Natural Language Processing – What it is and why it’s important

Introduction

Natural Language Processing — the application of software systems to examining, interpreting and accurately responding to speech is viewed as the next big leap in user interface technology. However, human speech is far more complex than most people realize. There are rules, such as spelling and grammar. How we interpret speech and text, though, is far less well-defined. How do you know when a person is being sarcastic, for example? How do we know that an athlete’s explosive sprint to the finish line didn’t involve any pyrotechnics? In human language, the words can say one thing, but the context and the tone make those words mean something else.

It takes humans a half a lifetime to learn the subtle nuances of language. Even then, there will be words and phrases that some of us don’t understand. Then, there are further complications in understanding language, such as dialects and colloquialisms. So, how can a computer that “thinks” in binary be programmed, line by line, to become fluent in any language? The answer is; it can’t. But, thanks to the advent of artificial intelligence (AI), a computer can now learn how to understand a language.

What Is Natural Language Processing?

Natural language processing (NLP) is a branch of AI. NLP relates to humans and computers communicating using natural language. NLP includes both speech recognition and reading text. Using machine learning, a computer is now able to learn how to understand our speech and writing. Computers can now look at more than the keywords to decipher our language. It can pick up on the more subtle aspects of our language to interpret the contextual meaning of the words.

Why is Natural Language Processing So Important?

In the past, computers could only work with structured languages. The language had to be precise and unambiguous. To program a computer to perform any task, you had to give it clear instructions. You could only use the limited number of commands that the computer understood. The syntax had to be perfect as well.

Even an end-user of a computer program needs to give the computer precise commands. Those who are old enough will remember that to use a PC you once had to know the common MS-DOS commands. That barrier was overcome, to a degree, with graphical user interfaces, such as Windows. Now, we can point to a file with a mouse, instead of having to know the name of the file.

NLP promises to remove the need for being so precise. Instead of having to learn the computer’s language, the computer will learn how to understand ours. A very basic application of NLP will be how we interface with computers. We won’t have to tell the computer to open our “aprilcashflowforcast.XLS” file. We will be able to ask the computer less precise questions, such as “How much cash have we got coming in this month?”

Practical Business Applications of Natural Language Processing

NLP is not an emerging technology that will, one day, have applications in business. It is a technology that is in use now. NLP is being used in applications such as online searching, and grammar checkers. That’s why you can now search on Google using normal sentences. NLP goes far beyond simplifying the computer/human interface, though. Being able to understand human language has many other practical applications. Here are few examples of how NLP is being used today:

Language Translation

NLP programs learn a language in the same way that humans do. And, like humans, if a machine can learn one language, it can learn many. There are now neural machine translation programs that can translate between languages. The first of these was Microsoft’s Bing Translator.

Chatbots

NLP has made chatbots far more effective. This has increased the applications that chatbots are now used for. In HR applications, for example, chatbots are now answering employees’ questions. There is a chatbot called Talla that will answer questions such as “Do I have any vacation left?”.

Document Reading Tools

NLP is also able to read and interpret the written word. One of the practical uses for this technology is the sifting of job applicants’ resumes. Machine learning allows text reading applications to learn synonyms. This is important when reading a resume because people use different terms to describe their personal qualities and their work history.

Sentiment Analysis

As NLP can understand the nuances of language, it can also understand the sentiment of the words. There is a technology known as opinion mining. This can analyze the opinion that people have of a brand by looking at blogs and social media profiles. It can understand the sentiment of posts and comments left by customers. Analyzing vast amounts of data like this would be an impossible task for a human.

Conclusion

Natural language processing is a major leap forward in AI technology. It removes the communication barrier that has always existed between machines and humans. The potential for the application of NLP in business is immense. A computer could now answer customer queries and take orders. Even if the customer uses obscure language. NLP is likely to remove the need for input devices, such as the keyboard and mouse as well. NLP matters, because it is about to revolutionize the way that we communicate with machines, and how they communicate with us.

Robotic Process Automation and Its Applications

Introduction

Many large enterprises are using robotic process automation (RPA) to reduce costs and improve efficiency. By implementing RPA, businesses can automate repetitive and mundane tasks. RPA could represent the first step towards true intelligent automation. But what is RPA, and what are its applications in business?

