5 Ways post COVID-19 retail would be modern and digital

The world is in the chokehold of the COVID-19 pandemic. People are trying to stay indoors as much as possible. Digital socialization is the only form of social life existing for now. Bars, restaurants, and touristic destinations are closed and empty. All this has hugely impacted the buying preference of people worldwide, and the retail sector is witnessing a significant shift in customer behavior. Retailers are facing multiple challenges around the labor force, supply chain, cash flow, consumer demand, marketing, health, and safety.

digital

Successfully tackling all these issues will not only resolve short-term challenges but also ensure a modernized future for the retail industry. Post COVID-19 world will be a digitally transformed era. Here is a list of technologies and transformations that the retail industry must go through not just to beat the impact of this pandemic but come out of it victoriously:

Artificial Intelligence will help customers find products faster

Artificial Intelligence (AI) makes machines smarter by teaching them via experience. It provides an opportunity for the in-store retail industry to bridge the gap between virtual and physical market. For the enhancement of customer experience and increasing sales, retailers are altering in-store environment. Tools that can help customers in finding the right product and deal easily and promptly, are being created with the help of AI. Customers will be able to enter their shopping list in the device and be prompted about the exact location of each product.

Visual Search is another similar application of AI. For visual search, shoppers use real-world images (downloaded images via internet, screenshots, or photographs) to find something similar. With AI & ML, it becomes possible to understand the context and content of these images and respond with a list of related results. It is a valuable tool for retailers, especially in home décor and fashion sector. Many retailers like ASOS, IKEA, Neiman, Marks & Spencer, etc. have already adopted this technology.

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Predictive Analytics – To make smarter business decisions

Predictive analytics can uncover behavior trends by crunching customer data. It is one of the most sought-after technologies for retail digital transformation. Shifting customer preference during COVID-19 has made it even more valuable. The ability to predict customer needs over the coming months is now more important than ever to manage inventory and supply chain. With an abundance of data everywhere, it is only wise to use it to analyze the following factors: 

  • Customer shopping journey – Using data to draw a typical customer shopping journey can help retailers in personalizing the consumer experience at each stage of the decision-making process. It can be used to improve sales and reduce cart abandonment. 
  • Customer behavior – It can help retailers in creating tailored customer loyalty programs. With this analysis, retailers can create personalized offers and deals.
  • Inventory reporting and purchasing patterns – This will help retailers in improving their replenishment strategies and boost customer satisfaction.

Augmented and Virtual Reality will help buyers feel and experience products before they buy

People want to try before they can buy. The contagious Coronavirus has made it difficult for people to try on things confidently. AR and VR are can help buyers experience a product before buying.

The automotive industry is applying this technology effectively and some brands have already started using it to give test drives to potential customers without actually driving the vehicle.

Loreal is another brand that has used AR & VR to allow buyers to see how a product might look and feel in real life. Shoppers would have the option to try and select apparels without touching them. This will help in maintaining hygiene and safety for all. In the near future, AR & VR are going to be as common as trial rooms in apparel stores. 

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IoT Devices to streamline retail operations

The retail industry can use IoT devices to automate procedures and streamline operations. Robot employees are also one of the options retailers are eyeing during COVID-19. 

As per Statista, the forecast suggests that by 2030 around 50 billion of these IoT devices will be in use around the world, creating a massive web of interconnected devices.

Mobile apps to enable cashier-less stores

Mobile app utilize different digital technologies to transform the retail industry:

Cashier-less stores Digital financial transaction via e-wallets has become a norm. This can further be applied to retail stores. Shoppers can use a mobile app to make payments at the stores. It is one of the safest ways to reduce touchpoints while shopping. It instils confidence in the buyer and makes their shopping experience safer, faster, and frictionless. A lot of retail stores are already using mobile apps for maintaining social distancing.

Chatbots People are trying to minimize physical human interaction for safety reasons. With limited staff and most of the people on work from home, many retailers are offering chatbot support to their clients. A chatbot is a smart way to continue serving your customers, answering their queries, and providing the required assistance. It is an easy and preferred way to interact. Many retailers are also using it to inform shoppers about product availability, offers, and deals using chatbots. 

Conclusion

Evolve or die. This common catchphrase captures what has become the number one rule for modern retail. Only those who survive this crisis will be able to thrive in the future. Adoption and implementation of these digital technologies can make it easier for retailers to run their day-to-day activities and make smarter business choices, not only during COVID-19 outbreak but also in the future.

How to begin learning Android App Development?

Learn Android App development seems to be the go-to mantra for quick career growth and big earnings. Android app development has become quite mainstream these days. It has been growing ever since the first full-fledged smartphone was released way back in 2007. To say that the app development industry is the future of software development, wouldn’t be an understatement.

Android App

With more and more people using smartphones these days, app development has seen a big surge in the demand for applications. To capitalize on this chance, many companies have started to develop apps all around the world.

Android app development has huge market scope, considering Android is one of the most widely used OS in smartphones these days. It occupies a huge market share, thanks to the strong backing by Google and mobile companies using it as their primary OS.

App development has many benefits that will help you in your career growth. Some of these benefits are mentioned below:

  1. Higher Income– App development provides a great opportunity for those who want to make good money. According to Payscale, the average salary of an entry-level Android developer in the United States is $98000. It is quite a huge competitive amount, if you compare it with other developments or other domains. Therefore, it is a good option to consider getting into, for those who want to make a good amount of money.
  2. Revenue Generated– This is no hidden truth, that apps are a great source of capital. Google Play Store gives you a great chance to sell your app. The number of downloads and ads you run on it determines the net revenue of the app. According to latest statistics, the revenue generated by apps on Google Store and Apple Store was $51 million and $84 million respectively.
  3. Freelancing– One of the biggest benefits of app development is the ability to do freelancing. You can easily work for yourself as per your need and convenience. Furthermore, one can work from the comforts of your home without actually going to the workplace/office.
  4. Better ROI– This is no hidden fact that apps offer great options to make money. Not only this, apps also offer a great return on the investment made during its development. According to a study done by Facebook and AppsFlyer, the ROI of apps varies as low as $1.7 per user for gaming apps to around $13.9 per user for shopping apps.
  5. Good Job Opportunities– As already discussed, the demand for app development is very high at this point in time. Therefore, companies are actively looking to hire app developers who can develop apps for them. In other words, there could be no period as perfect to learn android app development as now.
  6. Flexible Working Hours– As a developer, you don’t need to bind yourself to a fixed working schedule. You can work according to your availability. You can work more or less on any day given the demand for the work.

