Category: Business

What 2020 holds in store for software testing automation 

Enterprises are constantly on the hunt for trends that improve their application’s effectiveness, expedite development cycles, reduce downtimes, and improve cost savings. In such cases, they often resort to methods that can automate mundane testing procedures. Why is it the right time to leverage test automation trends? Here we discuss a few software testing automation trends expected to dominate in 2020. 

The automation testing lifecycle

Automation testing provides testing teams the ability to improve the coverage of their software tests and additionally offers improved quality, cost savings, shorter testing cycles, and a multitude of other benefits. To reap benefits out of automation techniques, the key is to incorporate the right skills, planning, as well as the right testing tools.

Let us walk through the various phases involved in an automation lifecycle:

1. When and what and how to automate?
2. Selecting the right tool
3. Test planning, designing, and strategy selection
4. Establishing the testing environment
5. Development and execution of the automation test script
6. Analytics
7. Report Generation

Related Reading: Understanding The Different Types Of Software Testing

Factors that drive the adoption of test automation in 2020

• Ability to strategize and plan.
• Finding resources and skills to make use of automation tools and frameworks.
• Ability to assess related risks.
• Exploration of tools.
• Providing instant feedback so that developers can gain insights into various areas that require improvement.
• Conducting multiple tests throughout various phases.
• Increasing efficiency to reduce risks.
• Reducing defect fixing time and effort.
• Investing more time for the development and enhancement of features.
• Analyzing strategies to capture data to assess various releases.
• Ensure API testing to determine the functionality, performance, security, as well as reliability of the application tested for.

Automation testing trends to watch out in 2020

1. Test automation to improve quality for Agile and DevOps

As businesses face constant pressure to meet the changing customer demands and expectations, agility becomes the key to success for coping with the transformation. Additionally, enterprises lookout for agile processes and software delivery approaches such as DevOps to ensure a faster delivery time of applications to the market. Agile-DevOps transformation has brought about higher levels of quality, flexibility, efficiency, and productivity to achieve faster release cycles, improved quality, and increased ROI.

Related Reading: Myths About Load Testing in Agile Environment

2. Usability testing to ensure improved user experience

Mobile and eCommerce applications are great enablers for businesses today. User Interface, as well as the operational flows, play a critical role in determining whether the visitors continue to be users or not. A quick application loading time can enhance your brand loyalty and improve customer experience and retention. 

3. Big Data testing to tackle huge volumes of data

Historical data helps enterprises gain critical insights on future plans and objectives and helps them to be proactive through predictive maintenance, machine learning, and AI techniques. Mining structured, as well as unstructured data, are hence important for effective testing. 

4.  IoT testing  for well-connected devices 

According to the latest reports published by Statista, the entire installed base of the Internet of Things connected devices is forecasted to amount to 75.44 billion worldwide by 2025. This figure was just 6.4 billion during the year 2016. This increase in the figures illustrates the massive requirement for effective IoT strategies in test automation. This testing includes testing of OS, various software and hardware of the IoT connected devices, different communication protocols, and so on. 

5. AI and ML testing  for technological innovations

The global AI software market is forecasted to grow to $14.7 billion by the year 2025. AI and ML technologies such as gesture recognition and speech recognition are taking over the world by storm. Similarly, technologies such as neural networks and predictive maintenance also require high-quality testing methodologies for technological innovations.

6. Blockchain Testing 

Blockchain Testing enables smart contracts and prevents fraudulent transactions, especially when dealing with digital currencies such as Bitcoin. Blockchain debugging is thus crucial for enabling streamlined and smooth financial currencies. 

7. Cyber Security Testing

Cyber vulnerabilities increase day by day and tackling them requires effective testing practices. (CEH) Certified Ethical Hackers with key security tools and technologies can safeguard applications from malfunctions and cyber attacks.

8. RPA Testing

RPA (Robotic Process Automation) testing ensures enhanced output, facilitates high-end performance and reduces the efforts required while performing end-to-end testing. For instance, robots can enhance a workspace with its capability to perform redundant tasks. RPA testing is thus crucial for effective applications with faster development cycles. 

Related Reading: Quality Assurance in Software Testing – Past, Present & Future

Integrating automation testing into your workflow requires you to take into account how it will impact the people, process, and technology of your organization. It’s also crucial to measure if automation fits into the cycle of continuous integration and delivery and how it will merge with your software development lifecycle. Fingent helps you reap the benefits of test automation. Contact us to know more. 

Industry 5.0 Is All Set to Highlight the Significance of Humanity at Workplace******

“The industrial revolution was another of those extraordinary jumps forward in the story of civilization.”

                                 – Stephen Gardiner, English bishop, and statesman.

Standing at the threshold of the 5th industrial revolution (also known as Industry 5.0 or 5IR), we are poised for another jump forward.  And yet, we have seen in the past that the march of these successive industrial revolutions has left an element of dehumanization in their wake. Will that be true of the 5th industrial revolution as well? Experts disagree, which is good news indeed. 

This blog takes a look at how the 5th industrial revolution is bringing the focus back to humanity.

A Phenomenal Journey Towards the 5th Industrial Revolution

The journey started in 1760 when the first industrial revolution ushered in urbanization, providing work for people at factories. 

The second industrial revolution changed the socio-economic situation of the world, improving transport and communication. Also, better automation provided better employment opportunities.

The third industrial revolution saw the invention of the computer, enabling automation in both the office and production lines.

The fourth industrial revolution brought in better communication and connectivity across the globe. It saw the advent of intelligent technologies like robotics, blockchain, IoT, and more.