What Is Robotic Process Automation?

RPA is a term that can be applied to any computer program that automatically performs a repetitive function. In its simplest form, RPA is the automatic out-of-office message that your email software sends. More sophisticated RPA bots can log into an application, perform tasks, and log out again. RPA is not a part of an organization’s IT infrastructure. RPA sits on top of the infrastructure and automates tasks that humans would otherwise perform.

There are three main types of RPA bots. There are programmable bots that interact with other systems. There are intelligent RPA bots that can make decisions based on unstructured data. And, there are self-learning bots, such as chatbots.

Robotic Process Automation is a software technology that automates the execution of tasks, typically those that are repetitive and mundane.

Robotic Process Automation (RPA) is an emerging trend in business process automation. It is a type of computer programming that uses software to control the execution of routine tasks. RPA automates these routine tasks by mimicking human actions, such as clicking or filling out forms on a screen.

Examples of RPA Applications

RPA is suitable for use on tasks that are repetitive, well-documented, and well-defined. If the task is rule-based, and it does not alter often, then it is a task that could be completed by RPA. Robotic process automation can automate a wide variety of tasks in many different industries. Here are a few of the practical applications of RPA.

Web site scraping

RPA can be used to gather information from web pages. Examples of this include extracting and summarizing data from stock trading websites. Once the data has been collected and summarized, it can then be passed to humans for further analysis.

Automated email processing

Many organizations receive lots of emails asking the same questions. RPA can take care of some of these emails and respond with standard replies. The emails that the RPA bot cannot answer can then be forwarded to the appropriate personnel for answering.

Data Cleansing

Data cleansing is a good example of where RPA can be used to complete time-consuming tasks. If there are clear rules as to what constitutes bad data, RPA can filter out that bad data much more efficiently than humans.

Data Entry

One of the most far-reaching applications of RPA is that of data entry. An RPA bot can read original forms using optical character recognition (OCR) and then “key” the data into an application. This would be faster than a human could key the data, and it would be more accurate.

The Benefits of Robotic Process Automation

The benefits of RPA to businesses are many. RPA removes the human error factor from many tasks. The effectiveness of RPA can be limited by the accuracy of technologies, though. Technologies such as optical character recognition and speech recognition software. Even so, RPA bots can work 24/7 without breaks, and they never get bored. Bots also only need training once, and they will never quit their job.

RPA technology brings more than only cost savings. It also improves the customer experience through faster processing of data and faster resolution of queries. For employees, it brings that removal of the boring, repetitive tasks, so that they can spend more time on the important aspects of a role. RPA will change the nature of some jobs, so the HR aspects of those changes must be planned for as well. Overall, though, RPA will change the nature of employment for the better, rather than put people out of work.

Why Businesses Need to Consider Robotic Process Automation

RPA is a technology of today, not of the future. RPA bots are being used in accounting, finance, HR, and marketing now. American Express Global Business Travel uses RPA to automate the canceling of airline tickets and the issuing of refunds. At Walmart, RPA bots answer employees’ questions. In the future, some elements of almost every business process could be automated by RPA.

Robotic Process Automation won’t replace the need for humans. But it will remove the need for humans to perform programmable repetitive tasks. Businesses that do not embrace RPA will find themselves falling behind their competition. They will find that their customer service functions are slower and less efficient. And, they will become less competitive because of the additional costs of employing humans to perform tasks that are better performed by boots, and by not innovating by freeing up humans to do things that bots cannot. Eventually, businesses that do not use RPA will also find it difficult to employ people to perform repetitive tasks. Like their customers, their employees will have all moved to the companies that are using Robotic Process Automation to make life better for customers and employees.

Content Marketing to the Small and Medium-sized Businesses

Content marketing has become an extremely important part of many successful marketing strategies, but there are still many small and medium-sized businesses that have yet to realize the full potential of this means of spreading the corporate message. It provides businesses with the opportunity of attracting customers without having to use traditional forms of advertising, but how does it work, and what are the benefits? Here’s a guide to what content marketing is and why it really does matter for SMBs

What is content marketing?

