Reasons to Create a Mobile App Development for Your Business | Charter Global

In a world where people are spending considerably more time on their mobile phones than on their computers, it is no longer enough as a business to only have online presence. Mobile business applications have become a necessary marketing tool for all businesses, regardless of size or industry. While many business owners may think developing an app is too expensive or an unnecessary investment, a mobile app can help a small business engage with and build their customer base, drive sales, and improve their reputation in the market.

Reasons why you should opt for mobile app development

1. Increased customer engagement.

A staggering 83% of all smartphone users begin their day by looking at their smartphones and using apps. According to CNN, the average American accumulates 10 hours of screen time daily. This is something businesses should take advantage of to ensure they reach as much customers as possible. The level of engagement mobile app types receive is several times higher than that of normal websites. With a well designed and user-friendly mobile app, visibility to a wider range of customers and prospective is guaranteed.

2. Brand Awareness and Recognition

One easy way to put your brand out there in the market is through mobile app development. Owning an app puts the business in the face of consumers as a solid vendor they can rely on as they make their buying decisions from the few or many choices available. Users easily associate a brand with its app and the experience they get as they use the app never leaves them, hence the importance of creating a great app. A Full-Service Mobile App Development will keep reminding users about the brand. Even when they’re offline or using other apps, they will regularly view the app icon in their app list. This would always keep the vendor at the forefront of customers’ minds.

3.To take advantage of location-based tracking

Location tracking is very important in mobile app development, as it opens the door to new ways of targeting customers for different marketing campaigns and driving increased action from them. Some of the most successful shopping apps use location-based notifications to alert users about the latest discounts and deals available at their nearby stores.

4. Increase product value

Mobile apps can help in the delivery of products and services in a much more effective and timely manner. Highlight and promote the most valuable aspects of products or services through the app and increase their effectiveness with tailored options and features.

5. Faster and Seamless experience

Apple and Google have minimum speed requirements to list mobile apps. This ensures a quicker and smoother experience for users resulting in more action and higher engagement levels. Frequent and thoughtful testing is the key to maintain a best-in-class experience that attracts and converts users.

6. New revenue streams

There are several other ways of making money using an app outside of the core reasons. Using in-app advertisement and sponsorship methods, apps can generate money through third party. Apps can also be monetized by introducing in-app purchases. It is however important to not sacrifice the customer’s convenience or the core purpose of the app on the altar of side earnings.

7. Increase brand image

A mobile app makes any business, big or small stand out, and gives the business an impression of being tech-savvy. Mobile Application Development Services also make the details (location, contact, etc.) about your business more easily available, which is obviously very good for the company.

8. Makes it easier to promote products

Companies with mobile apps make better impressions than those without one. A mobile application will make a business stand out. Frequent updates help develop customer interest in the company’s products. It will also help save money and effort in other types of promotional techniques, such as advertisements in newspapers and billboards.

9. Increased and faster sales

Mobile application is a tool for increased sales as it attracts and retains customers. All a business needs to do to meet up sales deadlines using applications is to create push notifications about promotions, bonuses and discounts to motivate customers to make a purchase. This can be sent to as many customers across certain geographical locations, times and periods. A “limited time” promotional coupons can be sent via mobile business app to customers. Such promotions encourage sales and will also provide publicity to the business.

10. Analytics made easy

Every efficient marketing campaign requires good analytics. The mobile app technology has immensely helped in the sourcing of information regarding customer preferences, how they use money and time and other important facts that would help place the business in a position to increase production and sales. A mobile app will help business owners track downloads, user engagement, and the products that users show interest in. It’ll also help determine how to make products more customers oriented.

Get in touch with our team to discuss IT staffing and software development solutions that can supersede your existing solutions on mobile and web applications.

How to Use Universal Resource Scheduling With Dynamics Field Service | Charter Global

Universal Resource Scheduling (URS) is a Dynamics 365 for Customer Engagement solution. In essence, it enables organizations from many different industries with different scenarios to assign resources to jobs and tasks.  

URS can be used to assign the best resources to tasks and projects based on:

• Availability of resources 
• Required skills
• Promised time-frames
• Business units
• Geographical territory, etc 

Universal Resource Scheduling (URS) are very useful to field service organizations that often use it to schedule mobile resources to location-specific jobs and tasks (or work orders) as their resources travel to various locations. Next, URS schedules the resources with closest proximity to work orders, as work orders are generally performed onsite. So, this eventually reduces travel time and costs.