But one question bothers most of us- How to begin Android development? It becomes a big problem when you have no prior knowledge of coding, i.e starting from scratch.

To ease out your android learning journey, we are presenting the resources and steps you could use for learning android app development without any problem.

For better understanding, let us read a little about app development-

What is App Development?

Application software developers also must consider a long array of screen sizes, hardware specifications, and configurations because of intense competition in mobile software and changes within each of the platforms. Mobile app development has been steadily growing, in revenues and jobs created.

Basically, app development is mostly done for the two dominant Operating Systems-

  • Android
  • Apple

Since this article is mainly focusing on Android, we would discuss the resources for app development in Android here-

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What is Android App Development

Android app development is basically the development of apps for the Android Operating System. Apps in Android are written using programming languages like Kotlin, Java, and C++.

Some programming languages and tools allow cross-platform app support (i.e. for both Android and iOS). Third-party tools, development environments, and language support have also continued to evolve and expand since the initial SDK was released in 2008. In addition, with major business entities like Walmart, Amazon, and Bank of America eyeing to engage and sell through mobiles, mobile application development is witnessing a transformation.

App Development in Android

For developing apps in Android, there are certain tools to perform these development tasks. These tools are-

  1. Android SDK– It is the Software Development Kit used to develop apps in Android. It comes fully stocked with libraries and resources you would require. It also provides additional developer tools used for debugging, compiling, and much more. To try out SDK, you would need to download it from Google’s official website.
  2. Android Studio– The most important element required for the development of any software is an Integrated Development Environment(IDE). An IDE enables you to write a computer code into it. It increases the productivity of the developer by combining multiple activities like debugging and writing code into a single entity. As Android Studio is the official IDE, it includes the SDK, an emulator, image files, and many more.

Now that we have discussed the main components of Android app development, let us see how we begin learning android app development.

How to Learn Android app development?

App development in Android isn’t very difficult. It requires complete attention to the topic. In this segment, we are going to discuss a simple tutorial, to begin with as well as some good courses that you can use as a reference to learn it.

For starters, let us begin by mentioning the best courses to learn android development at present. There may be some courses that may have been left out but most of them have been mentioned here.

  1. The Complete Android N/Oreo Developer Course– This course has been designed by Rob Percival and Marc Stock, who are considered the masters when it comes to Android development. More than 62000 people have taken this course and it has been given a rating of 4.6 out of 5 by 9100 users. The course will teach you to build a clone of apps like Uber and Twitter. This course will help you learn about Android development using Android Nougat.
  2. Kotlin for Android- Beginner to Masterclass– This course is primarily focused on teaching you how to build professional, fully-functional apps using Kotlin and how to submit them to the App Store. The trainer, Mark Price has taught over 230000 people and helps to transform people into professionals.
  3. Android Java Masterclass: Become an app developer– This is a great course for those who want to become experts in Android. As the name suggests, it teaches Android through Java, giving an opportunity to those who don’t know much about it. It covers all the topics to guide you through it. Over 300000+ students have taken this course and it enjoys a good rating of 4.6.
  4. Android Fundamentals: Ultimate tutorial for app development– This is a great course available at Udemy for free that covers all important parts of android. It begins by describing the architecture and simple APIs and then moving to complex parts like sensors and data storage. All in all, a good package for those who want to understand it.
  5. Learn Android application development– This is a comprehensive and free course when you compare it with other free courses. It will teach you Java in brief and help you in setting up the environment for development. You will also learn fundamental concepts of Android like Explicit and Implicit Intents, how to use Fragments, and many more.
  6. Become an Android developer from scratch– This is one of the most popular courses on Udemy. with over 340000 people who have enrolled in it. This course will teach you how to set up your environment and create, run, and debug the application on both emulators and devices.

The courses mentioned are for those who have time to give and don’t have in-depth knowledge of Android. For those who have a basic idea but don’t know how to start developing, we have prepared a short tutorial that might help you.

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Step 1: Download Android Studio

When you are programming in any language, you will require an entity for writing code and perform various functions. It is known as the IDE. Android Studio is the most preferred IDE for development in android.

Android Studio is mostly preferred because it is designed specifically for Android development. This means that it’s full of Softwares like Android SDK and Android Virtual Device, which can be used to test your apps.

Step 2: Setting up Android Studio

For setting up the IDE, you would need to download Java to use it. Similarly, you’re going to need to install the Java Development Kit (JDK) as the app programming is done in Java. After doing all the things mentioned, open Android Studio. Once it opens up, you’ll see a menu where you’ll be able to start the project or configure some options.

So, there are basically three things interacting when you use Android Studio to create apps-

  1. Android Studio itself, which is used for writing the codes for your app.
  2. The code you write in Java,.
  3. And the Android SDK which you’ll access through your Java code in order to do Android-type things

Step 3: Starting a new project

Once you’ve installed all your components, go back to the page you see when you open Android Studio. Now, choose Starting a New Android Studio Project. Enter the name you want for your application and your ‘company domain’. It will be something like this: com.companyname.appname.

The package will be the compiled file or APK (‘Android Package File’) that you can upload on the Google Play Store.

The last field to enter is the directory where you want to save all the files related to your app. The next step is to determine for what type of device you are going to develop your app. For starting, you can go with Mobile or Tablet.

This is what your page would look like. Since this would be your first attempt at building an app, let us keep it as simple as possible. Select ‘Basic Activity’ to keep things simple. Next, you will need to select a name and layout for your app.