Artificial Intelligence, Robotics, Augmented Reality and more such technologies have changed the technological landscape like never before. Let’s not forget how Artificial Intelligence has tremendously transformed, customer experience, in recent years. Here’s a look!

That leads us to the question: What can we expect from the 5th industrial revolution and will it help improve humanity? 

Before that, let us find out what the 5th industrial revolution is exactly.

The 5th Industrial Revolution

Though different experts have different explanations about what the 5th industrial revolution is, most of them agree that the 5th would be based on the 4th. 

Why?

A look at history shows that each revolution became the foundation for the next revolution. We can thus expect the 5th revolution to be built over the 4th revolution, but it will go one step further. 

An article developed in collaboration with the World Economic Forum puts it this way: “In contrast to trends in the Fourth Revolution toward dehumanization, technology and innovation best practices are being bent back toward the service of humanity by the champions of the Fifth … In the Fifth Industrial Revolution, humans and machines will dance together, metaphorically.” 

(Sorce: DataProt)

With this in mind, we can foresee the 5th industrial revolution to be an AI (artificial intelligence) revolution with the potential of quantum computing which will draw humans and machines together at the workplace. It is about harnessing the unique attributes of AI by recruiters and employers who in effect will be more equipped to make even better and more informed decisions.

“AI is becoming more prominent with 50 percent of workers currently using some form of AI at work. However, 76 percent of workers (and 81 percent of HR leaders) find it challenging to keep up with the pace of technological changes in the workplace.”

How Industry 5.0 Brings Back the Focus to Humanity

1. Uncaging recruiters

The 5th industrial revolution (5IR or Industry 5.0) places greater importance on human intelligence than ever before. Even today in the war on talent, AI enables recruiters to capture better profile matches. 5IR brings huge benefits in providing the candidates with a more personalized experience in their job search. 

“According to an article in Forbes: 34% of HR leaders are investing in workforce learning and reskilling as part of their strategy to prepare for the future of work!”

5IR will also uncage human resource teams from the major part of daily administration. This will give them time to fine-tune and meet talent requirements, allowing them to focus on the growth and productivity of their organization.

Read more:  Learn why you need to develop a custom platform for remote employee hiring and onboarding.

2. Puts women at the forefront

Martha Plimpton said, “Women have always been at the forefront of progressive movements.” This is true even with regard to 5IR. It will play a critical part in shaping the role of women. As businesses hire unbiasedly, women and girls worldwide will be empowered. 

3. Prevents the repetition of Engels’ pause

During the first industrial revolution, though per worker output expanded, real wages stagnated for about 50 years. This stagnation was called Engels’ pause. It is estimated that 5IR has the potential to prevent such stagnation. Though 5IR will take away mundane and repetitive tasks, it opens the way to curiosity, creativity, empathy, and judgment ensuring a balance between people and technology. 

4. Changes the way we work

Most of us no longer want to work at 9-5 jobs. The way we work is dramatically changing. As our preferences in job and timings change, companies are forced to change too. Surely 5IR will change this even further. 

New employees will no longer have to read a pile of documents or sit through meetings to get all the current and accurate information. This would mean that you can onboard them very easily without having to invest a great deal in training. 5IR will help companies make the most of existing resources helping management teams to focus on more strategic tasks.

The recent pandemic situation has also paved the way for remote working culture, which is now gaining fast popularity. Innovative cloud platforms, such as InfinCE, are supporting this rapidly evolving work culture with streamlined collaboration and smooth communication solutions. Enabling enhanced communication channels, video conferences, and a secured environment for task sharing, monitoring, and collaboration; InfinCE and such other integrated cloud platforms are revolutionizing the work culture of the future. Let’s not forget that with the revolutionary 5G technology, remote collaboration is expected to take new heights with virtual meetings and augmented solutions. Here’s a deeper look into how 5G is reinventing the way we work.

Although the advanced communication channels and collaboration apps, along with 5G technology is creating an impact on work culture, experts call AI and Remote Work, a match made in the future. Why? Here are a few reasons!

• Monitoring the outputs of the remote workforce has always been a concern. But with machine learning and artificial intelligence, tracking remote tasks in real-time is not just possible but also effective and seamless.
• The HR management has to comply with company policies and other legal requirements before recruiting, and these tasks prove quite tedious. Utilizing intelligent technologies to create remote positions can streamline these procedures and turn down the load of the people management department.
• Implementing survey-based tools can simplify collecting reviews and reports on employee performance which in turn can help strengthen the workforce of a company.

Intelligent technologies are sure to take a lead when it comes to human resource management, and 5IR is sure to embrace this change!

5. Paperless technology

As mentioned earlier in this blog, 5IR is all about embracing digitization and intelligent technologies to enhance human efficiency. And paperless technology is doing just that! 

Simplifying strenuous paperwork across industries, paperless technology is turning to become the future! Reducing excessive manual effort, to reducing duplication of work and errors, paperless technology is already highly streamlining complex work processes in Banking, Finance, and Law sectors. 

Another industry that has hugely benefited from this technology is the field service industry. Going paperless on the field is not just enhancing field service management efficiency but is also enabling field technicians to leverage complete digitization. Mobile field service apps like ReachOut Suite are utilizing these evolving capabilities of mobility and digital forms to empower field workers with streamlined collaboration, easy management, and instant report generation solutions to deliver enhanced customer experiences.