URS schedulers are very effective for finding and assigning the most relevant resources for a job or requirement. From simple maintenance, repair work, installations to anything else, URS finds the best people for the job with ease and speed.

Creating Work Orders

One of the most important components of field service are the work orders.  This helps define the kind of work that needs to be performed. With URS, it is possible to find the best hands to perform tasks at a given time.

Below are the major components of Field Service and URS:

1. Bookable resources (URS)
2. Resource requirements (URS) 
3. Work orders (Field Service) 
4. Resource bookings (URS)
5. Schedule tools – schedule board, schedule assistant (URS) 
6. Resource Scheduling Optimization (installed separately) (URS) 

For More Information, Please visit our website:

https://www.charterglobal.com/universal-resource-scheduling-urs/ 

URS Uses

There are several ways to use URS for scheduling. One is by using work orders and requirements, and then clicking on the book button on the top ribbon. This kick starts the URS assistant, which shows the available resources for the work. The resources listed are based on their characteristics for the specific work and their availability.

Other ways to book a work order is through the schedule board which gives a drag and drop option. Now, here you can even reschedule or reassign a work order if needed.

In addition, the resource scheduling optimization is a fully automated way to book appropriate resources. It runs on predefined criteria and can be activated with the run now button on the ribbon (but it needs to be installed and configured first to be used).  

Charter Global

In conclusion, good resource management involves an understanding of how much effort a task requires and assigning the right person for the job. So, the Charter Global team also offers a resource management solution that empowers global project teams to make the best out of project scheduling optimization, workload balance, and a general increase in productivity.

Reference –

https://charterglobal.com/enterprise-solutions/microsoft-solutions/ 

https://charterglobal.com/enterprise-solutions/microsoft-dynamics-365/

https://docs.microsoft.com/en-us/dynamics365/customer-engagement/field-service/schedule-work-order

Get in touch with our team to discuss IT staffing and software development solutions that can supersede your existing solutions on mobile and web applications.

Accelerate Your Application Delivery with QA Automated Testing - Charter Global

2019 will be remembered as an important year for software testing services – with a record 97% of Agile adoption according to Forrester. Upon entering 2020, it’s time to identify several new software testing trends in hopes of achieving new, strategic heights.

As advancements in testing approaches and techniques continue to surge, QA Automation Testing Services teams strive to improve their skill sets. This is crucial in maintaining synchronicity with rapid technological advances that effectively make of break software delivery strategy.

What trends have shown promise in 2019?

Creating a unique, refined, and savory customer experience has taken center stage in 2019 software delivery trends. Growing organizations rely on high-quality software to systematically produce succinct deliverable.

Moving forward, development teams must consider the following trends to maintain a competitive advantage in a fiercely expanding market.

AI Finds its Footing in Business and QA

The rise of automation and Artificial intelligence was predicted in last year’s trends. Nevertheless, it has been included this year as companies will analyze how artificial intelligence applies to their business. According to The World Quality report, 55% of respondents said that this was their main problem with setting up AI projects.

With regards to QA, more companies are expected to adopt machine learning techniques in areas such as predictive analytics (predicting future outcomes of the testing process based on historical data), defect analytics (highlighting at-risk areas of an application) and test suite optimization (identifying redundant test cases).

The use of AI in testing might require newer skills which will eventually lead to organizations creating new roles for AI QA strategists, data scientists, as well as AI test experts in QA and testing teams.

Instant Apps Take the Spotlight

Instant apps are native mobile apps that are smaller in size. Thus, more convenient for the user who is no longer required to download a standalone app.

The demand for better user experiences and shorter load times are constantly increasing.

Google’s introduction of Android App Bundles allows developers to modularize their apps and deliver features on demand; this will make more organizations adopt the Instant Apps approach.

QA Decentralization

The QA and testing department has been fragmented as a result of the transition to agile and DevOps. QA is now embedded into cross-functional teams. So, quality is dependent on the team members’ skills and their responsibility to integrate testing into their product life-cycle.

Continuous Improvement

The trends mentioned above have contributed to the rise in the adoption of Agile & DevOps over the past few years. Testing is an early part of the development process. More companies will adopt more agile/DevOps models to help them release faster and receive quick feedback. Other companies will take it a step further by adopting approaches such as continuous testing and continuous monitoring.

