A growing number of developers are leveraging this increasingly powerful technology. Utilizing the right software architecture is very important for developing quality applications. In order to develop applications relying on it, they should be familiar with the Node.js open-source server environment.

The Evolving Role of Node.js in Microservice Development

In today's world of software development, building and maintaining large-scale, monolithic applications can be a cumbersome task. This is where microservices architecture comes in, offering a modular and scalable approach to building applications. Let's explore the process of developing microservices using Node.js development services, a popular platform that is highly suitable for developing solutions based on microservices.

In this post, we will first dive into designing microservices architecture and its benefits. We will then move on to the implementation of microservices with Node.js and shed some light on setting up the development environment and building a simple microservice. We will also discuss communication between microservices, scaling and deployment strategies, as well as tools for managing and monitoring systems. By the end of this article, you will have a solid understanding of how to build microservices with Node.js and be able to apply this knowledge to your own development projects.

Designing Microservices Architecture

Microservices architecture is a modular and flexible approach to building applications that involves breaking down a large application into smaller, independent services. There are many benefits of microservices.

Each service can be developed and managed independently, allowing for greater scalability, fault tolerance, and ease of maintenance. Here are some prominent features that make microservices architecture so special:

• Better scalability – With microservices, each service can be scaled independently, allowing for greater flexibility and responsiveness to changing demand;
• Easier maintenance – Because each service is independent, changes or updates to one service do not affect the others, making maintenance and updates easier and less risky;
• Improved fault tolerance – If one service fails, it does not bring down the entire application, as the other services can continue to function independently.

To design a microservices architecture, adhere to the below:

• Identify the application's business capabilities – Determine which business capabilities will be broken down into individual services.
• Define the service boundaries – Determine how the services will interact with each other, and define their boundaries and responsibilities.
• Choose the appropriate communication protocols – Decide on the best way for services to communicate with each other, such as REST or messaging.
• Follow microservices patterns and principles – Consider microservices patterns and principles such as the Single Responsibility Principle, the Circuit Breaker patten, and the API Gateway pattern.

Implementing Microservices with Node.js

Node.js is based on JavaScript, which makes it easier for developers to switch between frontend and backend development and share code between them. Furthermore, Node.js uses non-blocking I/O, which allows it to handle multiple requests simultaneously and improving its performance and scalability. Node.js also has a large and active ecosystem of modules and libraries that can help you build microservices faster and more efficiently.

To set up a Node.js environment for microservices development, you can use dedicated tools to install the necessary packages and libraries. You can also use a framework like Express.js to simplify the development process. In order to build an elementary microservice with Node.js, you just need to follow the below steps:

1. Define the service – Determine the service's responsibilities and API endpoints;
2. Create the service – Resort to Express.js to create the service and define the API endpoints;
3. Implement the service logic – Add the necessary logic to accurately process system requests and respond with the appropriate data;
4. Test the service – Use special tools to test the service and make sure that it is functioning correctly.

What Are the Options for Inter-Service Communication?

When it comes to the architecture part, inter-service connection and communication is a critical aspect of the overall system design. There are several options for inter-service communication, including:

• Synchronous communication – Services communicate directly with each other using REST, gRPC, or other synchronous protocols;
• Asynchronous communication – Services communicate indirectly using message queues or publish/subscribe patterns;
• Event-driven communication – Services communicate by publishing events to a message broker, which are then consumed by interested services.

Choosing the right communication protocol for your microservices depends on several factors, including the level of decoupling required between services, the expected message volume and frequency, and the need for fault tolerance and scalability. For example, if low-latency communication is required between services, synchronous communication using REST may be the best option. On the other hand, if high fault tolerance and decoupling are required, asynchronous communication using message queues may be a better fit.

A common communication pattern between microservices is the API Gateway pattern, in which an API gateway acts as a proxy for multiple services, providing a unified API for clients to access. Another common pattern is the Circuit Breaker pattern, which helps prevent cascading failures by detecting and isolating failing services.

How to Scale and Deploy Microservices?

To scale a microservices architecture, you can use techniques like containerization with Docker and container orchestration with tools. The latter enable you to deploy and manage multiple instances of your microservices in a scalable and fault-tolerant manner. Deployment strategies for microservices include blue-green deployment, canary deployment, and rolling deployment. These approaches enable you to deploy updates to your microservices with minimal downtime and risk of failure.

The post How to Build Microservices with Node.js appeared first on Datafloq.

Around 90% of companies in the US and UK view artificial intelligence as a priority, with AI projects either in planning or production.

However, half of them acknowledge that they don't have skilled talent to make the most of AI advances. This is where experienced AI consulting firms come in to help.

The market of AI consulting is vast, ranging from tech giants like IBM and Accenture to Big 4 firms and smaller-scale innovators.

Here, we've compiled a list of the top 10 AI consulting firms that have earned a reputation for disruptive innovations. These experts run product discovery and deliver proofs of concept (PoC) and MVPs. This way, they help organizations bring pioneering products and services to the market and build proprietary AI systems for transforming operations.

Let's explore these top AI consulting companies – they are worth their salt. In this blog, you will find an overview of each of them as well as useful tips on how to pick the right partner for your AI project.