When talking about paperless technology and the future, let’s not forget how machine learning is impacting and shaping this new paperless era. With advanced tools to print, scan, and sign digitally, ML is taking the paperless revolution to the next level, providing a wider scope for paperless offices and digital environments. Here’s a deeper look into how Machine Learning edges us closer to paperless offices!

The 5th Industrial Revolution is Just What We Need

In 5IR, technology will bend back towards the service of humanity, marked by creativity and a common purpose. 5IR will empower us to close the historic gap and create a new socio-economic era. Isn’t that exactly what the world needs?

Fingent offers custom software solutions to address your unique business needs. If there is anything that we could help you with, please connect with us. 

Transform Your Business IT Infrastructure With Kubernetes

Today’s competitive world requires businesses to come out with applications that offer unified customer experience along with premium quality. In this scenario, every enterprise CIO is concerned about their IT infrastructure that needs to support such high-quality applications that are sophisticated in terms of capacity, customization, scalability, security, and cost factors. This is where Kubernetes, the open-source container orchestration platform has evolved as a de facto standard in enhancing the IT infrastructure of enterprises to achieve their business goals with positive outcomes. 

What Is Kubernetes?

Kubernetes can be explained as a workload distribution and orchestration method for servers that are clustered in a data center. It ensures the availability and accessibility of resources as well as offers a balanced execution for multiple servers involved simultaneously. 

Being a mechanism of distributed data processing, Kubernetes can enable any number of servers of various kinds at the same time, which can be located at any distance, to share workloads for a common client. These workloads are then presented to clients as services. Through this mechanism, Kubernetes enables the client system to access services via the network, pass data, and collect responses from the network as well.

Why Use Kubernetes?

Many data points reveal rapid Kubernetes adoption for their IT infrastructure benefits. Google-created Kubernetes is now part of the CNCF (Cloud Native Computing Foundation) and can be run on-premises or within the public cloud. 

Kubernetes deploys applications cost-effectively as it consumes less IT manpower for application management. Additionally, Kubernetes makes applications more portable so that they can be moved easily between various clouds as well as internal environments.

Related Reading: Cloud Service Models Saas, IaaS, Paas – Choose the Right One for Your Business

How Kubernetes Can Benefit Your IT Infrastructure

Kubernetes is a system that can be used to deploy applications efficiently. As a result, it can help enterprises save money by using less manpower to manage their IT infrastructure. 

Kubernetes effectively automates the management of containers. As containers allow pieces of code to be assembled into smaller and easily portable pieces, and larger applications involve a bundle of several containers, Kubernetes can organize multiple containers into units. Thus containerized applications can be scaled in an automated manner, making it more feasible with only lesser resources required to manage multiple containers. 

Kubernetes offers these capabilities to your business:

• Multi-cloud flexibility –  As more enterprises are running on multi-cloud platforms, they benefit from Kubernetes as it easily runs any application on any public cloud service or a combination of public and private clouds.  It is a great way to avoid vendor lock-in and allows you to assign the right workloads to the right cloud. 
• Faster time to market – As Kubernetes can help your development team to break down into smaller units to focus on single, specific, and smaller microservices, these smaller teams tend to be more agile. Additionally, APIs between these microservices can be a huge benefit to your IT infrastructure by significantly reducing the amount of cross-communication between the teams. Thus, Kubernetes manages large applications across multiple containers efficiently and also handles service discovery by allowing containers to communicate with each other. It also provides access to storage from different vendors such as Azure and AWS.
• IT cost optimization – Kubernetes provides a feasible container-based architecture which makes scaling of applications much simpler, using the cloud and hardware investments of your enterprise. This automated scaling of applications to meet business needs without over-provisioning your infrastructure will free up your resources and lead to the optimization of IT costs. 
• Improved scalability and availability – Performance and scalability are two critical factors that make an application successful. Kubernetes serves as a critical management system that can scale up the application as well as its infrastructure whenever the workload increases, and scale it down as the load subsides. This auto-scaling capability of Kubernetes can handle any kind of metrics, be it resource utilization metrics or custom metrics. 
• Effective migration to the cloud – Kubernetes can handle rehosting, re-platforming, as well as refactoring. It offers a seamless path to port your application from on-premise to cloud effectively. 

Related Reading: 5 Trends That Will Transform Cloud Computing in 2020

 Kubernetes offers a simpler way of managing containers effectively. It not only reduces your business cost but also provides value to your customers. 

Drop a call to us right away if you are looking out for options to reduce complexity and costs related to your IT infrastructure. Our experts will guide you on a feasible and agile way to structure your IT infrastructure for positive outcomes. 

Fingent Receives High Praise from Leading Businesses Around The World!

In today’s increasingly digital marketplace, technology is key to gaining a competitive advantage. Of course, with technology advancing at an unprecedented rate, determining how to most effectively deploy the latest technologies is easier said than done.  As a top custom software development company, we build high-quality, cost-effective web and mobile solutions that deploy the newest technologies and meet all of your enterprise needs. 

We’re committed to delivering the best quality and customer service — and for that reason, we’re a trusted partner to some of the world’s leading enterprises and businesses. 

We know how important it is for potential buyers to peruse client testimonials and understand what it’s like to work with us before signing a contract, and that’s why we’ve partnered with the ratings and reviews platform Clutch.

Of more than 300 firms, Clutch ranks us among the top 3 software developers in NY! Clutch determines industry leaders based on market research and client feedback, so we’re immensely grateful to the clients who have left reviews for us. One of our recent reviews was from Wage CALC, a company that provides attorneys and legal professionals with a better way to manage their wage and hour cases with wage & analysis software. 