An attitude of “continuous improvement” will enhance the overall performance and quality of products by teams.

Quality Engineering over Quality Assurance  

QA professionals will enhance their technical skills and include some automation-related work organized by quality engineers. The role of Quality Assurance will deviate to implementing the latest technologies to boost the speed of quality checks. This is a trend that will come into play in the coming years.

Big Data Testing

With big data testing, testers have to verify that terabytes of data are successfully processed. Additionally, the aggressive increase in quantity is making it more tasking for companies. More likely, QA will have to deal with validating the quality, accuracy, and consistency of huge datasets.

These trends above demonstrate the crucial transformation both companies and QA Automation Testing Services is undergoing. The expectations of consumers will continue to shoot up. Organizations must adapt and deliver if they must remain in the front line and grow beyond 2019.

If you are interested in learning more about Benefits of QA Automated Testing Services, check out other blogs here.

Get in touch with our team to discuss IT staffing and software development solutions that can supersede your existing solutions on mobile and web applications.

Machine Learning: A Valuable Enterprise

Benefits like cost savings and efficiency make ML an MVP 

 

These benefits are especially prominent when coupled with the IoT and industrial markets

 

Machine Learning is a valuable player in the realm of the Internet of Things. ML and Internet of Things (IoT) have gained tremendous popularity over the past few years, considered by many as revolutionary, game changing tech. Yet, much confusion exists in terms of understanding the purpose of Machine Learning, along with it’s benefits and suitability for use. 

 

Here’s a breakdown of Machine Learning, benefits of ML in AI and IoT, when it should be used, and it’s real-world applications today.
 

Data Analytics vs. Machine Learning

 

With all the aforementioned hype around machine learning, many organizations are asking if applying machine learning could benefit their business model. In the vast majority of cases, the answer is a resounding no. In the case of big data, however, Ml may prove very useful.

 

Machine learning takes large amounts of collected data and generates useful, real-time insights that help the organization based on it’s inherent learning capabilities. That could mean improving vast amounts of processes, cutting costs, creating a better experience for the customer, or opening up new business models.

 

The thing is, most organizations can get many of these benefits from traditional data analytics, without the need for more complicated machine learning applications.

 

Traditional data analysis are great at explaining data. You can generate reports or models of what happened in the past or of what’s happening today, drawing useful, insightful conclusions about your organization.

 

Data analytics can help quantify and track goals, enable smarter decision making, and then provide the means for measuring success over time.

 

When Is Machine Learning Valuable?

 

In general, machine learning is valuable when you know what you want but you don’t know the important input variables to make that decision. So you give the machine learning algorithm your stated goals, or inputs. Based on learning systems, and then it “learns” from the data which factors are important in achieving that goal.

 

The data models that are typical of traditional data analytics are often static and of limited use in addressing unstructured, fast-changing, sequestered amounts of data. When it comes to IoT, it’s often necessary to identify correlations between dozens of sensor inputs and external factors that are rapidly producing millions of data points.

 

In addition, ML  has the ability to accurately predicting future events. Whereas the data models built using traditional data analytics are static, machine learning algorithms constantly improve over time as more data is captured and assimilated. This means that the machine learning algorithm can make predictions, see what actually happens, compare against its predictions, then adjust to become more accurate.

 

The predictive analytics made possible by machine learning are hugely valuable for many IoT applications. Let’s take a look at a few concrete examples.

 

How are Machine Learning Applications used in IoT?

 

Cost Savings in Industrial Applications:

 

Predictive capabilities are extremely useful in an industrial setting. By drawing data from multiple IoT sensors in or on machines, machine learning algorithms can “learn” what’s typical for the machine and then detect when something abnormal begins to occur.

 

Predicting when a machine needs maintenance via IoT data is incredibly valuable, translating into millions of dollars in saved costs. A great example is Goldcorp, a mining company that uses immense vehicles to haul away materials.

 

When these hauling vehicles break down, it costs Goldcorp $2 million per day in lost productivity. Goldcorp is now using machine learning to predict with over 90% accuracy when machines will need maintenance, meaning huge cost savings.
 