Our list of the top 10 AI consulting firms for 2023

1. ITRex

ITRex is a full-cycle AI and big data solutions provider with teams in Poland, the US, and Mexico and a dedicated R&D lab where they design new AI concepts and build prototypes. They are tech savvy in all AI-related fields (ML, deep learning, NLP, and computer vision), delivering AI projects end to end, from preparing data for algorithms to rolling out systems to thousands of users.

Having adopted a start-small-and-scale-up approach, ITRex helps Fortune 500 companies and startups launch breakthrough AI products, apart from automating operations, boosting customer experiences, and supporting smart decision-making.

They've delivered quite a number of impressive AI projects, from an AI-powered big data platform for the world's biggest retailer to a fitness mirror with a personal coach experience, an ML-based clinical decision support system for cancer patients, a SaaS cybersecurity solution using face recognition, and many others. Walmart, 21st Century Fox, and Warner Bros. Entertainment Inc. are just some of their big-name clients.

• Rates: $50 – $99/hr
• Size: 300+
• Founded: 2009
• Headquarters: Aliso Viejo, California

2. Deeper Insights

The UK-headquartered Deeper Insights is fully focused on providing AI consulting and development services, with its expertise spanning from AI exploration to ML engineering, NLP, and computer vision. As they say on their website, they solve their clients' “impossible problems,” helping them achieve the desired business results.

The company develops custom AI algorithms and ML models using either their clients' data sets or data collected via their proprietary ML web scraper – the Skim Engine.

They have delivered many innovative AI projects for big-ticket and smaller clients, including an automated insights app for sales teams at Deloitte, a custom media monitoring platform for the global real estate services company Jll, and bespoke computer vision algorithms integrated with deep learning to recognize body parts in images in robotic surgeries.

• Rates: $50-$99/hr
• Size: 10-49
• Year: 2014
• Headquarters: London, UK

3. InData Labs

InData Labs also specializes in AI consulting and implementation services. As most top AI consulting firms on our list, they offer not only advice but also AI R&D, PoCs, MVPs, and development of AI web/mobile apps, empowering clients with data science and AI technology.

The company helps clients leverage predictive analytics, NLP, computer vision, and intelligent automation for getting meaningful insights from data, understanding audiences, forecasting demand, reducing risks, and eliminating cost overruns.

Examples of their AI-powered solutions include a computer vision system for pose estimation in fitness, face recognition for a surveillance system, image analysis for ticket processing software, and many more. They've also delivered different kinds of predictive analytics systems for logistics, ecommerce, sports, entertainment, and healthcare, along with NLP tools for simultaneous interpreting, remote education, and sentiment analysis.

• Rates: $50-$99/hr
• Size: 80+
• Year: 2014
• Headquarters: Nicosia, Cyprus

4. Cambridge Consultants

With over 20,000 sqm of R&F facilities and a 900-strong team, Cambridge Consultants helps organizations develop AI-based products that “will transform how we live and the world around us.”

Being part of the French-based tech consultancy Capgemini, Cambridge Consultants is a big and established player on our top AI consulting firms list, operating since 1960.

Cambridge Consultants is honored for AI breakthroughs in many fields across industries. Projects in their portfolio range from a drone delivery service to military robots using AI-based navigation and reinforcement learning, a proprietary crop spraying technology, an AI system for an automated response to cyberattacks built for the UK Ministry of Defence, and a piano music classification tool.

• Rates: Undisclosed
• Size: 900+
• Year: 1960
• Headquarters: Cambridge, UK

5. ThirdEye Data

Based in Silicon Valley with delivery centers in the US and India, ThirdEye describes itself as a one-stop-shop for data science, analytics, and engineering services. Apart from providing end-to-end big data and AI solutions, the company has developed their own open-source tools for anomaly detection and predictive analytics.

Their expertise is recognized by multiple industry awards. Microsoft, Walmart, British Petroleum, and AWS are among their Fortune 500 clients.

The company has implemented over 30 end-to-end data and AI projects, such as an image quality detection system for Southern California Edison, MLOps engineering for XPERI, and predictive metrology for Glas Trosch.

• Rates: $25 – $49 hr
• Size: 51-200
• Founded: 2010
• Headquarters: San Jose, California

6. LeewayHertz

Operating since 2007, LeewayHertz specializes in many AI fields, from ML and NLP to computer vision. Among its big-name clients are Procter & Gamble, McKinsey & Company, Siemens, and Hershey's.

With the mission to help organizations adopt AI at scale, LeewayHertz has entered our top AI consulting firms list for delivering innovative AI solutions across sectors. Among its landmark projects is collaboration with an Indian food tech startup, which has resulted in the creation of the world's first tea-making robot Arya using ML, speech recognition, and NLP. They've also built a computer vision-enabled marketplace for AI applications and an AI-based employee time-tracking app.

• Rates: $50-$99 hr
• Size: 51-249
• Founded: 2007
• Headquarters: San Francisco, California

7. DataRoot Labs

DataRoot Labs is a fast-growing company with teams in Ukraine and Israel. As a top AI consulting firm, it helps ambitious startups and startup accelerators turn their boldest AI ideas into reality.

DataRoot Labs prides itself on driving tech innovation by running the DataRoot University, which offers data engineering and data sciences courses.