The layout name meanwhile describes a file that determines the layout of an activity. This is a separate piece of code that runs in concert with the main activity code to define where elements like images and menus go and what fonts you’ll use.

And with that, you’ve mastered the basics of app development in Android. Pick a good front page and name and you’ve built your first app.

Conclusion

To learn android app development for career growth and big salaries is very trendy these days. There are a lot of job opportunities for developers with companies ready to pay for the quality. So it is understandable that many people are going towards this field. But to grab this opportunity with both hands, you need to learn android app development.

Comparing Top IoT Development Platforms

Platforms Before making any comparison, we should figure out why it’s a good idea to use an IoT platform on your project in the first place. Here are several benefits that most platforms provide.

Platforms

Many IoT platforms offer fully-managed services, which means they scale up on demand and are self-maintained. You won’t need to bother how your system will adapt to the growing number of devices or data volume. As a rule, these platforms have robust resources and can either perform standard patching and upgrading on their side or provide you with services for easy over-the-air updates.

Inbuilt security

Security has always been one of the biggest challenges in IoT development. Remember the case in Las Vegas casino when hackers used a connected fish tank to get access and steal 10G of confidential data? Low-level sensor devices based on simple IoT development boards can be a weak point in an IoT system and pose a real threat to the integrity of the whole system. Therefore, overall multiple-step security is crucial. However, to implement and maintain healthy security practices over a multi-component system is not so easy.

IoT development platforms offer packaged security solutions for every layer of a system thus lifting a serious weight off the developer’s shoulders.

Convenience and simplicity

Usually, major IoT platforms like the ones we will be talking about have all the services you need in one place, from bringing your network of devices online to handling ML-based data analytics. Some providers even offer prebuilt templates for standard IoT applications, plenty of guides and developer tools as well as open-access libraries.

Cost-efficiency

Often, IoT platform services are paid depending on the number of devices, messages, the volume of data processed, etc. This granular pricing model helps avoid overpaying, goes without flat fees or upfront cost. In the end, customers pay only for the services they use. Also, many platforms offer free trials and multiple free tier options to let you get a hand of some services and figure out if you want to stay or go on shopping around.

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Best Development Platforms for IoT

Earlier, we have reviewed three best development platforms for IoT in detail – AWS IoT platformMicrosoft Azure IoT and Google Cloud IoT. You can check every review following the given links. Now, let’s put them side by side and see what each of the platforms offers for every part of IoT system development.

To connect and manage devices

One of the leading cloud providers, Amazon offers several dedicated services to connect, configure, manage and secure IoT devices. AWS IoT Core is a major service that helps connect billions of devices with each other and to the cloud and enables two-way data communication. To manage a large fleet of devices, you can use AWS IoT Device Management. This service simplifies device onboarding, monitoring and maintenance. In turn, AWS IoT Device Defender provides security and helps detect abnormalities in device behavior and address issues in time.

Azure IoT Central acts as a core service of the IoT platform from Microsoft. This service is enough to build an IoT application for a common use case, and even provides a set of templates for easy setup. Unlike AWS IoT Core, it already includes device monitoring and management tools. If you combine it with Azure IoT Hub, you can build more complex IoT applications that extend to billions of devices. You can implement a custom data infrastructure channeling metrics to different Azure services and returning commands to your fleet of devices.

To enable edge intelligence

Each of IoT software platforms provides services to enable edge intelligence given its growing importance and applications in IoT systems.

Amazon IoT Greengrass is exactly this kind of service. It allows programming local computing devices like gateways to process sensor data on the edge and send commands to act on this data immediately.

Azure IoT Edge performs similar functions in Azure-based systems and helps move part of data processing to edge Windows and Linux devices.

By the way, both Amazon IoT Greengrass and Azure IoT Edge allow running trained ML models locally. However, possibly, the most powerful offering for adding machine intelligence to the edge comes from Google.

Google offers a combo of Edge TPU chip and Cloud IoT Edge software that allows running ML models locally super-fast, super-efficiently, and adds an extra layer of security for connecting edge devices to the cloud.

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To use cloud services

Probably, the best part of comparing IoT development platforms is exploring their vast capabilities for IoT data analytics, visualization and management.

For these purposes, AWS IoT provides a set of tools including:

  • powerful AWS IoT Analytics for preparing data and implementing different analytics and visualizations practices;
  • AWS IoT SiteWise tool for industrial IoT applications focused on working with heterogeneous equipment data;
  • AWS IoT Events service to define events and efficiently act on them.

Azure Times Series Insights is a complex of data analytics and visualization tools from Microsoft. Initially, it filters and prepares IoT data depending on its purpose. When prepped, the data can be used for analytics and building custom visualizations or redirected to other services, for example, Azure Machine Learning. Azure Times Series Insights can also be integrated with Power BI which is convenient for the many companies that already use this service.

Google Cloud IoT provides a range of its own services for data analytics and visualization. Among them are:

  • Cloud Functions to configure devices to act on certain events;
  • Dataflow to process streaming data in real-time;
  • BigTable to store large huge volume of data;
  • BigQuery to quickly pull out data insights;
  • DataStudio to visualize data insights pulled out from BigQuery data warehouse;
  • DataLab to develop custom data analytics practices and visualizations.

Perks

It would be hard to compare the major IoT development platforms when all of them basically cover all bases and provide similar services. However, there’re always some perks that define certain benefits of each platform.

AWS IoT Platform

In the case of AWS IoT, it would be the simplicity of building a standard IoT application and integrating it into an existing business process. One of the platform’s services is a drag-and-drop tool for building IoT applications – AWS IoT Things Graph. It offers a convenient interface to connect and configure devices and different web services. On top of that, it has a range of prebuilt models for popular applications like agricultural software for soil monitoring, etc.

How to Manage A Project: Closing Out a Project

You’ve built the deliverable, hit all milestones, and ensured the product meets your organization’s quality standards across the board – but you’re not done yet. While it may seem as though everything was taken care of at the end of the execution phase, formally closing out a project involves several procedural yet essential steps in concluding the project management process; there are still some important loose ends to tie up yet.