Shaping Experiences to Individuals:

 

We’re actually all familiar with machine learning applications in our everyday lives. Both Amazon and Netflix use machine learning to learn our preferences and provide a better experience for the user. That could mean suggesting products that you might like or providing relevant recommendations for movies and TV shows.

 

Similarly, in IoT machine learning can be extremely valuable in shaping our environment to our personal preferences.

 

The billions of sensors and devices that will continue to power connected devices, smart homes, and IoT devices in the coming years will generate exponentially more data. This huge increase in data will drive great improvements in machine learning, opening countless opportunities for us to reap the benefits.

 

Not only we will be able to predict when machines need maintenance, we’ll be able to predict when we need maintenance too. Machine learning will be applied to the data from our wearables to learn our baseline and determine when our vitals have become abnormal, calling a doctor or ambulance automatically if necessary.

 

Beyond individuals, we’ll be able to use that health data at scale to see trends across entire populations, predicting outbreaks of disease and proactively addressing health problems.

 

Although both machine learning and IoT can be over-hyped, the future of machine learning applications in IoT are worthy of that hype. We’re really just scratching the surface of what’s possible.

 

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4 Tips to make Mobile Recruiting an Essential Part of Your Hiring Strategy - Charter Global

Using mobile technology, an HR unit can engage mobile recruiting to attract, engage as well as convert candidates. Typical examples of mobile recruiting methods include mobile recruiting apps, mobile career sites, social recruiting, and recruiting by text.

IT Staffing Solutions offers an evolving opportunity for employers to connect with candidates in a more efficient manner. A research study showed that more than 89 percent of job candidates confirmed that their mobile devices are going to be an essential tool as well as resource for job search.

No doubts, the use of traditional methods such as phone calls and emails have helped in time past in employment processes. However, the rise in mobile usage among people searching for job has made mobile recruiting a more viable tool for recruitment in 2020 and beyond.

What Research Results are Saying about Mobile Recruiting?

Tip #1: Don’t Ignore Mobile or You will be Ignoring the Best Candidates

If you ignore mobile in your recruitment process, you may end up ignoring the top candidates for those positions you wish to fill. So, why is it quite important to feature your IT requirements analysis on handy devices such as smartphones and tablets? The answer is simple…

“By not integrating mobile strategy in recruitment, companies are giving up skillful and qualified candidates. This is because a good number of highly-talented people are changing the way they search for job, both the entry-level candidates and the senior executives”, says a recruitment expert. And, it’s a pity that a lot of companies are hesitating to swing into mobile recruiting.

Tip #2: Imbibe a Strategic Mobile Hiring Strategy

Wondering where to start when it comes to mobile hiring strategy? For now, don’t focus much on smartphone apps. The first step is to focus on making your company’s career website mobile-friendly. Be the judge of whether or not your career site would enable mobile users to apply for your positions by browsing the site on a mobile device – iPhone, Android phone or tablets. This will help you determine how best to repackage your site to suit the present day job seekers.

Tip #3: Take a Cue from Your Rivals

Another great way to do mobile recruiting is to take a cue on how your competitors are doing it. There’s no need reinventing the wheel — be smart and do less work by taking a cue from your rivals who are already taking advantage of mobile for recruiting. Take a long and insightful look at a well-structured mobile career site.

For More Information, Please visit our website: 

https://charterglobal.com/people-solutions/

Tip #4: Find out and Implement Mobile Users’ Needs 

You should also research on the needs of mobile users. The message is simple; learn about your target audience. Locate a group of persons/candidates critical to your recruiting. Subsequently, you should sit back and find out their needs in terms of what your company has to offer better than the other rival company.

Finally, get to the essentials of mobile recruiting by developing robust mobile devices’ landing pages.

Read More: https://www.charterglobal.com/mobile-recruiting/

Get in touch with our team to discuss IT staffing and software development solutions that can supersede your existing solutions on mobile and web applications.

7 IoT Trends on the Rise

Look Out for These 7 Trends in the Internet of Things (IoT)

 

Trends include the rise of cloud computing, big data convergence, artificial intelligence, smart cities, and more

 

By Leila Kojouri

 

The internet has become a beastly enterprise, with the past ten years seeing more technological advancements than perhaps any other industry. The Internet of Things, or IoT,  for example, is one such advancement gaining immense traction in the marketplace. Here are 7 IoT trends to look out for this year.