Content marketing can take many forms, but it can be summarized as the distribution of informative, useful and valuable information with the objective of gaining and retaining a targeted audience and, ultimately, driving that audience closer to becoming customers.

It can take the form of an information-based blog, being quoted on industry websites, the publication of white papers, and the publication of informed expert articles on news sites and in magazines or newspapers.

The primary objective of content marketing is to get the name of the business more widely known, but in a form that is informative and helpful, rather than in a form that requires any specific positive action from the reader in return.

What are the benefits of content marketing to SMB?

There are numerous benefits to be gained from a well-planned content marketing campaign that range from improving SEO rankings for the company’s website, to improving the company’s public image. The hidden benefits include increased brand awareness, brand authority, and brand trust.

Content marketing for SEO

Content marketing can have a direct impact on the position that a website achieves on search results. By including important keywords in the text of articles published on a company blog, as well as in articles published on third-party websites that contain links back to the corporate website, content marketing can strengthen and improve the position at which the company’s website appears in the search engine results for those keywords.

Content marketing for brand awareness, authority, and trust

At its basic level, it can be seen as a means of getting a brand better known, but well-written, authoritative content will also create more trust in a brand and infer more authority, and people will always be more likely to buy from a brand that they know and that they trust.

Content marketing Encourages subscription and sharing

A regular flow of high-quality content will encourage the sharing of that content and that will lead to more and more people becoming aware of the brand. If people find the content useful, they are also more likely to subscribe to feeds and email lists, which will open up the opportunity of sending them more traditional direct sales messages as well as future content.

Why Content Marketing Matters

Content marketing is a very effective way of increasing brand awareness and encouraging engagement with a business but producing a regular flow of high quality, informative content is not as simple as it may first appear.

The starting point is to develop a comprehensive outline of the topics to be covered and, for SEO purposes, identify the relevant keywords. This can then be translated into a strategically sequenced editorial calendar.

Producing high-quality content on a regular basis is a time-consuming task and it can be especially challenging for a small and medium-sized business that have limited resources. For many SMBs, outsourcing content creation is likely to be the best option.

However, it is an extremely powerful form of digital marketing that small and medium-sized businesses really can’t afford to ignore if they want to stay ahead of their competition. Content marketing matters as much to SMBs as it does to the major corporations.

30 Days Minimum Viable Product Wisdom

When anyone sets out to design and market a new product or system of any kind, their first inclination is likely to be to make the first release of that product or system the most functionally rich and complete that it can be. There is, however, a growing acceptance that releasing a minimum viable product (MVP) to early adopters is a far more efficient way to develop a new product or system and one that will ultimately lead to a much better deliverable.

What is a Minimum Viable Product?

The concept of a minimum viable product, which has been popularized by Silicon Valley entrepreneurs Steve Blank, and Eric Ries, is a design and development process in which a new product, such as an app, is developed and initially released with only sufficient functionality to satisfy the needs of the early adopters. Further features and functionality are only added to the product after consideration has been given to the feedback that has been received from those early adopters.

A minimum viable product is a product that has sufficient value to make people want to use it and that has been sufficiently developed so that early adopters can see the future of the product. The aim of MVP is to provide a feedback loop that can be used to guide the future direction of product development.

The advantages of the MVP

Developing a product using the MVP model has distinct advantages over the traditional, all-in-one-go, approach. Here are the main reasons why an MVP produces better apps.

Removes uncertainty

A system spec can only be, at best, a guess of what users will do with an app, how they will interact with it and what functionality they will need from the app. An MVP takes much of the guesswork out of product development and allows time for the feedback of users to drive the development of the product.

Eliminates wasted time

If you attempt to develop a fully completed app-based only on system spec, it is virtually guaranteed that you will develop functionality that users don’t use or functionality that doesn’t quite meet their expectations. It is far more cost-effective, therefore, to develop an app that has all the basic minimum functionality and then lets the user feedback be what dictates the future development of the product.