Wage CALC was in need of custom software development services. They were looking for a trustworthy, well-known developer — and they found us on Clutch! Deploying a Microsoft Excel prototype that they’d created, we built their cloud-based app from the ground up.

“I’ve had such an excellent experience with them. Fingent exceeded my expectations.” — Founder & CEO, Wage CALC

The client was impressed that we were able to break down their complex, formula-heavy prototype. They commended our professional and responsive team and were particularly appreciative of how our SVP helped to streamline communication between our team in India and theirs in California.

We received another 5-star review from a large transportation and logistics company that specializes in oil and gas equipment pickup and delivery. There’s a significant technology gap when it comes to processing orders, invoicing, and workflow management within the logistics industry, and we were prepared to change that.

We developed an end-to-end transportation management solution. The solution allows customer service representatives to assign vehicles for order pickup and delivery, while drivers can use a mobile version of the solution to send documentation and process tickets and billing. The company’s accounting team also uses the system to do invoicing, collect payments, and close orders. 
“The management system is light years ahead of anything else in our industry.” — IT Director, Transporation Company

The client appreciated our consistency and availability, along with our team’s impressive knowledge and talent.

Meanwhile, The Manifest, Clutch’s partner site listing market experts, ranks us as the #1 custom software development company.

Fingent is not just recognized by the Clutch! A few well-known rating sites like the Software World, have also appreciated Fingent for its expertise in software development and technology solutions.

Learn more on why Fingent is the most trusted Tech Partner for emerging enterprises, and how our expertise can benefit your business. Contact us today — we offer free consultations! 

2020 Turning The Year Of Multi-Cloud Adoption for Enterprises

There has been a lot of hype going on around businesses adopting multi-cloud strategies that make use of public, private, and hybrid cloud services. Businesses, especially the mid-market and enterprise-level industries can utilize multi-cloud strategy as a smart investment by leveraging the benefits of its resilient performance and virtual infrastructure.

A multi-cloud strategy is all about adopting a mixture of IAAS (Infrastructure As A Service) services from multiple cloud providers and sharing workloads among each of these services which are reliable, secure, flexible, and of course cost-effective. 

Why Must Businesses Opt For A Multi-Cloud Strategy?

Businesses can adopt a multi-cloud strategy to acquire an optimal distribution of assets across the user’s cloud-hosting environments. With a multi-cloud strategy, businesses can have access to multiple options such as favorable Service Level Agreement terms and conditions, greater upload speed selection, customizable capacity, cost terms, and many more.

How Can Businesses Make A Multi-Cloud Adoption Decision?

Multi-cloud adoption decisions are based on 3 major considerations:

• Sourcing – Agility can be improved and chances of vendor lock-in can be avoided or minimized by sourcing. This decision can be driven by factors such as performance, data sovereignty, availability, regulatory requirements, and so on.
• Architecture – Architecture is a major decision-driver as many modern applications are mostly of modular fashion that can span multiple cloud providers and obtain services from any number of clouds.
• Governance – Businesses can now standardize policies, procedures, processes, and even share tools that can enable cost governance. By adopting services from multiple cloud providers, enterprises can now ensure operational control, unify administrative processes, and monitor their IT systems more effectively and efficiently.

Better disaster recovery and easier migration are the other key benefits that drive enterprises to adopt multi-cloud strategies.

Related Reading: Cloud Computing Trends To Expect In 2020

Top 7 Reasons To Adopt Multi-Cloud For Your Business

• Ability To Find The Best-In-Class Multi-Cloud Providers

Businesses administrators can bring in the best-in-class cloud hosting providers for each task that best suits their requirements. In a recent survey by Gartner, 81% of respondents said that the multi-cloud approach proved beneficial to them. Businesses are free to make their decisions based on the sourcing, architecture, and governance factors as mentioned above.

• Agility

According to a recent study by RightScale, organizations leverage almost 5 different cloud platforms on average. This figure shows the transformation of enterprises increasingly towards multi-cloud environments. Businesses struggling with legacy IT systems, hardware suppliers, and on-premise structures can benefit from adopting multi-cloud infrastructures to improve agility as well as workload mobility amongst heterogeneous cloud platforms.

• Flexibility And Scalability

With a competent multi-cloud adoption, enterprises can now scale their storage up or down based on their requirements. A multi-cloud environment is a perfect place for the storage of data with proper automation as well as real-time syncing. Based on the requirements of individual data segments, businesses can depend on multiple cloud vendors specifically. For improved scalability, enterprises must focus on achieving the following 4 key factors:

1. A single view of each cloud asset
2. Portable application design
3. The capability to automate and orchestrate across multiple clouds
4. Improved workload placement

•  Network Performance Improvement

With a multi-cloud interconnection, enterprises can now create high-speed, low-latency infrastructures. This helps to reduce the costs associated with integrating clouds with the existing IT system. When businesses extend their networks to multiple providers in this manner, proximity is ensured and low-latency connections are established that in turn improves the application’s response time along with providing the user a better experience. 

• Improved Risk Management

Risk management is a great advantage that multi-cloud strategies can provide businesses with. For instance, consider the case where a vendor has an infrastructure meltdown or an attack. A multi-cloud user can mitigate the risk by switching to another service provider or back up or to a private cloud, immediately. Adopting redundant, independent systems that provide robust authentication features, vulnerability testing as well as API assets consolidation ensure proper risk management. 