They have accomplished a great number of projects around computer vision and other AI technologies for clients, delivering, for instance, a solution for defect detection in solar panels, a personal coach app, an in-store customer activity tracking app, an empathetic virtual assistant, and many others.

• Rates: $51-$99/hr
• Size: 10-49
• Founded: 2016
• Headquarters: Kyiv, Ukraine

8. Azati Software

Creating fully functional AI solutions since 2016, Azati Software shares its expertise on a consultancy basis across AI fields, from supervised/unsupervised learning to NLP, computer vision, predictive analytics, and conversational AI.

Their featured AI-based projects include a data processing tool to analyze inputs from oil and gas meters using ML and computer vision, an ML model for pharmaceutical marketing, a semantic search engine to tap into scientific datasets, and an AI-powered app that changes the interior on smartphone pictures.

With an R&D center in Poland, this top AI consulting firm successfully helps clients translate their AI vision into prototypes and MVPs.

• Rates: $25-$49/hr
• Size: 150
• Founded: 2001
• Headquarters: Warsaw, Poland

9. Tooploox

The EU-based AI consultancy Tooploox has built its AI expertise by working extensively with US startups, innovators, and VCs.

With the mission to improve people's lives through cutting-edge technology, Tooploox has extensive R&D capabilities that have widened after the company joined forces with Microscope IT, a development shop offering AI-related services for healthcare, medtech, and life sciences. Their skillsets around AI now extend to computer and 3D vision, deep learning, sensor fusion, NLP, data capture & OCR, and beyond.

Tooploox has been recognized for its research at international conferences, such as NIPS and ICML. They are also known for building Virtum, an AI-powered image analysis system that helps spot cancer cells.

• Rates: $100-$149/hr
• Size: 150
• Founded: 2012
• Headquarters: Warsaw, Poland

10. Addepto

Addepto is another fast-growing company that deserves a spot on our list of top AI consulting firms. It was established in 2017 and now helps companies grow with the power of data and AI.

With expertise in all data-related fields, the Addepto team has won the trust of a few Fortune 500 companies, which they support in creating complex AI solutions. Among them are Citibank and P&G.

Addepto has helped build a digital twin monitoring airport operations, an intelligent passenger and baggage tracking system, a shipping schedule and inventory management system using predictive modeling for the world's second largest aluminum company, and an ML-powered demand forecasting tool for postal services.

• Rates: $50-$99/hr
• Size: 10-49
• Year: 2017
• Location: Warsaw, Poland

How to choose your AI partner – Tips from the ITRex CTO

Reducing a lot of options available in the AI consulting market to just a few should make life simpler. However, you still need to choose only one of them at the end of the day. What should you consider? We've asked ITRex CTO Kirill Stashevsky, who has over 15 years of experience helping companies deliver innovative solutions, to share his tips. Here they are:

• 1. Explore the vendor's website to make sure they indeed offer AI consulting services, not just development.

This can be especially helpful for those with little or no technical background. The thing is, an experienced consulting partner might figure out a more elegant tech solution for translating your vision into a reality. This solution can be cheaper, quicker, and more efficient than the one you had in mind. The latest AI breakthroughs can be fascinating, but it is useful to make sure first before any coding begins that they are exactly what you need to build a fascinating product.

A good AI consulting firm would be happy to look at your vision from different perspectives and give you free advice over the phone. Don't hesitate and ask for it first.

• 2. Look through the vendor's portfolio to check if they delivered a similar solution in the past.

Companies' portfolios with featured projects or case studies are a great source of valuable information. They let you understand which clients they served and what projects they accomplished previously.

It is best to reduce your list of top AI consulting firms to companies that have a demonstrable experience with what you are trying to achieve. These guys should know your domain well so you will speak the same language with them without having to waste time explaining the basics. They are also likely to know all the potential pitfalls that might be typically encountered on a journey like yours.

However, don't be too quick to strike off a vendor of your choice that doesn't have the exact expertise you are looking for. The firm can still be a perfect fit for your project if they specialize in AI consulting services (see the first tip).

• 3. Do a bit of homework to clearly define your business objectives.

Instead of contacting all the 10 or 20 companies on your top AI consulting firms list to discuss your future product, prepare a one-pager describing what you are trying to build from the business point of view, and send it out. Some vendors would reply they don't know how to help, some might figure out at once how they can implement your idea best, while others might offer you a cost-efficient customization of a tool that is already in the market. This way, you will narrow down your list quicker, saving time and energy.

• 4. Don't forget about social proof

Check out reviews from actual clients who partnered with the company previously and the company's rating. This information can be found on sites like clutch.co or goodfirms.co. Ask your acquaintances, colleagues, and people you meet at hackathons and industry conferences – they might have heard something about a firm of your choice. You can also ask the vendor for feedback from their previous clients.

Wrapping it up

Artificial intelligence is already having a profound impact on our daily lives while transforming the business landscape. PwC estimates that AI could add more than $15 trillion to global GDP by 2030, meaning that it has the potential to completely change the way we live. Capitalize on the emerging trend and put your company at the front of the line by partnering with the right AI consulting firm.

The post Top 10 AI Consulting Firms Today appeared first on Datafloq.

Data Structure and Algorithm (DSA): What is it?