 

1. Big Data Convergence:

IoT is changing the way we live and conduct business exponentially, generating a huge amount of data in the process. Big data platforms, for example, are usually made for supporting the demands of large-scale storage and for performing investigative work.

 

Interestingly, IoT and big data have a lot in common. Smart devices, for example, are now being designed specifically for the purpose of digesting massive amounts of system and user generated data. The cloud has proven instrumental in meeting analytic and storage requirements in the realm of big data. Moving forward, the junction between IoT and big data will definitely be a trend on the rise.

 

2. Data Processing with Edge Computing:

Albeit a powerful force, weaker elements in IoT are evident in the addition of devices behind the firewall of the network. While Securing the devices may be easy, securing the IoT itself proves a trickier phenomenon. Thus, security measures must exist between the network connection and the software applications linking to the devices.

 

Perhaps the most notable benefits of IoT are it’s cost-effectiveness and efficiency, especially in data processing. Rapid-fire data processing is prominent in most smart devices, re: self-driving vehicles and intelligent traffic-lights (aptly coined, “smart lights”). Edge computing has been proposed as a potential solution, gaining immense popularity.

 

Edge computing usually outperforms the cloud when it comes to speed and cost. Faster processing translates to lower latency, which is one of the premium benefits of edge computing. Data processing with edge computing will see an uptake in IoT trends in the near future, for certain. 

 

3. Auto-ML (Machine Learning) for Data Security:

In present days, developers are tasked with finding newer methods in which people can share data securely by the use of block-chain-like technologies. Many industrial companies are learning how to trust and accept the forecast of machine learning models (otherwise known as “predictive analytics”), and will acclimatize their operations for preventing the downtime by model outputs.

 

Machine learning model training will likely become a highly automated process. Industrial companies in particular will increase the large capital assets, particularly in cloud computing, in the near future. 

 

4. IoT – Massive Growth Coming:

When it comes to data analytics, IoT is perhaps the most promising technology to date.  Smart devices ingest more data and information about the devices and users, and by 2020, it is expected that IoT devices will exceed 31 billion. Today, we see IoT devices as the major part for reporting and tracking.

 

 IoT is capable of the extraction, storge, and analysis of massive data stores. When coupled with other ground-breaking technologies, like Artificial Intelligence (AI), for example, the essential data can be appropriately measured, filtered and categorized.  IoT trends will most definitely see an increase in the amount of “work” smart devices are doing. What’s more, they will serve to assist data scientists and technicians in providing powerful, insightful suggestions.

 

5. Better Data Analytics:

Chances are, you’ve heard some of the hype and clamor surrounding artificial intelligence in modern business practices. The merger of IoT and AI has seen many recent developments, as the two can be used interdependently to provide e a centralized decision-making tool for all types and sizes of businesses.

 

AI and machine learning are systems that can easily identify trends, patterns, and unique behaviors otherwise invisible to the naked human eye. Better data analytics and the need to safeguard this said data are two major reasons for the rise of this trend. By collecting insights from this data, we could even suggest it be rendered to help us make better decisions in our personal lives. The sheer intelligence, thoughtfulness and self-learning capabilities make this a hugely popular trend to look out for in the near future.

 

6. Smart Cities to Become Mainstream:

When it comes to data collection, many states have adopted a more technological approach – replacing or improving upon antiquated infrastructure; integrating sensors to reap data that proves invaluable for the purpose of urban planning and development. Prepare yourself for the integration of IoT into just about every sidewalk, crosswalk, highway, and byway, as data collection becomes less of a convenience and more of an evolutionary imperative for American progress.

 

Cities both nationwide and globally will become pioneers for the great data exchanges affording accessibility and empowering evidence for better decision-making. Ultimately, the digestion and dissemination of this unique, all-telling data will provide a fundamental platform for both private and public organizations, and the citizens under their watch.

 

IoT integration for the sake of developing “responsive cities” can accomplish goals such as lessening traffic congestion, unlocking sustainable development and improving safety precautions. 

 

7. Personalization of the Retail Experience:

With IoT, the efficiency of supply chain and information systems management has grown by leaps and bounds with respect to retail. Sensors and other smart beacon technologies are being used to tailor shopping experiences with ease, speed, and accuracy like never before. 