• Prevention Of Vendor Lock-In

With a multi-cloud strategy, enterprises can evaluate the benefits, terms, and pitfalls of multiple service providers and can choose the option to switch to another vendor after negotiation and careful validation. Analyzing terms and conditions before signing a partnership with a vendor can prevent vendor lock-in situations.

• Competitive Pricing

Enterprises can choose between the vendors and select the best-suited based on their offerings such as adjustable contracts, flexible payment schemes, the capacity to customize, and many other features.

To learn more about adopting an effective multi-cloud strategy and the benefits it offers, drop us a call and talk to an expert. 

Understanding the Importance of Times Series Forecasting 

To be able to see the future. Wouldn’t that be wonderful! We probably will get there someday, but time series forecasting gets you close. It gives you the ability to “see” ahead of time and succeed in your business. In this blog, we will look at what time series forecasting is, how machine learning helps in investigating time-series data, and explore a few guiding principles and see how it can benefit your business.

What Is Time Series Forecasting?

The collection of data at regular intervals is called a time series. Time series forecasting is a technique in machine learning, which analyzes data and the sequence of time to predict future events. This technique provides near accurate assumptions about future trends based on historical time-series data.

The book Time Series Analysis: With Applications in R describes the twofold purpose of time series analysis, which is “to understand or model the stochastic mechanism that gives rise to an observed series and to predict or forecast the future values of a series based on the history of that series.” 

Time series allows you to analyze major patterns such as trends, seasonality, cyclicity, and irregularity. Time series analysis is used for various applications such as stock market analysis, pattern recognition, earthquake prediction, economic forecasting, census analysis and so on. 

Related Reading: Can Machine Learning Predict And Prevent Fraudsters?

Four Guiding Principles for Success in Time Series Forecasting

1. Understand the Different Time Series Patterns

Time series includes trend cycles and seasonality. Unfortunately, many confuse seasonal behavior with cyclic behavior. To avoid confusion, let’s understand what they are:

• Trend: An increase or decrease in data over a period of time is called a trend. They could be deterministic, which provides an underlying rationale, or stochastic, which is a random feature of time series.
• Seasonal: Oftentimes, seasonality is of a fixed and known frequency. When a time series is affected by seasonal factors like the time of the year or the day of the week, a seasonal pattern occurs.
• Cyclic: When a data exhibit fluctuates, a cycle occurs. But unlike seasonal, it is not of a fixed frequency.

2. Use Features Carefully

It is important to use features carefully, especially when their future real values are unclear. However, if the features are predictable or have patterns you will be able to build a forecast model based on them. Using predicted values as features is risky as it can cause substantial errors and provide a biased result. Properties of a time series and time-related features that can be calculated could be added to time series models. Mistakes in handle features could easily get compounded resulting in extremely skewed results, so extreme caution is in order.

Related Reading: Machine Learning Vs Deep Learning: Statistical Models That Redefine Business

3. Be Prepared to Handle Smaller Time Series

Don’t be quick to dismiss smaller time series as a drawback. All time-related datasets are useful in time series forecasting. A smaller dataset wouldn’t require external memory for your computer, which makes it easier to analyze the entire dataset and make plots that could be analyzed graphically.

4. Choose The Right Resolution

Having a clear idea of the objectives of your analysis will help yield better results. It will reduce the risk of propagating the error to the total. An unbiased model’s residuals would either be zero or close to zero. A white noise series is expected to have all autocorrelations close to zero. In other words, choosing the right resolution will also eliminate noisy data that makes modeling difficult.

Types of Time Series Data and Forecasts

Times series basically deals with three types of data –  time-series data, cross-sectional data, and pooled data, which is a combination of time series data and cross-sectional data. Large amounts of data give you the opportunity for exploratory data analysis, model fidelity and model testing and tuning. The question you could ask yourself is, how much data is available and how much data am I able to collect?

There are different types of forecasting that could be applied depending on the time horizon. They are near-future, medium-future and long-term future predictions. Think carefully about which time horizon prediction you need.

Organizations should be able to decide which forecast works best for their firm. A rolling forecast will re-forecast the next twelve months, whereas the traditional, or a static annual forecast creates new forecasts towards the end of the year. Think about whether you want your forecasts updated regularly or you need a more static approach.

By allowing you to harness down-sampling and up-sampling data, the concept of temporal hierarchies can mitigate modeling uncertainty. It is important to ask yourself, what temporal frequencies require forecasts?

Keep Up With Time

As businesses grow more dynamic, forecasting will get increasingly harder because of the increasing amount of data needed to build the Time Series Forecasting model. Still, implementing the principles outlined in this blog will help your organization be better equipped for success. If you have any questions on how to do this, just drop us a message. 

A Look Into The Cloud Computing Trends for 2020

“Fewer, but larger, public cloud platform providers and a maturing SaaS ecosystem will dominate enterprise cloud spending” – The Public Cloud Market Outlook, 2019 To 2022 Forrester Report.

Organizations are recognizing the importance of cloud computing and are adopting the technology steadily over the past few years. With recent technological advancements creating new excitement around the idea of cloud computing, the adoption is now skyrocketing! 

According to Gartner, the worldwide public cloud services market will gain a positive growth of 17% in 2020. That is an increase from $227.8 billion in 2019 to 266.4 billion in 2020. This makes it vital for organizations to identify the forces that will shape the cloud computing market this year. This article will help you with this as we discuss five specific trends that will transform cloud computing in 2020.

Why Keep Up with Cloud Computing?