Data structures and algorithms, a subject of computer science, are responsible for creating computer programmes that are machine-efficient and optimized. Algorithms are used to define problem-solving techniques, whereas data structures are used to organize and store data. In software engineering, we optimize the codes by fusing “data structure” with “algorithm.”

DSA in Software Development

Data structure and algorithm (DSA) is used across all software development disciplines.DSA is the cornerstone of the software development process. It's not constrained to just one kind of programming language. DSA is implemented into all programming languages, even though some of them mutate or go extinct over time.

Selecting a suitable data structure and algorithm determines how effectively software is developed.

In some circumstances, you might be given the best data structure to use with a reliable method. The code will only deliver the desired result if the two are compatible. Therefore, choosing a suitable data structure for an algorithm is a crucial step in the software development process.

How does DSA apply to your regular life?

Let's look at some real-world DSA applications.

Data Structures

• Utilizing a Stack Data Structure to Reverse a String

A stack is a linear data structure, with the term “linear” denoting the arrangement of the items. A new element can only be accessed after the earlier elements have been accessed.

Why do we need a stack representation?

You might be wondering why a programmer must learn how to stack and remove plates from a pile. Let's investigate the solution. You have been tasked with reversing a string. What method would you use?

• Queue Data Structure while Boarding a Bus

You might be wondering why a programmer must learn how to stack and remove plates from a pile. Let's investigate the solution. You have been tasked with reversing a string. What method would you use?

Why is a queue representation necessary?

You might wonder how a queue functions on a computer. Assume you are in your office where five machines are connected to a network. These computers are all connected to the same printer by you. Let's say a worker wants to print some documents and uses his computer to send a command to the printer. After receiving the instructions, the printer begins printing the documents. For detailed information, visit the data structure training, offered by Learnbay.

Google Maps and the Social Media Graph Data Structure

A graph is a collection of related objects. Each item is known as a node, and the connection between them is known as an edge.

You most likely use websites like Instagram, Facebook, LinkedIn, and others. Social media is an excellent illustration of a graph in use. In social media, user data is stored in graphs.

Each user, in this instance, acts as a node, much like in Graph.

And if one user, let's call him Jack, befriends another user, let's call her Rose, then Jack and Rose have an edge (connection).

Algorithms

Algorithm for Sorting Books on a Shelf

Simply put, sorting is the systematic arrangement of similar items. Consider how you might arrange books on a shelf according to their height. The taller books will be on the left, and the shorter books will be on the right if we do it the other way around.

Algorithms for sorting use this same idea. In DSA, various sorting methods are accessible. The objective of each algorithm is the same, but each algorithm behaves differently for various reasons.

• There are a few things to consider in the example above if we want to sort the books as quickly as possible.
• Can the books on the shelf be moved around? We might need additional time if the books are heavy. Similarly, there can be further restrictions. (accessibility)
• How many books are there in total? (Data volume)
• How quickly can we get to them? (The capacity of hardware)

Finding a Book in a Shelf Using a Searching Algorithm

Searching helps people find things, as the name suggests.

Say you want to search for a specific book on a shelf. The books in my collection are not in any particular order. How would you find the book in the shortest period of time if you were to? DSA provides the solution to this issue.

You may think, “I'll start looking for the book at the beginning and find it.” You will be searching from the top of the shelf to the bottom.

Finding the Shortest Path in a Google Map Using Shortest Path Finding Algorithms

Have you ever wondered how Google Maps can provide the quickest route to your destination? Shortest Path Finding Algorithms, a class of algorithms, are used by programmes like Google Maps to do this.

These algorithms search a graph for the shortest path. We may utilize graph algorithms to discover the shortest path between two specified places on a map, just like the example covered in the Graph data structure above.

Find the quickest route between points A and F on the following map to demonstrate the issue.

There is just one way to go to F from D. We can travel to B from D as well, but since B has already been reached, it is not considered. By choosing the DF route, we arrive at our destination.

Hope you understood the concept. If you're still unsure and want to master DSA, sign up today for a data structure course taught by industry tech leaders.

The post Everyday Use of Data Structures and Algorithms appeared first on Datafloq.

In today's world, the importance of data quality validation is hard to overestimate. For instance, the 2020 Gartner survey found that organizations estimate the average cost of poor data quality at $12.8 million per year, and this number will likely rise as business environments become increasingly complex.

Assuring the quality of data is possible with modern data pipelines that should include data quality components by default. I have solid experience in the Data Quality Assurance (Data QA) niche and understand how to achieve data quality in the best way possible. I will share some of my expertise in this article.

Great Expectations – A Data QA Tool of Choice

To begin with, let's talk about one of the best Data QA tools – Great Expectations (GX).

Great Expectations is an open-source data quality tool based on Python. GX can help data teams to profile, test, and create reports for and on data. GX has a friendly command-line interface (CLI) that enables you to easily set up and create new tests, while quickly customizing available test reports. GX can be integrated with various extract, transform, and load (ETL) tools, such as Airflow, and also with many databases. (You can find the list of integrations here and official documentation here.)

Most importantly, Great Expectations supports AWS.

Reporting on Data with Allure

Allure is the gold standard for reporting in QA. Allure enables managers and non-technical professionals to review test results and keep track of the testing process. That is why, we decided to use Allure as a demonstration tool, to display Data QA results and implement a self-written adapter that converts GX results to the Allure format.