 

In the not-so-distant future,  IoT can be used to monitor, gauge, track, and personalize your investment portfolio – making unique, custom trade recommendations based on your data insights.  Or, imagine getting notified immediately when a highly-sought after product from your favorite shop is discounted via push notification which when expanded, offers an indoor map of your favorite shop – leading you to the exact product you desire. 

 

The value of this trend ensures the better integration of personalized retail experiences which ultimately can bring upon a new era of shopping as we know it. 

 

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Giving the Green Light with QA Automation Testing

Improve customer experience, business processes, and enhance technical skills with QA Automation

 

2019 will be remembered as an important year for software testing – with a record 97% of Agile adoption according to Forrester. Upon entering 2020, it’s time to identify several new software testing trends in hopes of achieving new, strategic heights.

 

As advancements in testing approaches and techniques continue to surge, QA teams strive to improve their skill sets. This is crucial in maintaining synchronicity with rapid technological advances that effectively make of break software delivery strategy.

 

What trends have shown promise in 2019?

Creating a unique, refined, and savory customer experience has taken center stage in 2019 software delivery trends. Growing organizations rely on high-quality software to systematically produce succinct deliverables.

 

Moving forward, development teams must consider the following trends to maintain a competitive advantage in a fiercely expanding market.

 

Crafting a Quality Customer Experience

Remember testing was merely about bug finding, reporting, and fixing? We’ve come a long way. Now, testing trends are aligned with a central theme: customer satisfaction.  

 

As it stands, customer experience is the key differentiator for consumers when it comes to product choices. Customers expect more from their suppliers than ever. The advancement in technical areas like performance and DevOps are fundamental in creating a great end-user experience.

 

Performance engineering seeks to create a phenomenal,  one-of-a-kind customer experience. This is done by observing how the entire system, including hardware, software, configuration, etc. communicate and collaborate together to generate business value.

 

AI Finds its Footing in Business and QA

The rise of automation and Artificial intelligence was predicted in last year’s trends. Nevertheless, it has been included this year as companies will analyze how artificial intelligence applies to their business. According to The World Quality report, 55% of respondents said that this was their main problem with setting up AI projects.

 

With regards to QA, more companies are expected to adopt machine learning techniques in areas such as predictive analytics (predicting future outcomes of the testing process based on historical data), defect analytics (highlighting at-risk areas of an application) and test suite optimization (identifying redundant test cases).

 

The use of AI in testing might require newer skills which will eventually lead to organizations creating new roles for AI QA strategists, data scientists, as well as AI test experts in QA and testing teams.

 

Instant Apps Take the Spotlight

Instant apps are native mobile apps that are smaller in size. Thus, more convenient for the user who is no longer required to download a standalone app.

 

The demand for better user experiences and shorter load times are constantly increasing.

 

Google’s introduction of Android App Bundles allows developers to modularize their apps and deliver features on demand; this will make more organizations adopt the Instant Apps approach.

 

QA Decentralization

The QA and testing department has been fragmented as a result of the transition to agile and DevOps. QA is now embedded into cross-functional teams. So, quality is dependent on the team members’ skills and their responsibility to integrate testing into their product lifecycle.

 

Continuous Improvement

The trends mentioned above have contributed to the rise in the adoption of Agile & DevOps over the past few years. Testing is an early part of the development process. More companies will adopt more agile/DevOps models to help them release faster and receive quick feedback. Other companies will take it a step further by adopting approaches such as continuous testing and continuous monitoring.

 

An attitude of “continuous improvement” will enhance the overall performance and quality of products by teams.

 

Quality Engineering over Quality Assurance

QA professionals will enhance their technical skills and include some automation-related work organized by quality engineers. The role of Quality Assurance will deviate to implementing the latest technologies to boost the speed of quality checks. This is a trend that will come into play in the coming years.

 

Big Data Testing

With big data testing, testers have to verify that terabytes of data are successfully processed. Additionally, the aggressive increase in quantity is making it more tasking for companies. More likely, QA will have to deal with validating the quality, accuracy, and consistency of huge datasets.

 

These trends above demonstrate the crucial transformation both companies and QA is undergoing. The expectations of consumers will continue to shoot up. Organizations must adapt and deliver if they must remain in the front line and grow beyond 2019.

 

The post Giving the Green Light with QA Automation Testing appeared first on Software Development & IT Staffing Company.

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