Project

Secure Approvals And Transfer Deliverables
Now is the time to finalize your project deliverables, and ensure that all stakeholders and clients sign off on the final product. This eliminates any potential concerns or debate moving forward by identifying any subsequent changes as change requests outside the original budget or timeline. This is especially valuable when reviewing scope, and in helping to avoid the dreaded scope creep. With that confirmed, you can safely hand-off all officially completed deliverables to the customer.

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Settle All Finances And Invoices
When it comes to payment, keep it prompt. Maintaining positive client relationships is much easier when you proactively communicate on costs to ensure all your WIP and unbilled hours have been accounted for. Now is the time to finalize any additional payments, discounting, and unpaid invoices to close out the customer’s revenue stream and make sure you get paid for all the moving parts.

Release And Reallocate Resources
With the project finally delivered, you can now formally release your resources, including vendors, team members, and contractors to free up their schedules for other work. Keep in mind that paying off contractors quickly will work in your favor by accounting for actual project costs, metrics, and margins sooner rather than later. Simplify the process by utilizing a solid project & resource management software that tracks resource availability and allows for easy removal from the now completed project. Doing so helps to confirm accurate payment amounts and serves as a final check for any remaining obligations.

That said, it’s not too early to start thinking about where else your resources might be needed. Chances are good that other projects in your organization are ongoing or in the planning stages, and could benefit from some help. Consider each of your team members’ specific skills and when and where it might make sense to transition them afterwards.

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Conduct A Post-mortem Session
A post-mortem (also referred to as a retrospective or review) is a helpful post-project team briefing that identifies and documents lessons learned throughout the project’s lifecycle. Together, you can review successes, failures, oversights, challenges, and more to identify possible areas of improvement. Gather feedback from stakeholders and team members for a thorough record of what worked and what didn’t – the purpose here is not to assign blame, but to continuously strengthen workflows, cost-effectiveness, quality, and more for subsequent projects. Referencing the gathered data in reports and analytics from the project will be helpful in this discussion. Some of the questions you might ask:

  • Did we stay on budget?
  • How well did we communicate and collaborate?
  • Were available skill sets and resource allocations sufficient for each phase?
  • Was the client satisfied with the final product?
  • What worked well, and what could we improve moving forward?

Archive Project Documentation
The work may be completed, but don’t ditch those documents! They can be used for valuable insight and implementation on projects in the future, as well as providing security for any potential inquiries. Gather all the documentation your project generated from start to finish – such as business requirements, plans, financial documents, contracts, agreements, and other materials – and arrange for them to be stored or indexed for safekeeping in your system. Always ensure a thorough record is kept. Consider a cloud-based project platform for easy document collection and management.

Plan Your Next Steps    
Now that you have a little breathing room, consider checking in with your current clients to see what other projects might be in the pipeline. If your latest project experience struggled to meet any requirements, look into arranging training or other services to keep your project resources in tip-top shape. You may need to make some fast hiring or contracting decisions if you find yourself lacking an urgently needed skill set.

Fundamentals of Web Application Architecture

The web application architecture contains many components and exterior applications. To have better quality and outstanding application which completed to changed frontend and backend methods. A web application is a normal computer application, web application works over the internet.

Architecture

As everybody is on the web these days, most developers are looking to advantage from web apps and attract as many users as possible via opportune offerings.

What is Web Application?

It is a client-server computer program anywhere the user runs on the browser that contains the user interface and client-side logic. This web application has ordinary webmail, online trade, and online auction.

Components of Web Application Architecture

Web Application Architectures contains various components that are segregated into two categories of components – user interface app components and fundamental components.

User Interface App Components

This is an orientation to the web pages that have a role that is connected to the display, settings, and alignments. It is associated with the interface/experience, rather than the improvement, and consequently, it deals with display consoles, configuration settings, notifications, and logs, etc.

Structural Components

The structural components of a web application essentially refer to the functionality of the web application with which a user interrelates, the control and the database storage. In other words, it has got additional to do with the structural features of the architecture, as the name proposes.

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Component Models of Web Application

One Web Server, One Database

It is the simplest as well as the minimum consistent web app component model. Such a model customs a single server as well as a single database. A web application develops on such a model will go slow as soon as the server goes down. Hence, it isn’t much consistent.

Multiple Web Server, One Database

In this type, the server does not save any data in the database. When the client comes in the data to the web server, it will process the similar data and then inscribes it to the database that is kept outside of the server. In this method two servers used in the component model. in case one web server goes down another server will take over the control immediately. All the requirements will be redirected automatically to the new server and the web app will remain execution. Hence consistency is better equated to a single database model.

Multiple Databases, Multiple Web Server

It is the most effective web application architecture model for neither the webservers nor the databases have a single point of disappointment. There are two choices for this type of model. Either to save identical data in all the working databases or allot it evenly among them.

How Does It Work?

With any distinctive web application, there are two different encryptions (sub-programs) running side-by-side. These are:

– Client-side Code

– Server-side Code

When creating an app, web developers decide what code is used for the server about what code is used on the browser. Server-side languages are:

Any code that can reply to HTTP requests that can be run on a server. Client-side languages are:

A grouping of HTML, CSS, and JavaScript is used to create the client-side code. This code is analyzed by the web browser. Unlike the server-side code, client-side code can be seen as well as altered by the user. It responds to the user request. The client-side code connects only via HTTP requests and is not able to read files of a server directly.

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Types of Web Server Architecture

Node.Js Web Application Architecture

Node.js framework is progressively increasing due to its effectiveness in the development process. This web application framework architecture could deal with different requirements regarding design and structure. Node.js is Java-based web architecture with the different frontend technological elements that shorten the work of web developers. Web developers maintain the frontend services also backend services. Web application architecture designs source code distribution and reusability, basic knowledge-exchange that assurance reliability and diversity in the available tools.

PHP Web Application Architecture

PHP The tools and topographies offered by PHP frameworks allow for less code and assurance of strong protection, prompt development, simple operation, and enhanced support from the developer community.