We suggest the following Data QA approach for automating test creation:

1. Retrieve tested data from data sources using AWS Lambda
2. Run AWS Lambda with Pandas Profiling and generate tests for GX
3. Run GX Test Suite for each dataset, all run in parallel for each dataset
4. Store/serve results for each data source as a static Amazon S3 website
5. Convert GX results to the Allure report format using AWS Lambda
6. Store results in Amazon S3
7. Generate Allure reports from the Allure format; reports are stored and served in Amazon S3
8. Send the reports to a Slack channel with AWS Lambda
9. Push results to Amazon DynamoDB (or Amazon S3 to reduce costs)
10. Crawl data from Amazon DynamoDB by using Amazon Athena
11. Create a dashboard with Amazon Quicksight

Building a Data Quality Gate

We now have all the components needed to build an efficient data quality gate. To simplify their deployment to AWS, we created a Terraform module – Data Quality Gate – that enables you to assure the quality of your data in one click. This module allows you to quickly deploy the infrastructure for DQ and generate the first test suite for your data. Use this module as a standard Terraform module for AWS-based deployments.

Conclusion

Data Quality is a fast-growing field, and many engineers are involved in this process daily. Data Quality Engineers should build a solid pipeline for testing data and presenting results to stakeholders. Today, leveraging the availability of open source tools to deploy solutions faster plays a crucial role in data processing.

The post Assuring Data Quality: How to Build a Serverless Data Quality Gate on AWS appeared first on Datafloq.

Django, a scalable Python-based web framework that's become an industry leader based on its combination of simplicity, speed, and scalability, showed the power of its open-source approach to problem-solving in recent weeks as an identified high-security risk was quashed in a matter of days.

The security flaw, categorised as CVE-2022-34265 by the Common Vulnerabilities and Exposures system, was identified as a critical vulnerability by Red Hat on July 4th 2022. This assessment was based on its preliminary review, with the open-source software vendor allocating it with a CVSS v3 base score of 9.8.

Red Hat had determined that the attack complexity of the flaw was ‘low' and that the privilege and user interaction required to carry the exploitation out was ‘none' – making it a particularly dangerous issue for businesses operating on Django frameworks.

However, as soon as the news was released regarding the flaw, it had already been fixed by The Django Software Foundation.

Just how long the issue had been active before detection and the subsequent fix is unclear, however. The National Vulnerabilities Database (NVD) created the record for CVE-2022-34265 on the 21st of June 2022, but it's important to note that this data refers to when the CVE ID was created and doesn't necessarily refer to the date when the issue emerged.

Through the release of Django‘s new updates, Django 4.0.6 and Django 3.2.14, users were quickly able to upgrade or patch their software in an extremely swift manner.

Specifically, the vulnerability was capable of allowing a threat actor to attack Django web applications through arguments provided to the Trunc(kind) and Extract(lookup_name) functions.

“This security release mitigates the issue, but we have identified improvements to the Database API methods related to date extract and truncate that would be beneficial to add to Django 4.1 before [its] final release,” disclosed the Django team on the framework's website. “This will impact 3rd party database backends using Django 4.1 release candidate 1 or newer until they are able to update to the API changes. We apologise for the inconvenience.”

The Value of Open-Source Web Frameworks to Businesses

As businesses continue to grow their online presence in the wake of the Covid-19 pandemic, open-source projects like that of Django are continually proving their worth in terms of superior security measures.

Fundamentally, open-source platforms are capable of fixing vulnerabilities and releasing patches, as well as new updates, much faster than their more private and commercial counterparts. This is because many collaborators can work together to provide better solutions and to action on emerging issues in an efficient manner.

(Image: Diligent)

As the data above shows, the consequences of a data breach or exploited vulnerability can be extremely hazardous for businesses that engage in their customers online. Not only can data breaches cause 65% of its victims to lose trust in a company, but 80% of consumers believe that they will avoid using the business if their information is compromised in a breach.

The advantages that Django‘s open-source framework has for businesses looking to build web and mobile applications that are safe and secure are many. One of the key factors behind this is that many individuals can work to create quick fixes, whereas with commercial vendors the update cycles can take longer due to fewer people working on projects.

Furthermore, commercial vendors may seek to prioritise updates based more on financial considerations. Due to this, some vendors operate on 6-12 month release cycles – meaning that it can take as long as a year for a solution to arrive.

If open-source projects are developed by commercial companies, the increased levels of visibility creates a greater urgency for issues to be fixed, and as a result, better code could ultimately take its place.

This greater visibility can be largely beneficial for the output of businesses, too. This is because Django development can work in a more comprehensive manner in building the applications and web structures that a company requires with full knowledge of the framework at hand.

As more businesses seek to embrace digital transformation, the necessity of providing secure web frameworks for customers and users is imperative. In countering an early emerging security threat in recent weeks, Django has once again demonstrated the value of open-source projects in offering a high-quality and reactive form of security for businesses seeking to operate online.

Given the damaging effects of businesses that fall victim to cyberattacks, it's certainly worth decision makers to look to programming languages that operate in a similar fashion to Django as a means of shoring up their online presence as an essential consideration.

