web development you must have the fundamental knowledge of HTML and CSS. They are the basic building blocks of the web that enable you to add content and styles to your web pages. So start your journey of becoming a full-stack developer by gaining a sound understanding of these front-end concepts.

JavaScript-

The fact that JavaScript can be used both in front-end and back-end development makes it very popular. It is one of the hottest technologies in the market where continuous innovations take place. With new tools and frameworks getting released every year, one needs a piece of sound knowledge in this area. Knowledge of JS frameworks like AngularJS and ReactJS would help one to write long codes with ease. A solid understanding of jQuery would be an added advantage.

Backend Programming Languages–

After gaining a strong foothold in the front-end arena next comes backend languages like Ruby, Python, PHP, etc. which handle application logic, user authentication, and data operations. Start with a language that is easier to learn. Whatever language you choose, just make sure you are thorough with its nuances. You may learn Node.JS which is based on JavaScript that you would have already learned before reaching this point.

Database & Web Storage-

In order to design and develop dynamic websites, one should surely know how database-driven websites store and access data. Learn the benefits of relational database management systems like SQL. Understand how to connect a backend language with a database. Gain knowledge about web storage so that you know how to store cookies, sessions, and cached data in the browser.

HTTP and REST-

You must gain insights into HTTP- that is the protocol required to facilitate communication between the client and server. You must also know how REST is important to the HTTP protocol and web applications. Knowledge of Chrome DevOps Tools and SSL certificates would be advantageous.

Read more: The Fundamentals of Front End and Back End Development

Additional skills set to adopt as full-stack developers are as follows.

Application Architecture-

Developing complex applications would require a deep knowledge of how the code should be structured, how the data needs to be structured in the database, how to separate files, where to perform computational tasks, and where to host large media files. So a full stack web developer surely needs a deep knowledge of web application architecture.

Version control system-

A full-stack web developer needs to be well versed with a version control system. An understanding of GIT will help you keep track of any changes that you make to the code base.

Acquiring expertise in so many technologies and becoming an expert in all the layers of web development may seem like a daunting task in the beginning. It’ll be hard work learning all of this, but it’s rewarding in the end and Full-Stack Development is fun!

https://www.charterglobal.com/understanding-full-stack-development/

Using IoT to Enhance Your Mobile App – Increase Online Customer Subscription

A healthcare startup was looking for an application development company to enhance their smartphones and a wearable (sensors) application that enables the patient’s family to connect with their loved ones while in hospital, skilled nursing, or memory care facility. The client’s goal was to make the connected world a simpler and more affordable place to live in using the Internet of Things and mobile technology.

 

First, this was accomplished by uploading and displaying personalized videos from family and friends to enhance personal connections and reduce the feelings of isolation and loneliness. Secondly, by using wearable technologies (medical sensors of vitals) to predict and warn users when their medical parameters (Heart rate, SPO2, Stress) are going below or above an established threshold. This essential system also warns the medical staff and family automatically. Periodically, status can be monitored through smartphones.  The application provides feedback regarding how many times the videos are watched by the patient and it is a platform for status updates from healthcare staff via text messages.

 

Challenge:

 

They needed a feature-rich application that could handle thousands of videos being uploaded and shared over the internet. Additionally, it was required to run in a cloud environment and to be developed within six weeks. The current application had the following challenges:

 

1. Feature enhancements took more time to implement due to inconsistent development standards.
2. Frequent (OS) operating system device crashes occurred because of outdated application libraries.
3. Application performance was slow due to existing code quality.
4. The server-side architecture needed to be enhanced.
5. TV functionality needed upgrading to support patient privacy policies.

 

Solution: 

 

The Charter Global team upgraded the client’s application libraries to the latest versions and migrated all of their android and iOS code to support the Android X components. Refactored the TV application codebase to support the updated privacy policy terms. Charter Global’s team identified the root causes for the system crashes and low performance. They designed and implemented solutions that improved the code quality and the performance of the entire application by 100%.

 

Results:

 

As a result of these enhancements, the client was able to increase its subscription base by 50% within six months of deployment to the production environment.

 

Are you thinking about creating a mobile application? If so, Schedule an appointment today with our full-service mobile app developing team.

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Machine Learning (ML) vs. Artificial Intelligence (AI) — Crucial Differences

Artificial intelligence and Machine Learning are the part of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems.

Although these are two related technologies and sometimes people use them as a synonym for each other, but still both are two different terms in various cases.

On a broad level, we can differentiate both AI and ML as:

Artificial Intelligence vs. Machine Learning: Required Skills

Because artificial intelligence is a catchall term for smart technologies, the necessary skill set is more theoretical than technical. Machine learning professionals, on the other hand, must have a high level of technical expertise.

Artificial Intelligence Skills

People pursuing a career in artificial intelligence must have a foundation in:

1. Algorithms, and techniques for analyzing them
2. Machine learning and how to apply techniques to draw inferences from data
3. The ethical concerns in developing responsible AI technologies
4. Data science
5. Robotics
6. Java programming
7. Programming design
8. Data mining
9. Problem-solving

Machine Learning Skills

People pursuing a career in machine learning must have a foundation in:

1. Applied mathematics
2. Neural network architectures
3. Physics
4. Data modeling and evaluation
5. Natural language processing
6. Programming languages
7. Probability and statistics
8. Algorithms

The Future is now with AI and ML 

So, by now, you’ve learned the basic differentiating factors between ML and AI. Machine learning uses past experiences to look for learned patterns, while Artificial Intelligence uses the experiences to acquire knowledge and skills, then applies that knowledge to new scenarios.