Python Web Application Architecture

Python features compressed, legible, and supporting code. Python contributes to the improved web application speed and is exempt from app conservation. Additionally, it is extremely supple and well-integrated with other languages.

Ruby on Rails Web Application Architecture

Ruby on Rails Web Application Development is well-known as the comparatively simple framework to apply. This model offers services for web design. The main goal line to reach efficiency is to the ability to remember that convention always goes before conformation. It delivers developers with good speed settings for finishing specific tasks.

Angular Js Web Application Architecture

Angular js is a framework that carries a variety of advantages, with UX with the lazy charging effect added to minimalize code size.

Java Web Application Architecture

It has typically been a beloved in the early development environment due to its flexibility. Currently, Java is the undoubted top-player among the most favored programming languages. The complex of a web application architecture completely depends on the requirements of the chosen solution. Whether it’s a simple, educational web application or a robust, multi-tiered web application, Java Web Application Architecture technologies can help achieve successful results.

Laravel Web Development

Laravel is a PHP web development framework that uses on the model view supervisor architectural design and has at its core syntax that is sensitive, creative and sophisticated. It offers a simplified web development process from side to side better routing, sessions, verification, and caching; as a result, it takes smaller time for completing projects.

Cloud-Based Web Application Architecture

The migration to the cloud is more of an imperative than a select, mainly as a result of the benefits across all limitations. Subsequently, cloud-based web application architecture has been established, this has resulted in the creation of a corollary – the decoupling of data. In other words, cloud-based apps function and store information on local servers and the cloud.

Types of Web Application Architecture

– Single-page applications

– Microservices

– Serverless architecture

Conclusion

The web applications are evolving incessantly like the internet. The first web application architecture was web 2.0. The latest web application architecture was web 3.0 which increased a lot of users. The model and type of web application development architecture describe the toughness, sensitivity, security and several more features.

Understanding Big Data Analytics In Less Than 10 Minutes!

Analytics Have you ever wondered what exactly the difference between data and big data is? Both are collections of information, right? While that is true, a unique identifier for big data is its large volume. Big data is often used by businesses for obtaining customer insight. Such datasets are so extensive that traditional software like MS Excel is not agile enough to handle them anymore.

Analytics

Not long ago, businesses were using traditional database methods to store quantitative information on spreadsheets like Excel; a program using grids, tables, and columns to organize the storage of data. Little did we know that the gradual inflow of data would accelerate at such a high speed that we would find ourselves in an explosion of information. It was around that time that we realized that the traditional data management systems were no longer capable of processing such massive volumes of information.

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The 3Vs That Define Big Data

Volume, Velocity, and Variety are the 3Vs that best define what big data stands for.

Volume

Whether or not a dataset is considered to be big data depends entirely on the volume of the information. Hence, this is the most important V defining big data. It is a simple rule: any information that is massive in volume is big data. For example, according to Fortunly, there are around 1.5 billion WhatsApp users in 180 countries! Just imagine the huge volume of data being generated on a daily basis. As traditional data management can no longer take the burden of this colossal amount of information, we rely on new methods (like Hadoop) to store and analyse the information.

Velocity

In his recent letter to Amazon shareholders, Amazon CEO Jeff Bezos emphasized how “speed matters in business.” Velocity, which refers to the high speed at which data is received, helps businesses make the most timely decisions. Tesco, Sainsbury, and Marks & Spencer are some examples of retailers using big data analytics in retail and leisure industries.

If you were the owner of a retail business, your biggest concern would be to know which items go out of stock within minutes. For retail businesses, predictive analytics is practised on a large scale, which means they predict future consumer demand with present data available. Retailers can observe customer behaviour to predict what product should be stocked in future to meet the demand.

Variety

Big data always features different varieties of data. Social media alone has a diversified range of data, such as text messages, videos, audio files, pictures, and much more. When working with big data, it is important that you organise and structure the variety of information for later analysis.

Variety of data refers to two basic categories:

  • Structured Data: This can be easily defined and searched for by machine language. It is made up of quantitative information, e.g. name, address, telephone number, and billing information.
  • Unstructured Data:  It is unorganized in nature and is mostly text-based, e.g. emails, voicemail, ECG recordings, and business recordings.

Now that we know what big data is, it’s important to understand how big data and analytics integrate to extract value from the data. Before big data came into existence, businesses relied on basic data analytics, a traditional system to examine data for insights. With the cutting edge technology we have today, big data can be examined through big data analytics, a much faster way to draw out customer insights and behaviour patterns.

What Is Big Data Analytics?

A lot of people wonder what big data analytics is, and how it can be used to create value for their business. A simple definition of big data analytics is:

The process of examining big data for adopting appropriate business strategies and better decisions.

For example, if you were running an entertainment channel like YouTube, you would depend on big data and business analytics to answer some of the following questions:

  1. What kind of videos do viewers watch the most?
  2. How long is each video watched for?
  3. What are the viewer’s preferences?
  4. Which celebrity video is watched more?

Once we are able to obtain the answers to these questions, we can combine the powers of big data and analytics, and adopt a business strategy that would help lay out our marketing goals.

To further comprehend big data analytics, let’s take a look at its three major aspects:

  • Sources of big data analytics
  • Top 5 big data analytics tools
  • Innovative ways companies are using big data

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Sources Of Big Data Analytics

Big data can be split into three wide categories on the basis of the three primary sources that it is obtained from.

1. Social Data

Social media has completely turned our lives around. Every click, tweet, and comment that we make is stored and used for the purpose of big data analytics.

Are you still wondering how that happens? Well, social data gives an insight into user behavior patterns through various social media sites. Big data is obtained through the monitoring of how a user engages through different media channels, including Google, Facebook, LinkedIn, Instagram, and many others.

2. Machine-Generated/Internet-Of-Things (IoT) Data

Machine data is composed of all the digital information that we get from software installed in devices such as road cameras, smartwatches, smart meters, and satellites. Let’s take the smartwatch, as an example. Smartwatches track an individual’s health data by monitoring their blood pressure, seizures, and steps walked on a daily basis. This data can then be used by doctors who can offer their patients with better diagnosis owing to the easy access to their consistent medical record.