Aggregated mostly around Amazon, Google and Microsoft, the cloud market underwent a profound change in the recent past. The pace for cloud adoption and innovation will inevitably continue to accelerate across industries and regions providing new opportunities, and new levels of quality and efficiency. The question you must be asking is: What is in store for the cloud computing market and how should you prepare for it in 2020?

1. Shifting Gears from Multi-Cloud to Hybrid-Cloud

2019 has seen how organizations routinely deployed workloads across multiple clouds. In order to achieve expected outcomes in business, organizations will have to adopt the right and appropriate cloud strategy. A hybrid cloud computing structure uses an orchestration of local servers, private cloud, and third-party public cloud services to achieve desired results. According to The RightScale 2019 State of The Cloud Report, the hybrid cloud adoption rate was estimated at 58% last year.

In this transitional era, the hybrid-cloud will become an integral part of the long-term vision for industries on how they will meet their needs. It can provide a seamless experience to enterprises and help them solve complicated challenges around latency. Customers too won’t have to deal with two different pieces of infrastructure; on-premise and public cloud. Thus, the shift to a hybrid-cloud will make things easier for both the organization as well as the customers.

Related Reading: Hybrid Cloud Infrastructure: How It Benefits Your Business

2. Serverless Computing 

“Serverless computation is going to fundamentally change not only the economics of what is back-end computing, but it’s going to be the core of the future of distributed computing,” says Satya Nadella, Chief Executive Officer at Microsoft. This comment clearly shows what the future of serverless computing is. 

Serverless computing ensures that developers must only focus on their core product without worrying about operating and managing the servers. This is an advantage that moves enterprises to adopt serverless computing. According to Gartner, more than 20% of global enterprises will deploy serverless computing technologies by 2020.

3. Cloud Security will Become Paramount

Many organizations feel that cloud computing could pose security issues. They might have concerns about regulatory and privacy issues, along with compliance and governance issues. Consequently, security features of public data have become the key focus in 2020. It will not be just about access controls or policy creations. Aspects such as data encryption, cloud workload security, and threat intelligence will gain priority as part of an organization’s security measures. 2020 will also see security features such as privileged access management and shared responsibility models.

According to Kristin Davis of 42crunch.com, 2019 became the year where API Security threats came to notice. As the year progressed, we have observed a lot of high profile API breaches and vulnerabilities, including the ones at Facebook, Amazon Ring, GitHub, Cisco, Kubernetes, Uber, Verizon, etc. In their October 2019  report, Gartner estimates that by 2021, exposed APIs will form a larger attack surface than UIs for 90% of web-enabled applications. In 2020, we expect API security getting to the top of the agenda of a chief information security officer. Also, DevOps tools and processes are expanding to DevSecOps, to lower the risks and implement security by design. 

Mihai Corbuleac, Senior IT Consultant at StratusPointIT predicts security acquisitions to make more headlines in 2020, it has made the headlines over the last year. It is because all cloud companies that can’t develop in-house modern security solutions have to look to buy them.

Related Reading: How Secure is Your Business in a Multi-Cloud Environment

4. Digital Natives

As the workforce evolves, the expectations of the workers will definitely increase. Those joining the workforce will be well-acquainted with cloud computing and its advantages. Such workers are called ‘digital natives.’  

Organizations will have two sets of workers as a consequence: those who have adopted digital best practices and those who have not. This would call for a need to train the second set of workers, which is called ‘reverse mentoring.’ The adoption of cloud computing and related technologies will enable organizations to integrate both the workgroups into one unified workforce. 

5. Quantum Computing 

Quantum computing requires massive hardware developments. This opens up the potential to exponentially increase the efficiency of computers in 2020. It allows computers and their servers to process more rapidly than ever before. Quantum computing also has the potential to limit energy consumption. It requires lesser consumption of electricity while generating massive amounts of computing energy. Best of all, quantum computing can have a positive effect on the environment and the economy. 

Are You Keeping Up the Pace? 

Whether you are a large organization or a small one, cloud computing will remain a compelling, fast-moving force in 2020. Adopting cloud computing technology will enable organizations to mitigate risks and capitalize on opportunities. Ultimately, organizations will have a number of decisions to make with regards to cloud computing. It will include deciding when and how to adopt cloud computing technology, as well as for deciding on the specific model they would like to adopt. 

Related Reading: Cloud Migration: Essentials to Know Before You Jump on the Bandwagon

With years of experience in helping clients transform their business by the power of the cloud, Fingent can help you understand and implement this technology seamlessly in your business. Contact us to know more.

How AI and Voice Search Will Impact Your Business in 2020

“It is common now for people to say ‘I love you’ to their smart speakers,” says Professor Trevor Cox, Acoustic engineer, Salford University. 

The Professor wasn’t exactly talking about the love affair between robots and humans, but his statement definitely draws attention to the growing importance of voice search technology in our lives. AI-driven voice computing technology has drastically changed the way we interact with our smart devices and it is bound to have a further impact as we move into 2020. 

In this blog, we will consider six key predictions for AI-Driven voice computing in 2020.

How Essential Is AI-Driven Voice Search For Businesses?

Voice search is becoming increasingly popular and is evolving day after day. It can support basic tasks at home, organize and manage work, and the clincher – it makes shopping so much easier. No doubt about it, AI-driven voice search and conversational AI are capturing the center stage. 

Related Reading: Why you can and should give your app the ability to listen and speak

Voice-based shopping is expected to hit USD 40 billion in 2022. In other words, more and more consumers will be expecting to interact with brands on their own terms and would like to have fully personalized experiences. As the number of consumers opting for voice-based searches keeps increasing, businesses have no option than to go all-in with AI-driven voice search. With that in mind, let’s see where this is going to be leading businesses in 2020. 