Applies the 80/20 principle to the development process

The Pareto (80/20) principle is never truer than it is in software development. 80% of the most important requirements of an app are likely to be cared for by just 20% of the functionality. The MVP focuses early development time on getting the essential 20% right so that 80% of essential user needs will be met with the first release.

Improves development focus

The MVP development model allows developers to focus on the development of core functionality first, followed by the development of additional functionality. This is a much more efficient way of developing a product than attempting to develop many aspects of functionality simultaneously. It allows the focussed use of resources on fewer aspects of the app, which ensures that each element of an app is completed to the highest specification.

It allows a product to evolve

Evolution has created some of the most complex and efficient systems on the earth, so why not let a product evolve too? What begins as an MVP can evolve naturally, through end-user feedback, and refinement via subsequent development iterations.

The Wisdom of the Aezion Inc. 30 Days MVP Development Model

The 30 Day MVP model does not doggedly insist that any product can be delivered as an MVP in 30 days. Instead, it recognizes, and leverages, the realization that the 30-day constraint (when applied with carefully crafted and optimized facilitation, design, planning, development, and usability testing techniques) can sharpen focus and improve project and custom software development process efficiency.

These efficiencies accrue as a result of the following:

Greater focus: A 30 days development constraint can further sharpen the focus by forcing prioritization and squeezing out all but the essential aspects of the app idea.

More efficient project structure: In contrast to conventional agile MVP processes, the Aezion Inc. approach defines and validates the entire multi-sprint MVP deliverable at the outset during week 1. This process eliminates the uncertainty often associated with open-ended agile processes and provides the dev team with a highly actionable solution definition that can be implemented sequentially by one team or in parallel by multiple sub-teams to meet the desired timeline.

We concede that our 30-Day MVP Model is unusual and is not suited to everyone and every software project; but if our approach resonates with you or whets your appetite, please schedule an appointment to discuss your app requirements.

Why Mobile User Experience UI/UX Design Matters

Mobile User Experience UI/UX Design Why It Matters

When designing a digital presence, whether it is a website or a mobile app, attractive graphics and engaging content are not the only things that matter. One aspect of the web and app design that many designers still overlook is the need for good user experience design. But, what exactly is user experience design (UX Design), and why does it matter so much? Here’s why every business must think about the user experience when they design websites and apps.

What User Experience Design Is

User experience design is often used to describe the usability of an application or the user interface. The true meaning of UX design, though, goes far beyond that. UX design encompasses the entire process of software design and development. It includes branding, functionality, design, integration, and usability. UX designers look beyond simply creating usable products. They also consider the user’s pleasure and enjoyment in acquiring and using the product. UX design is the process of creating applications that are relevant and meaningful. Applications that users want to use. So, how can UX design benefit a business?

UX Design Encourages Use Interaction

Creating content is not enough. You need to create content that people will want to interact with. That includes written content, images, advertisements and calls to action. UX design includes techniques that encourage user interaction. These techniques include producing content that will appeal to the target audience. It also includes personalization features, such as “You may also like” types of functions. A UX designer will also be looking at consistency throughout an app or site. Software that is predictable and comfortable to use is software that people will want to use. 

UX Design Generates Loyalty

UX design creates customer loyalty through great experiences. An easy to use app or website backed by great service will encourage a user to use the then again. To do this, a UX designer will create a customer journey map (CJM). This maps a user’s entire journey through the site or app. This journey will be thoroughly tested to ensure that a user’s interaction with the product is as smooth and trouble-free as possible. It’s putting the design team in the shoes of the user. 

UX Design Generates Recommendations

The good UX design encourages word of mouth recommendations. The ease of use of a well-designed site or application and the usefulness of it will encourage people to tell others about the product. A part of UX design is to make sharing easy. A free recommendation from a user is far more powerful than a paid-for advertisement.

UX Design Reduces Development Costs

UX design keeps a project within budget and reduces development costs. UX design includes extensive user research, prototyping, and usability testing. This ensures that development time is targeted on the areas of functionality that matter. This focused approach means better initial design specs, less risk of feature creep, and more relevant content. It greatly recuses the need for last-minute redesigns and enhancements.