3. Transactional Data:

For the owner of a retail shop, transactional data is no less than a treasure chest. A large volume of data is available to them, including:

  • Purchases and returns made by the customers through payment slips
  • Information about the services that customers are subscribed to
  • Invoices for recording all the sales transactions and orders placed by the consumer
  • Consumers’ personal information gathered through loyalty cards programs for better customer relations.

As surprising as it may sound, even a small incentive, such as a loyalty card, has a big role to play in the collection of big data. Customers are given discounts in exchange for their personal information, helping businesses to determine the consumer preferences for future planning.

While all sources of big data are important, the most widely used method in the modern world is social media. Hence, it would be unfair to go ahead without shedding some light on this relationship.

Technology in Financial Services: Analytics Stack Performance

Financial services organizations operate in a challenging environment. Their industry is one of the most regulated in the world, and their sites, services and applications serve a critical function within the global economy. New technology in financial services is constantly emerging, aimed at helping enterprises conduct their affairs smoothly, compliantly, and free from technical error.

Financial

What is Analytics Stack Performance?

Savvy companies keep abreast of the latest technology in financial services in an effort to keep up with competitors. Everyone wants their applications to be highly available and performance-optimized while generating investor and shareholder returns. Because data-driven analytics are key to the current and future competitiveness of financial services companies, most technology innovation in financial services is focussed on leveraging data to increase uptime and efficiency.

Analytics stack performance is a key example of new technology in financial services. Proactively monitoring the performance of your critical applications and services with big data analytics stack performance can help you avoid operational nightmares and enable you to find and fix application and infrastructure issues before they impact your organization.

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Seven Ways Analytics Stack Performance Helps Financial Services Companies

As a flexible piece of financial technology, analytics stack performance can refine and boost a range of financial services’ company goals:

    • Predicting the risk of churn for individual customers and recommending proactive retention strategies to improve customer loyalty.
    • Providing early warning predictions using liability analysis to recognize  potential exposures prior to default. As a new technology in financial services, analytics stack performance encourages proactive engagement with customers to manage their liabilities and limit exposure.
    • Predicting risk of loan delinquency and recommending proactive maintenance strategies by segmenting delinquent borrowers and identifying “self-cure” customers. A better functioning big data analytics engine enables financial institutions and banks to better tailor collection strategies and improve on-time payment rates.
    • Detecting financial crime such as fraud, money laundering, or counter-terrorism financing activities by pinpointing transaction anomalies or suspicious activities through big data analytics derived from transactional, customer, black-list, and geospatial data.
    • Predicting operational demand based on historical data and future events. Insights from analysis and projections of data allow banks to anticipate call center traffic volumes or predict demand for cash at ATMs.
    • Evaluating customer credit risk by analyzing application and customer data. With analytics stack performance, financial institutions can get better at automating real-time credit decisions based on information such as age, income, address, guarantor, loan size, job experience, rating, and transaction history.
    • Managing customer complaints by using information from various interaction channels helps financial institutions understand why customers complain, identify dissatisfied customers, and find the root causes of problems.
    • The applications and workloads that the Pepperdata analytics stack performance solution can optimize provides the “source of truth” that ultimately underlies a whole range of customer-facing, transactional use cases.

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Analytics Stack Performance = Scalability for Massive Deployments

Pepper data analytics stack performance solutions provide the scalability that makes them the choice of the world’s largest financial services organizations, with some customers running in excess of 1,000 nodes in their distributed computing environment.

Customers with high node counts face unique operational challenges while operating their financial technology, including extremely high numbers of concurrent queries. They cannot afford any service or data loss. To reduce risks associated with potential downtime and data loss, some organizations have established data centers with triple-redundancy cluster architectures.

Financial services organizations with such huge physical infrastructure investments naturally want to maximize their workloads and utilize their infrastructure as efficiently as possible. Pepperdata is a technology innovation in financial services that can create:

  • 90% capacity utilization without manual application tuning
  • Up to 50% improvement in throughput that results in significant savings in infrastructure spend
  • 95% reduction in MTTR, with an average 5,200 hours per year saved on triage and troubleshooting time

For example, a Fortune 100 financial services giant gained control over their runaway data infrastructure spend with the help of Pepper data analytics stack performance products. Learn more about how they did it by downloading the case study here.

Bridging the DevOps Communication Gap

Financial services companies using Pepperdata appreciate being able to bridge the communication gap that exists between developers and IT operations (a gap that can negatively impact application development and the production workloads).

Our new technology in financial services helps across the board. Using Pepperdata Application Spotlight, customers can readily monitor an application as it transitions through the development cycle—from pre-product to production. As the application evolves, issues like bottlenecks, CPU, and memory issues are quickly detected and resolved using Pepperdata Platform Spotlight and Capacity Optimizer to ensure optimal performance in the production environment. Pepperdata Query Spotlight then gives you insights on the thousands of concurrent queries and helps you understand query execution and database performance.

Better communication allows ITOps to help the application team efficiently work through the development transitions. These benefits optimize application performance and uptime and help ensure that SLAs are met.

WHY TO CONSIDER DATA SCIENCE IN 2020?

Today, more and more organizations are leveraging big data and its potential as they are generating a voluminous amount of data every day. However, this is increasing the value of data science and the demand of data scientists that use scientific methods, processes, algorithms and systems to mine insights from both structured and unstructured data. There is no doubt data is an essential asset for every business, enabling executives and leaders to make effective decisions based on facts to bolster their productivity and profitability.

SCIENCE

Considering a market report, the global market of big data is predicted to grow at a CAGR of 0.6 percent from US$138.9 billion in 2020 to US$229.4 billion by 2025. It has also been projected that the data science platform market size will grow at a CAGR of around 30 percent from US$37.9 billion in 2019 to US$140.9 billion by 2024.

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Data Science plays a vital role in any business, supporting businesses to deliver germane products, assisting in minimizing peril and fraud in business, and helping business leaders to understand and manage their data effectively.