The post Django’s Swift Patch of High-Severity Bug Illustrates the Power of Open-Source Frameworks for Businesses appeared first on Datafloq.

This will require you to conductthorough business research and examine your competition, of course, but it will also require you to assemble an expert team of developers, operations managers, and marketers. Today, though, let's focus on the problems of seamless development and market rollout.

Here are some key strategies to get your software product out on time and make an impact on the market from day one.

Ensure cash flow and asset allocation

First things first, money. Cash flow is the single most important element of a successful SaaS development cycle, followed closely by rollout. Without cash flow and smart asset allocation, you can't move forward and you can't prepare your product to hit the market successfully with proper branding, advertising, and marketing.

While money is not the only thing SaaS leaders should worry about, it's definitely the first thing. With that in mind, you need to secure funding for your initial cash flow needs, take steps to ensure the onlinesecurity of your business finances, and line up future backers and investors.

You can use advanced payment security solutions and transaction tools for cash flow security, but when it comes to backers, consider:

• Angel investors
• Small business loans
• Crowdfunding
• Recurring independent backers
• Investment groups

Likewise, make sure you have several monetization tactics lined up for when the product rolls out, so that you can pay off your debts (you will have debt) quickly and start profiting within the first year.

Leverage DevOps to make incremental progress

There are many reasons why it's important to utilize the DevOps methodology in modern software development. For one, DevOps aligns operations with the development team to minimize setbacks and improve automation,and doing so helps keep your finances in check.

When you're looking to roll out your software product efficiently and effectively, and not miss your deadline, thenDevOps becomes instrumental in your success. The DevOps approach relies heavily on process standardization, automation, and the mindset of daily, incremental progress.

DevOps teams will make sure to automate anything they can to eliminate the risk of error, minimize financial waste, and prevent project stagnation. The DevOps approach will also standardize communication between operations and the dev teams to ensure nothing slips through the cracks.

The key benefit here for you and your software development process is that DevOps will make sure the project moves forward. That means small, daily progress to justify your development spend and ensure you reach your rollout date with a polished product.

Align operations and development with agile metrics

Tying directly into the previous point, it's tough to ensure incremental progress if your operations and DevOps teams are not using the right metrics and monitoring the right data. Agile is generally the way to go when it comes to software development, and usingagile metrics is one of the best ways to keep track of all the variables, understand how the process is unfolding, spot roadblocks early, and prevent common pitfalls.

So, what are agile metrics, exactly? Agile metrics are data points that measure a team's productivity, progress, and effectiveness across the entire software development project. Using agile metrics means that you get constant feedback as to how the process is developing, it helps ascertain the quality of the dev team's work, and it helps manage resources several steps in advance.

Rather than reacting to project developments, you'll be able to predict certain outcomes, sense the demand for resources, and prepare for the next stages of the development lifecycle.

Build a rollout website for your product

We talked about the importance of funding and operations management for the development process, now let's talk about marketing and rollout. For one, you should focus ondata-driven marketing and demand sensing in order to optimize your product and your marketing strategy for your target demographic prior to release.

But before you invest in your marketing campaigns and building hype for your product, you should have a polished, optimized website. Much like software development, thewebsite development process is a lengthy one, and you should start it months prior to the rollout date to ensure you have enough time to change the design, the visual guides, and any content on the site.

Likewise, just like you need to test your product rigorously before launch, you need to test your website in a private cloud environment. Host your website on internal servers so that it doesn't rank on Google, but keep optimizing to have a polished site in time for rollout.

Start your marketing campaign early

Continuous software development, website development, and marketing are three crucial elements of a successful rollout strategy. When it comes to marketing your product, you need ample financial resources as well, so all the more reason to manage your finances and cash flow wisely. Apply the same financing strategy to your marketing as you do to your development.

That's because digital marketing, which requires a substantial budget to be successful, is no longer a luxury. To succeed, particularly in the SaaS field,your marketing efforts must take a fully modernized digital approach, from social media to personalization to video events, and more.

Now, to market your SaaS product effectively, you can't kick-start your campaigns on the day of the rollout, or a week before. Even a month before the big day is too late, because you need time to build interest, engagement, visibility, and true demand for your product.

With that in mind, start organizing your marketing strategy at least six months before the projected rollout date. Assign financial parameters to each marketing tactic, and make sure to consistently run marketing campaigns to build hype across the web.

Test rigorously before D-day

The rollout can make or break your SaaS product. Sure, there'll be opportunities to improve and optimize when you get consistent user feedback, but you have to make sure that the initial product delivers on the users' expectations.

To that end, you need to conductrigorous internal testing every step of the way (choose your testing level and again, use DevOps), and generate closed user feedback. This means running focus groups and beta testing for UX and UI, as well as the key functionalities of your product.

After all, there's only so much your developers can do with their own testing without leveraging real-world users. You can also make beta testing public and invite users from around the world to give your product a try to collect as much user feedback as possible.

Wrapping up

Software development entails months of hard work and collaboration between development, operations, marketers, and business leaders. During that process, there are a lot of roadblocks you may encounter, all of which can set you back financially and strategically.

Don't let that happen, instead, use these tips to seamlessly take your development cycle forward, minimize errors and setbacks, and enter the market in an efficient and effective way in 2022.