UX Design Reduces Internal Costs

UX design is end-user focussed from the outset. That concentrates design and development effort on what users want, not on what developers think they want. As well as saving money on development costs, UX design stops businesses from wasting internal resources. For example, UX design will help identify the products that people want. This would allow sales and marketing efforts to be focussed on profitable products, rather than the less profitable ones. It also reduces support costs by reducing the need for manual intervention.

UX Design Increases Profits

UX design can have a direct impact on the bottom line. It has been proven that 75% of people judge an app or website on its aesthetic design.  People are more likely to buy from a well-designed website or app than they are from an unappealing one.

The easier a site or app is to use; the more people will use it. That is true for the entire journey that a user takes through the app or website. From how fast the screens and pages load, to how easy it is to sign up for an account and place an order. If all the steps are easy, a user is more likely to progress to the final step of making a purchase or completing a desired action.

UX design seeks to reduce the number of user interactions to a minimum. It also guides the user through processes with clear calls to action. The overall effect of UX design is increased revenues, reduced costs, and improved customer satisfaction.

Historically, websites and mobile apps have been developed with the needs of the business in mind. UX design is reversing that trend and putting the needs of the user first. Consumers are becoming more and more experience-driven. Global online spending is increasing at a phenomenal rate. Businesses that don’t adopt UX design principals may soon find themselves trailing far behind the competition that does. Benefits of the web-based system.

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9 Essential Features of Successful Mobile Applications

Features of Successful Mobile Applications

With almost 4 million mobile apps available for download on Google Play alone, it can be difficult to see how you can develop a business mobile app that will stand out. However, as adults spend an average of nearly 4 hours a day using them, mobile apps are not something that a modern business can ignore.

A mobile application is a software application designed to run on smartphones, tablets, or other mobile devices. Mobile apps are usually developed in one of the programming languages like HTML5, Swift, or Java. They can be downloaded from app stores or accessed through links that are provided by the developer.

Mobile applications are different from normal applications as they have to be able to operate independently without relying on installation on a desktop computer. Moreover, they have to be compatible with multiple platforms and form factors.

There are many aspects of a mobile app that will determine its success. But, if you get the core principles right, it will go a long way towards making your app an app that people want to use. Here are the key features that any mobile app will need if it is to be a success.

1. Successful Mobile Apps Satisfy a Need

Any type of product needs to satisfy a need. When you are designing a business mobile app, you should not simply copy what your competitors are doing. You should think outside the box and think big. A successful mobile app is one that solves a problem for its users better than any other solution. It is an application that makes a user’s life simpler. 

2. Simplicity

While people are spending more and more time on mobile apps, the amount of time they are willing to spend on any one app is very limited. For that reason, an app must be easy to access and easy to use. Content and functionality need to be available with a minimum of user interaction. A key design feature of a good mobile app is effortless simplicity.

3. Customization

Allow the users of your mobile app to customize the app the way they want it. That can be as simple as giving them control over the fonts and the colors. Or, it could be allowing users to save their own favorites. Customization gives the user a sense of ownership. Once they have the app the way that they like it, they will be less willing to switch to using a competitor’s app.

4. Performance

Speed is of the essence with mobile apps. Mobile app users are often multi-tasking. So, if an app takes too long to load or to perform a function, users will switch off and do something else instead. Performance testing will be part of the development cycle for a mobile app. However, ongoing performance testing will also be needed to ensure that changes to the app do not cause any performance issues.

5. Develop for Android and iOS

It is important to develop mobile apps for both Android and iOS. These are the two most popular platforms. This can be achieved by developing the app in a cross-platform development framework, like Xamarin. Cross-platform development tools reduce the total cost of development and make your app available to a wider audience.

6. Social Integration

Social media integration is a must for most types of mobile apps. For simplicity, you can allow users to sign in with Twitter or Facebook. Users love to share their experiences too. So, allow users to share posts or purchases easily. It improves the user experience, and it can be a valuable form of marketing.

7. Feedback

Make it easy for users to leave feedback. It creates a sense of involvement and it shows that your business listens to its customers. It should be simple for a user to leave reviews and comments. You should also encourage comments about the functionality of the app. It will help you to improve your services and it will help with the future direction of the app.