Already, most companies that use big data and analytics technologies into their business processes are benefiting from the growing democratization of data. With a large set of data that have the potential to drive business transformation, organizations, public and private, are now turning to data science knowledge and programming experts like Python developers. Because data scientists are able to make sense out of the data companies are gleaning, using specialized platforms in data management and analysis.

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Heightened Demand of Data Science

According to IBM predictions, the demand of data scientists will surge by 28 percent in 2020, which will give the spike to get the best talent. The huge demand for data science skills will also cause a disruption in the workforce that will have to be addressed by the education sector.

The increasing adoption of robotic process automation (RPA) is further giving rise to the demand of data science professionals. Since a wide range of industries are leveraging this technology, infusing intelligence in automation using data science and analytics will bring the era of hyper-automation that seems to be expanding its territory than ever before. Thus, this integration can assist businesses in analyzing risks and controlling mechanisms associated with hyper-automation.

Many data scientists have advanced and training in statistics, math, and computer science. Their experience is a vast horizon extending to data visualization, data extraction, and information management. While the complete data science process is driven by data that cannot be considered anonymous at all, the cybersecurity industry is also investing heavily in data science techniques to ward off attacks.

By embracing the application of data analytics and machine learning tools, an organization can conduct a thorough analysis of the collection of information, and professionals can evaluate data closely to unlock trends, patterns and actionable intelligence. Also, as a data breach can harm extremely valuable data and information that can be really damaging to an organization, involving data science here can be effective in assessing the history of cyberattacks and creating algorithms to spot the most frequently targeted chunks of data. With the rising capabilities of data science, it is clear that the demand of data scientists will become a vital job in years to come. And integrating them into businesses will drive innovation at large.

An Overview about Javascript frameworks

As JavaScript notoriety keeps on developing and with it, the encompassing biological community of current libraries and apparatuses, it can in some cases be difficult to keep up, prompting what some portray as JavaScript Fatigue.

Javascript

This post will dig into a portion of the advances we’re finding in the JavaScript people group and how such arrangements may profit you and your group, without making you exhausted.

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Frontend

  • React.js

2015 was without a doubt a major year for Facebook’s React; with numerous expansive organizations embracing React, (for example, The New York Times, Netflix, Airbnb, Instagram and so forth.) it’s difficult to overlook. So what settles on React an incredible decision for your front-end? For one thing, React is damn quick. This is accomplished by means of a virtual DOM diff with the DOM and cluster redesigns to fix just the parts of the DOM that need upgrading. Respond permits you to assemble little, reusable parts that envelop the layout and the JavaScript rationale behind them. Obviously, this requires the utilization of a fabricate instrument, for example, Webpack (and different apparatuses). It is this need of extra tooling and the advances inside this space has a considerable measure of designers feeling overpowered.

Respond, being only the perspective layer, requires extra libraries which you for the most part tend to sort out yourself, be that as it may, there are numerous standard undertakings accessible that have everyone of this prepared to leave the crate, the React Starter Kit being one of them.

The executioner components of React are ‘widespread rendering’ and ‘Respond Native’.

‘Widespread rendering‘ implies that our web application can be rendered on the server and to the customer, all from the same code base. This dispenses with any SEO concerns average of customer side JavaScript applications without resorting to arrangements, for example, PhantomJS or Prerender.io.

‘Respond Native’ permits you to target portable stages with a genuine local  Java application utilizing JavaScript. Not at all like half and half portable applications that normally utilize web views inside a local shell, React Native aggregates your application down to a genuine local application for iOS and Android. In case you’re as of now utilizing React as a part of your web-stack, utilizing React Native to provide food for portable would bode well.

  • Precise 2.0

Google haven’t had the least demanding of ways overhauling Angular from 1.x to 2.0 and 2015 saw Angular’s notoriety decay. A few individuals from the group weren’t excessively content with the course Google were taking the system as it’s a significant takeoff from Angular 1.x. This underlying stun made numerous look somewhere else. Additionally, the creator of Durandal joined the Angular 2.0 group in 2014 just to leave a couple of months after the fact to proceed with work on Aurelia, the successor to Durandal. In any case, Angular is in substantial use in numerous associations and a ton of the outline choices for Angular 2.0 were as a consequence of them listening to these clients, which is dependable to be empowered.

Precise 2.0 grasps ES2015, Typescript (which is discretionary) and takes the part approach much like different structures said here. Precise drops large portions of the ideas presented in 1.x, (for example, $scope) and improves numerous different components, for example, mandates. A major center for the Angular group has likewise been versatile execution, so it’s nothing unexpected to hear that The Ionic Framework has focused on receiving Angular 2.0. We can likewise anticipate that the MEAN stack will redesign once Angular 2 has been formally discharged.

In general, I think Angular will keep on getting more grounded and conceivably reinforce its place inside the venture upon the arrival of 2.0. Full Stack engineers may likewise think that it’s advantageous to manufacture both their web and versatile applications utilizing the same front end structure, conceivably expanding code-reuse because of the segmented way of v2.0.

Learning Resources: Ng-Learn has a pleasant review on Angular 2.0. In case you’re avid, to begin with Angular 2.0 in the MEAN stack, this instructional exercise is for you.

  • Vue.js

Vue.js is a front-end system that is anything but difficult, to begin with, yet in the engine lies a capable structure. First off, the documentation is phenomenal and takes after a characteristic learning way. Vue.js takes the best parts of numerous different systems and wraps them up into a strong, absorbable entirety. Much like React, Vue.js advocates single-record segments and unidirectional correspondence between parts to make it simpler to keep up java application development  state (store design with the changeless state). Not at all like React, Vue makes it much less demanding to begin on account of an official framework device – Vue-cli. We can even utilize other preprocessor dialects inside our single-document Vue parts, for example, Jade and Stylus. Sadly there’s no server-side rendering arrangement just yet, keeping in mind Vue performs incredibly on portable, it doesn’t have a huge group behind it like Angular, Ionic or React do.