The post 6 Strategies for Effective Software Development and Rollout appeared first on Datafloq.

In an era where trust is held very highly, Blockchain is super appealing because of its ability to validate, authenticate and secure information. This is no small improvement on what was working earlier, especially in the recruitment industry where a simple verification process takes weeks and the same is repeated over and over when applying for a new job, a burden on both the candidate and the business that is trying to hire.

How exactly can Blockchain be used in the recruitment industry?

To understand how Blockchain can help in the recruitment industry, you need to know how Blockchain works. Let us give you an easy explanation of how it works.

Blockchain is a public digital database that leaves a trail of validated facts, it could be anything from documents to money. Each transaction and the accompanying details are validated. Anyone with access to the ledger receives the information and it is impossible to tamper with it since each block of information references the block before it.

Therefore, industries like banking, insurance and manufacturing are clamouring to get their hands dirty with Blockchain as it provides privacy and security standards that were unheard of earlier.

What kind of a dent is Blockchain making in the recruitment industry?

A huge part of the hiring process involves ratifying the documents, certificates, and other information that the candidate gives to the potential employer. This process is usually done by the HR team or is outsourced to a third party that verifies the information using various methods.

The fact that candidates these days would have worked with many companies and would have had different varieties of experiences, both personal and career-wise, makes it much more difficult to track and validate the information given.

Since Human Resources is a data-intensive function, Blockchain would find newer ways in which it can serve this domain as data here is tamper-proof.

Background verification

The background verification process that is practiced today ishuman, time, and research-intensive, and can be an exhausting process not only for the candidate but for the company as well.

What happens with the involvement of Blockchain in this process is that all the candidate's records, including academic certifications, ID proofs, employment history, salary slips, and more such details can be stored in a safe platform.

This information can be given access by the candidate to potential employers whenever the need arises. This removes the need for 3rd party verification services which will only add to the recruitment costs and saves truckloads of time because there is no necessity to repeat the entire process again.

In fact, this eliminates the huge dependency on background verification agencies and reduces the need to go after chasing previous employers, educational institutions, and so on.

Seamless on-boarding

When a business uses blockchain to validate the information of a candidate like educational background, salary proof, age proof, employment verification and so on, it ensures a facile on-boarding of candidates into the company fold without an exhaustive set of procedures.

Decentralized recruiting

Recruiting usually works this way where they either hire a freelancer or a recruiting firm whose job is to take care of sourcing candidates to get information about candidates who match the skillsets required for the job.

When you involve Blockchain into this equation, it becomes much more efficient. Imagine a recruitment marketplace on Blockchain which gives participants points for each action that they take. Points could be earned for referring friends, adding information about a set of people with a specific skillset, sharing job openings, and so on.

Since the participants benefit from this, they are a lot more active and employers get access to a huge talent base and recruiters get paid too. It is a win-win situation for everyone involved.

Saves time in the recruitment process

With the drastic reduction in reference requirements, thanks to the public digital ledger that pre-validates information (read Blockchain), the entire process of recruitment, including the onboarding of candidates becomes extremely fast.

Blockchain which gives validated content translates into higher quality of talent pool being available in the market. Using Blockchain in the recruitment industry will ensure that the information that businesses get to look at during the application process or any other stage will always be correct, because it cannot be tampered. This speeds up the process incredibly making it easy to wade through a huge number of applicants to find your ”'purple squirrel!'.

Recruiting is an extremely intensive as well as complex mechanism that involves a lot of stakeholders and truckloads of data. With the help of Blockchain technology, the possibilities in the recruitment space are endless, and will eventually help in creating a professional and efficient system that helps both the candidates and the recruiter. Blockchain is more than just a ledger that holds data, it could be a huge game-changer in the field of recruitment and its usefulness will only be established more in the coming years.

The post How Can You Use Blockchain Technology In Recruitment? appeared first on Datafloq.

• Performance & Mechanical Sympathy
• Modern Java
• Next Generation Microservices: Building Distributed Systems the Right Way
• Architectures You've Always Wondered About
• Building and Evolving APIs
• Developer Enablement – The Secret Weapon
• Modern Data Pipelines & DataMesh
• Debug, Analyze & Optimise… in Production!
• Innovations in ML Systems
• Staff-Plus Engineer Path
• WebAssembly & Modern Systems Programming Languages
• Optimising for Speed & Flow

Dont miss out on real-world insights to help you adopt the right technologies and practices.

The post QCon Plus Online Software Conference 2022 appeared first on Datafloq.

In this guide, we'll walk you through fifteen of the best Java frameworks currently available, so you can analyze & determine which one will work best with your needs. In no particular order:

Here's the list:

• Spring
• JSF
• Struts
• Hibernate
• Vaadin
• Play
• Dropwizard
• Blade
• Jersey
• OSGi
• GWT
• Spark
• Vert. x
• Richfaces
• Primefaces

Let's explore them in detail

Best Java Frameworks to Use in 2022

1. Spring Framework

Developed by SpringSource, Spring is an application framework that Rod Johnson wrote with flexibility in mind. Unlike many other frameworks before it, Spring wasn't explicitly designed for one type of application or development style.

Instead, it's adaptable enough to work across different architectures and types of applications. To achieve its flexibility, Spring gives developers a wide range of programming options.