Six key predictions for AI-driven voice search and conversational AI in 2020

1. Voicing a human experience in conversational AI

Chatbots are excellent, but the only downside is that most of them lack human focus. They only provide information, which is great in itself, but not enough to provide the top-notch personalized experience that consumers are looking for.  This calls for a paradigm shift in conversational design where the tone, emotion, and personality of humans are incorporated into bot technologies. 

Statista reports that by 2020, 50% of all internet searches will be generated through voice search. Hence, developers are already working on a language that would be crisp, one that is typically used in the film industry. Such language could also be widely used on various channels such as websites and messaging platforms. 

Related Reading: Capitalizing on AI Chatbots Will Redefine Your Business: Here’s How

2. Personalization

A noteworthy accomplishment in voice recognition software enhancing personalization is the recent developments in Alexa’s voice profiling capabilities. Personalization capabilities already in place for consumers are now being made available to skill developers as part of the Alexa Skills Kit. This will allow developers to improve customers’ overall experience by using their created voice profiles.

Such personalization can be based on gender, language, age and other aspects of the user. Voice assistants are building the capacity to cater even to the emotional state of users. Some developers are aiming to create virtual entities that could act as companions or councilors. 

3. Security will be addressed 

Hyper personalization will require that businesses acquire large amounts of data related to each individual customer. According to a Richrelevance study, 80% of consumers demand AI transparency. They have valid reasons to be concerned about their security. This brings the onus on developers to make voice computing more secure, especially for voice payments.

4. Natural conversations

Both Google and Amazon assistants had a wake word to initiate a new command. But recently it was revealed that both companies are considering reducing the frequency of the wake word such as “Alexa.” This would eliminate the need to say the wake word again and again. It would ensure that their consumers enjoy more natural, smooth and streamlined conversations.

5. Compatibility and integration

There are several tasks a consumer can accomplish while using voice assistants such as Amazon’s Alexa or Google’s Assistant. They can control lights, appliances, smart home devices, make calls, play games, get cooking tips, and more. What the consumer expects is the integration of their devices with the voice assistant. 2020 will see a greatly increased development of voice-enabled devices.

6. Voice push notifications

Push notification is the delivery of information to a computing device. These notifications can be read by the user even when the phone is locked. It is a unique way to increase user engagement.  Now developers of Amazon’s Alexa and Google Assistant have integrated voice push notifications which allow its users to listen to their notifications if they prefer hearing over reading them.

What Does It Mean for Your Business In 2020?

AI-driven voice computing and conversational AI is going to change all aspects of where, when and how you engage and communicate with your consumers. By 2020, IDC  estimates a double-digit growth in the smart home market. Wherever they are and whatever channel they are using, you will be required to hold seamless conversations with your customers across various channels. 

“Early bird catches the worm.” Be the first in your industry to adopt and gain the benefits of voice search and conversational AI.  Call us and find out how we can make this happen for you.

Attaining Digital Transformation Success with AIOps in 2020

Your IT infrastructure is the key pillar of your organization and this dependency will only increase steadily in 2020. You need help to cope with this massive dependency, and digital transformation will play a crucial role in this. Now, in order to make your digital transformation successful, you need something powerful, radical and looking up to the next-gen. That is what AIOps is.

Related Reading:  How Digital Innovation Transformed Today’s Business World

This blog will discuss how organizations can apply AIOps to drive digital transformation and make your IT operations a success for the future of your business.

Defining AIOps and Its Crucial Role

AIOps was initially used by Gartner in 2017 as an acronym for Artificial Intelligence for IT operations. AIOps is a beautiful synchronization of machine learning, analytics, and AI. These technologies are brought together in order to derive meaning from massive datasets. It pools all kinds of data gathered from different sources and uses advanced AI and ML operations to enhance a wide range of IT operations. The insights derived are far beyond what human analysis could achieve. 

As IT infrastructure is becoming progressively complex with the demands of digital transformation, this potential of AIOps is becoming critical to successful IT development. Traditional methods of managing your complex infrastructure could increase your costs, create maintenance issues and increase possibilities of slowdowns. AIOps can equip your IT teams to overcome such problems, trends, and slowdowns. It allows your teams to prioritize and focus on the most important information while AIOps reduces normal alert noises and identifies patterns automatically without human input.

Related Reading: How IT-as-a-Service Boost the Digital Transformation of Enterprises

In fact, AIOps is becoming a necessity for every organization. Gartner predicts that 30% of large enterprises will adopt AIOps by 2023.  According to another research, AIOps platform market is expected to grow to $11.02 billion by 2023. Hence, the question larger organizations should ask themselves is not “if” they need to adopt AIOps, but “when.” 

How is AIOps Driving Digital Transformation?

Since digital transformation includes cloud adoptions, quick change and implementation of new technologies, it requires a shift in focus. Instead of users struggling with traditional services and performance management strategies and tools, AIOps offers organizations a perfect model to handle digital transformation. It can help your team to manage the speed, scale, and complexity of changes, which are the key challenges of digital transformation. 

Here are some essential steps to effective AIOps:

1. Act Fast

Timing is everything in business and hesitation in the adoption of technologies can set you back more than you can imagine. Even if you feel that you aren’t ready to adopt AIOps yet, read about it and familiarize yourself with the vocabulary and capabilities of AIOps. It will help you make an informed decision when it is the right time. 