Learning Resources: The Vue.js documentation is the best place to begin. Jeffrey Way at Laracasts has made an extraordinary video arrangement called Learning Vue 1.0: Step by Step.

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Backend

A backend JavaScript engineer will be acquainted with Express, Hapi or Koa. These are all web servers whereupon you can assemble your java applications; they’re for the most part little and un-obstinate about how your application ought to be organized. Extra usefulness is regularly given through NPM modules. Nonetheless, towards the last a portion of 2015, we saw the ascent of all the more full stack structures for node.js.

This domain has ordinarily been evaded by JavaScript engineers the same number of like to sort out their own stacks. That is still the case for the greater part of JavaScript engineers and it’s the way we like to do things here at Clock as it gives us the most control.

For a very long time the main reasonable full stack system was Sails.js, firmly displayed after Ruby on Rails. Sails is still an extraordinary system, yet we now have some new contenders.

  • Trails

We should start with this structure as there has been a great deal of Internet Drama around Sails and Trails of late. Trails is the work of Travis Webb and his group, initiating a measured web structure that permits you to swap out parts (even the server). This development likewise permits you to effortlessly amplify your java application with reusable trail-packs.

Travis was a center giver to the Sails.js extend yet was evacuated by Mike McNeil, the BDFL of Sails. Both sides hadn’t figured out how to settle their question in private and it was rather battled on Hacker News, in Github issues, on Twitter and so forth. Wow. In any case, just to be clear, Trails is not a fork of Sails but rather is in truth a complete re-compose and takes a full favorable position of ES2015. v1.0 is booked for discharge in April 2016 and from an underlying look, it ought to be exceptionally well known to any individual who has utilized Sails as a part of the past.

  • Nodal

Nodal is conveyed to us by Keith Horwood and intends to be a simple to utilize structure for making REST APIs. While this isn’t as full-stack as it at first claims to be (server-side rendering isn’t a need) and it utilizes an unsupported templating dialect DoT.js, Keith’s gained some awesome ground permitting engineers to make REST APIs effectively, fundamentally using code generators.

Nodal is developed from the beginning ES2015. Keith was despondent with the lego-style way to deal with building web applications with node.js and needed something with a durable look and feel over the stack that made him as profitable as could be allowed. It’s likewise worth specifying that Nodal utilizes Postgres for information constancy. Generally speaking, this is an incredible structure with an exceptionally dynamic group.

  • Adonis

On the off chance that you’ve ever utilized Laravel, a well known PHP web structure, then you’ll feel comfortable with Adonis. Adonis grasps the engineering and outline designs Laravel advocates and conveys them to node.js like no other full stack structure. Using ES2015 generators, intermediaries, Service Providers, Inversion of Control compartments and a capable ActiveRecord affected ORM called Lucid, Adonis surely brings a great deal of usefulness to the table.

This system favors SQL databases over NoSQL arrangements, something that is beginning to wind up significantly more regular now that PostgreSQL has awesome JSON support.

While Adonis is exceptionally youthful, it has a considerable measure of potential – particularly to attract amateurs as its documentation is very careful. Experienced designers will likewise value the engineering decisions Adonis has made as to building and keeping up extensive applications.

This system is most appropriate for the individuals who are not simply intrigued by building stateless REST APIs (which it can do great), yet the individuals who additionally wish to do server-side applications. Most systems which concentrate on being a REST API back-end tend to tumble down in the server-side rendered division and Adonis knows this.

  • Strapi

Strapi is an exceptionally intriguing structure which concentrates on the development of REST APIs. It’s based on top of Koa and contains numerous elements out-of-the-case that a run of the mill designer would need, for example, a client administration framework, JWT verification, document transfer and email bolster and even backings GraphQL.

In any case, what makes this system especially intriguing are the going with web applications; an administrator dashboard that comes packaged with your venture and an online device called Strapi Studio.

The administrator dashboard permits you to deal with the clients and information inside your application, whereas Strapi Studio permits you to construct your API by means of a web interface and the subsequent code is matched up down to your PC – exceptionally cool stuff.

Why Full-Stack Development? See These Top 5 Facts

Full-Stack development as the name suggests, it is the process of developing both front and back end segments of an application. The three prominent layers that involved in this process are,

Stack

  • Presentation layer – One that covers the UI
  • Business logic – Back end part, which concentrates on data validation
  • DB layer – Vast space for information storage

Ultimately the Full Stack development process plays the role of taking a concept into a real usable product.

The reason why enterprise prefers Full Stack resources lies in the expense of hiring individual coders for each development works involved. Deploying a single full stack candidate who is master in collective stacks would make the job even easier.

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Why it is preferred?

This technique involves the power of functional knowledge and facility to put effort on different aspects that contribute to application development. The handy reasons why agencies prefer full stack development are,

  • More optimized code in Java, JS & HTML
  • Making use of APIs with backend using Java/Python or Ruby
  • Easy working with infrastructure (hardware & OS inclusive)
  • Networking & Security

For deeper understanding about Full Stack procedure you should be going through the facts mentioned below,

A mixture of both front & back end

As mentioned at the beginning of this article, Full Stack development stands for the process carried out in both designing and development stacks. The candidate involved in this task will be proficient in handling front end and back end works involved.

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Techs emphasised under Full Stack

For an enterprise to choose a Full Stack expert, it’s not necessary for the candidate to have knowledge in all 170 programming languages used for application development. Yet there are definite techs that one must be well versed with and those include HTML/CSS, JS, Storage & DB, REST API & HTTP, Version control platforms like Github and Learning Architecture details.

Never fallen demand

The term digitization led business owners to think about the audience’s seamless experience than just focusing on creating an application for sake. The power of single resource to handle all the aspects of an application including designing, formatting, UX & programming opened a new door of opportunity in creating most engage-able applications. After seeing standard ROI for an application built over Full Stack procedures; the demand for it never went down since its establishment.

Calibre reached within budget

Meeting audience expectations is the ultimate goal of an enterprise application. But achieving it would cost high for a small business/start-ups with a great idea/concept. With Full Stack, both elegant and engaged applications are built with the minimum cost involved.