It’s clear that both AI and machine learning have valuable business applications, empowering companies to respond quickly and accurately to changes in customer behavior and solve critical business problems.

As the adoption of AI and ML become more commonplace, namely predictive analytics and data science will see a massive uptake in virtually all industries across the marketplace.

Reference Link:

https://www.charterglobal.com/machine-learning-vs-artificial-intelligence-whats-the-difference/

https://www.charterglobal.com/ai-machine-learning/

How automation reduced the customer processing time by 300 percent.

A public transportation company was looking for a strategic partner to automate their manual workflow process. They needed a feature-rich application to replace the current process to provide data insights to their customer’s eligibility.

 

Challenge:

 

Their entire process — from applications being submitted to assessing the eligibility of the rider was paper-based. This manual submission process led to significant delays in determining their customer’s eligibility. It was determined to be inefficient and costly in man-hours, as it required a lot of effort to remember various workflows for each rider and process accordingly. This manual process was also prone to basic human error.

 

Solution:

 

Charter Global developed the Single Page Application solution using the client-recommended technologies. The User Interface was built using the Vue framework and APIs were developed using the Express web application framework adhering to the microservice architecture. The new features consisted of the following:

 

1. Enabled the user to generate dynamic forms in real-time.
2. Allowed setting up meetings with customers.
3. Technology stack needed to be consistent with existing systems.
4. The solution needed to be easy to maintain.

 

Results:

 

The new online application eliminated all existing paper documents simplifying their entire workflow management process. It allowed their customers to submit applications online creating a self-service model. In addition, their management team was able to create reports in one click. As a result of the new application, the client was able to reduce the customer eligibility time by 300 percent.

 

Implementing a new microservice architecture and automation proved to be highly effective and saved valuable resources for our transportation client. During the pandemic, this digitalized solution helped our client users to continue operations without any manual interactions.

 

How can we help your business succeed and thrive!

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We increased our client’s online customer subscription by enhancing their mobile application

A healthcare startup was looking for an application development company to enhance their smartphone application that enables patients to connect to their loved ones while in a hospital or nursing home using personalized videos.

 

Challenge:

 

They needed a feature-rich application that could handle thousands of videos being uploaded and shared over the internet. Additionally, it was required to run in a cloud environment and to be developed within six weeks.  The current application had the following challenges:

 

1. Feature enhancements took more time to implement due to inconsistent development standards
2. Frequent (OS) operating system device crashes occurred due to outdated application libraries
3. Application performance was slow due to code quality
4. The server-side architecture needed to be enhanced
5. TV functionality needed upgrading to support current privacy policies

 

Solution: 

 

The Charter Global team upgraded their application libraries to the latest versions and migrated all of their android and IOS code to support the Android X components. They identified the cause for their system crashes while improving code quality.  Refactored the TV application codebase to support the updated privacy policy terms, identified the causes for low performance, and improved all the application’s performance by 100%.

 

Results:

 

As a result of these enhancements, the client was able to increase its subscription base by 50% within six months of the code being in production.

 

Are you thinking about creating a mobile application? If so, Schedule an appointment today with our full-service mobile app developing team.

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How Charter Global developed a .Net Cloud Solution by Automating the Client’s Manual Process.

A Fortune 500 company was looking for an application development company to reverse engineer their manual processes and design an internal system to improve how they managed their customer infrastructure support requests.

 

Challenge:

 

Their current process was managed with excel spreadsheets. It lacked integration with the various key departments within their internal systems to accurately execute a proper infrastructure request. They needed a feature-rich application to replace the current process to provide data insights to their customers, back-office support, and management. Additionally, it was required to run in a cloud environment and to be developed within four months.

 

Solution: 

 

We recommended .NET as the application development platform to allow for improved code management, ability to run on cross platforms (Windows, Linux, and OS X, etc.), flexibility to deploy, and easy maintenance. The Charter Global team reverse-engineered their manual process, while simultaneously collaborating with their Product management team to gather the requirements. The new application provided an easy-to-use Cloud Ordering experience. Its features include view available service catalog items, ability to add/update/delete required items to their Project infrastructure estimates, view capability via the shopping cart, support bill of Materials, and submit/checkout project estimates. The Backend functionality provided important validations of their Data Center capabilities to serve project estimates; ability to submit estimates to the backend Deployment team for build/deployment of infrastructure requests provided key integrations with ServiceNow and Data Management operations Audit trails.

 

Results:

 

The new Cloud-based application reduced the turnaround time of the order capture process to build/fulfillment of all infrastructure requests. The solution also provided useful reports on how the Data Centers were utilized as well as capacity metrics helping the management team with important business organizational decisions. The Backend Data Management tools provided the ability to manage Service Catalog items, pricing, and availability of catalog items more efficiently compared to the previous manual process.

 

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