8. Security

Recent well-publicized online breaches of confidentiality have made app security even more important. It is a fundamental requirement of any mobile app that users’ private data remains confidential. It is also important that the users know that robust security is in place. So, make sure that the app’s confidentiality statement is easy to locate.

9. Offline Functionality

It is natural that most apps will require an internet connection to work fully. However, there should be some features that will work off-line as well. If an app can offer even limited functionality offline, it could represent a major advantage.

Upgrades and Support

A business mobile app will need ongoing development and support. That will be both in terms of fixing bugs, and in terms of ongoing software enhancements. An app needs to be kept fresh and relevant. If a mobile app stagnates, users may become bored and switch to a more modern app.

The way that people access the internet is changing. Mobile device access to the internet has already surpassed desktop access. Today, businesses, large and small, need to develop mobile apps if they are going to stay ahead of their competitors. Developing an app for the sake of an app, though, will be counterproductive. Mobile apps of the future will need to connect with and engage customers. They will need to be easy to use, relevant, and they will need to fulfill a need.

When you’re ready to consider a mobile app for your business, choose a development partner like  Aezion Inc. The platform, mobile application development experience.

Python Programming For Data Science and Machine Learning

Python is a general-purpose, high-level, object-oriented, and easy to learn programming language. It was created by Guido van Rossum, who is known as the godfather of “Python”.

                         

Python is a popular programming language because of its simplicity, ease of use, open-source licensing and accessibility — the foundation of its renowned community which provides great support and help in creating tons of packages, tutorials, and sample programs.

Python can be used to develop a wide variety of applications — ranging from Web, Desktop GUI based programs/applications to science and mathematics programs, and Machine learning and other big data computing systems.

Let’s explore the use of Python in Machine Learning, Data Science and Data Engineering.

Machine Learning

Machine learning is a relatively new and evolving system development paradigm that has quickly become a mandatory requirement for companies and programmers to understand and use. See our previous article on Machine Learning for the background. Due to the complex, scientific computing nature of machine learning applications, Python is considered the most suitable programming language. This is because of its extensive and mature collection of mathematics and statistics libraries, extensibility, ease of use and wide adoption within the scientific community. As a result, Python has become the recommended programming language for machine learning systems development.

Data Science

Data science combines cutting edge computer and storage technologies with data representation and transformation algorithms and scientific methodology to develop solutions for a variety of complex data analysis problems encompassing raw and structured data in any format. A Data Scientist possesses knowledge of solutions to various classes of data-oriented problems. And expertise in applying the necessary algorithms, statistics, and mathematic models, to create the required solutions. Python is recognized among the most effective and popular tools for solving data science-related problems.

Data Engineering

Data Engineers build the foundations for Data Science and Machine Learning systems and solutions. Data Engineers are technology experts who start with the requirements identified by the data scientist. These requirements drive the development of data platforms that leverage complex data extraction, loading, and transformation to deliver structured datasets that allow the Data Scientist to focus on solving the business problem. Again, Python is an essential tool in the Data Engineer’s Toolbox — one that is used every day to architect and operate the big data infrastructure that is leveraged by the data scientist.

Use cases for Python, Data Science and Machine Learning

Here are some example Data Science and Machine Learning applications that leverage Python.

• Netflix uses data science too, to understand user viewing patterns and behavioral drivers. This, in turn, helps Netflix too, understand user likes/dislikes and predict and suggest relevant items to view.
• Amazon, Walmart, and Target are heavily using data science, data mining and machine learning to understand the user's preferences and shopping behavior. This assists in predicting demands to drive inventory management and to suggest relevant products to online users or via email marketing.
• Spotify uses data science and machine learning to make music recommendations to its users.
• Spam programs are making use of data science and machine learning algorithm(s) to detect and prevent spam emails.  

This article provides an overview of Python and its application to Data Science and Machine Learning and why it is important.

 Aezion Inc. Solution Architects, Engineers, and Custom Software Developers can assist you in exploring Python-based solutions for your Data Science and Machine Learning applications. Contact us to learn more.