2. Start Small

All in or all out doesn’t necessarily apply to digital transformation. Starting small could actually prove beneficial to your organization. This would mean that you focus on what is practical and achievable. Your initial use cases could include application performance monitoring, dynamic baselining, predictive event management, and event-driven automation.

3. Restructure Your Team

Successful adoption of AIOps might require restructuring the roles of your team. This would ensure that the best resources are used for the right jobs. Also, identify experience gaps and fill those gaps by providing the necessary training. 

Related Reading: Fingent Speaks: What it Takes to Build a Successful Digital Transformation Strategy

4. Leverage Available Resources

Your organization might already have data and analytic resources. Since these teams are already skilled in data management, their skill set can be effectively leveraged for AIOps.

5. Increase Proficiency by Developing Core Capabilities

Developing core capabilities such as machine learning, open data access, and big data can prove beneficial. For example, the massive amount of data generated by digital transformation can be overwhelming.  Since the AIOps platform must support responsive ad-hoc data exploration and deep queries, developing this capability can also help you build up progress towards the use of AIOps.

6. Track Business Value

Make sure that the value of AIOps is tied to your overall business objective. The key performance indicators must correlate with best practices and should remain measurable. Ensure that your business is able to obtain a complete and referenceable history of such values.

What Is Your Plan of Action?

AIOps might be taking its first steps, but it is what will eventually drive your digital transformation with unmatched speed and stability. Selecting the right use cases might be challenging initially and might require significant process reengineering. Fingent can help you get there. Call us to find out more.  

Factors To Consider While Migrating Your Code To Python 3

It’s clear that Python 2 will be sunsetting on January 1, 2020. The Python Software Foundation (the organization behind Python) has stated that Python 2 will not be improved anymore after that day and no support will be provided to existing Python 2 users even if they find a security problem. The only option is to upgrade to Python 3 as soon as you can. Migrating your business suite from an old to a new software version comes with its own challenges. How can you ensure a successful and smooth migration to Python 3? Here is a guideline that addresses the prerequisites and key considerations. 

Related Reading: Switching to Python 3: Is It An Apt Decision For Your Business?

Steps To Successfully Migrate To Python 3

The recommended steps or course of action is to follow intermediate steps in modernizing incrementally and addressing issues progressively. Simultaneously, it is also important to aim for cross-generational compatibility without replacing the code entirely. A seamless migration process requires the following steps:

1. Drop Support For Python 2.6 And Older Versions

It is to be noted that Python 2.6 is no longer supported freely and is not receiving fixes for bugs. Hence, solving issues that come across while working with Python 2.6 or older versions will be difficult. For instance, Pylint which is used for setting up a Linter coverage is not supported by Python 2.6.

2. Specify A Proper Version Support In The setup.py File

In the setup.py file, a proper trove classifier has to be mentioned. This will help in determining whether all packages are Python 3 compatible. 

3. Ensure A Proper Test Coverage

Proper test coverage can avoid many bugs at production. For instance, your test suite must have at least 80% code coverage. The code coverage will let you know how much source code is executed during testing. coverage.py is the best-recommended tool to measure your test coverage.

4. Update Your Code

Most projects will include multiple third-party dependencies. It is thus important to ensure that all third-party packages are compatible. You can make a choice between two tools namely, Futurize and Modernize to port your code automatically.  

5. Division 

Python 3 evaluates 5/2 == 2.5 and not 2. That means, all divisions of int values in Python 3 result in a float value. Going through your code and adding from_future_import division to your files and updating the division operator to // or using floor division will do the needful.

6. Understanding The Confluence Of Text And Binary Data

It is important to decide which  APIs take text and which of them take binary data. For instance, Python 2 made sure that APIs that take text work with Unicode and APIs that take binary data work with bytes. However, Python 3 takes text as str, and binary as bytes. Additionally, Python 3.5 adds the _mod_ method to the bytes type. 

7. Utilize Feature Detection Instead Of Version Detection

Relying on feature detection helps in avoiding potential problems of compatibility errors. For instance, suppose you require access to a feature of importlib that is available in Python’s standard library since Python 3.3 version. Consider the fact that it is also available for Python 2 via importlib2 on PyPI. In this situation, it is very common to write code using the version. This will create issues with Python 4. It is thus better to utilize feature detection. 

8. Prevent Compatibility Regressions

Once the code is translated and made compatible with Python 3, it is important to ensure that the code does not regress. You can use the Pylint for the same. Example, pip install pylint.

9. Check For Dependencies That Can Block Your Transition

The caniusepython3 will help you determine all projects that directly or indirectly can block your transition to Python 3.

10. Continuous Integration To Ensure Compatibility

It is important to run your tests under multiple Python interpreters such as tox by integrating them with your system. 

11. Use Of Optional Static Type Checking

A static type checker such as mypy or pytype on your code will help in porting your code. It analyzes your code and checks whether it can run on Python 3 as well. For instance, if you tend to misuse a binary data type in one particular version of Python, running a static type checker will solve the issue.  

The Python Software Foundation offers a comprehensive guide on how to achieve cross-generational compatibility for enterprises that require Python 2 and 3 to run simultaneously. More guidelines and steps to be noted while migrating to Python 3 can be found in these places: 

• An official Python porting guide
• Reference to python-future
• Porting to Python 3 – Django Tips

To learn more about migrating to Python 3 seamlessly, stay tuned to our latest articles and blogs. If you are looking for a technology partner to help your business transform with the latest digital trends, then get in touch with our experts today!