Advantages of Spring Framework

• Lightweight Framework
• Flexible libraries
• Powerful abstractions to JEE specifications
• Declarative support
• Dependency injection

Top brands using Spring Framework:

• Accenture
• Deleo Korea
• Zalando

2. Java Server Faces

This framework, built by Sun Microsystems, was once used to create interactive web applications for desktop users. Later on, the development team scaled it down to suit mobile device technology. It is used to construct dynamic HTML user interfaces that are very similar to desktop applications.

The functionality of these systems includes custom commands and page navigation capabilities, known as action commands. JSF is currently one of four standards included in Enterprise Development Projects under Oracle Development environments.

It creates a standardized approach to many projects on different devices with different operating systems. These include mobile phones, standard computers, and extensive business servers with complex operating system structures.

Advantages of JSF Framework

• Highly pluggable
• Robust event handling
• Rich managing architecture
• Render kit support
• Multiple vendor implementations

Top brands using JSF Framework:

• Scopeland Technology
• Deutsche Kreditbank
• Insoft.

3. Struts Framework

Apache Struts is an open-source application framework for developing Java EE web applications. It was initially created by Craig McClanahan and donated to the Apache Software Foundation in 2000.

Struts combine MVC design pattern, convention over configuration, and architecture-neutral API, thus reducing the development time of java business applications built on it. Struts are widely used for enterprise portal solutions, serving as a server-side component of JavaServer Faces (JSF).

Advantages of Struts Framework

• MVC structure
• Centralized configuration
• Good documentation
• Faster development
• Built-in capabilities

Top brands using Struts Framework:

• Coinatstar
• Spookies
• Aspen

4. Hibernate Framework

Hibernate (sometimes called Hibernate ORM) is an object-relational mapping (ORM) framework for JVM-based programming languages. Hibernate provides database abstraction and gives your applications a uniform data access layer, making it possible to swap databases without having to rewrite every line of code that uses them.

It also provides lazy loading of related data, cache support, primary key generation, and more. To start using Hibernate, you have to specify which database you're using in your application configuration file, then write Java classes that represent your tables in terms of objects with methods for storing/retrieving information from/to those objects.

Advantages of Hibernate Framework

• Open-source
• Lightweight
• Fast performance
• Simplifies complex joins
• Database independent query

Top brands using Hibernate Framework:

• Wealthsimple
• Trade Republic
• Ataccama ONE

5. Vaadin Framework

The Vaadin framework is a client-side, open-source web application framework that is compatible with all major browsers. It is built on top of Google Web Toolkit and thus delivers rich features in a fast and reliable way. While it mainly makes modern web applications and business dashboards, it can also create animated desktop applications in Java.

Available under the LGPL license, Vaadin brings in many benefits to both businesses and individual developers. The wide range of supported browsers enables you to reach larger audiences. At the same time, its unique UI components give you plenty of opportunities to add high-quality design elements to your apps.

Advantages of Vaadin Framework

• Fully object-oriented
• Plug-in supports
• Smooth integration
• Multiple components & layouts
• Gentle learning curve

Top brands using Vaadin Framework:

• Motorola
• JPMorgan Chase
• Dell

6. Play Framework

Play is a high-productivity web framework for Java and Scala. Play is based on a lightweight, stateless, web-friendly architecture. Built on Akka, Play provides predictable and minimal resource consumption (CPU, memory, threads) for highly-scalable applications.

Leveraging both HTTP and HTML5 WebSockets, Play Framework offers developers an easy way to build scalable real-time apps in Java & Scala. For that purpose, it takes care of many low-level details such as connection management and protocol implementation so you can focus on business logic instead of dealing with infrastructure code.

And thanks to its reactive programming model, Play provides developers with tools for asynchronous programming in a simple manner, so your code remains clean when it comes to event handlers & callbacks without much boilerplate or repetition.

Advantages of Play Framework

• Lightweight
• Stateless
• Web-friendly
• Highly scalable
• Minimal resource consumption

Top brands using Play Framework:

• LinkedIn
• Accenture
• Glovo

7. Dropwizard Framework

Dropwizard is a new framework that helps you build simple, high-performance, RESTful web services with minimal effort. It borrows ideas from other frameworks and packages them together in a simple, coherent whole. If you are familiar with JUnit or Maven, then you will feel right at home using Dropwizard.

The code samples are available in both Java and Scala. Don't worry if you are not familiar with either of these languages because it should not take long to become acclimated to them.

Advantages of Dropwizard Framework

• Supports multiple independent libraries
• Ops-friendly
• Highly modular
• High performance
• Rapid prototyping

Top brands using Dropwizard Framework:

• CRED
• Upwork
• Rent the Runway

8. Blade Framework

The Blade is a minimal, open-source framework for creating modern web apps using Groovy on top of any Servlet container. The Blade extends Groovy with support for annotations and domain-specific languages that make it easy to build highly expressive APIs quickly.

At its core, Blade is inspired by Spring MVC's template model but also allows developers to leverage Groovy features like builders, meta-programming, AST transformations, and dependency injection to improve productivity without sacrificing power or performance dramatically.

It provides full support for annotation-based or convention-over-configuration style development with an intuitive DSL that allows you to create dynamic HTML views directly from your controller code.

Advantages of Blade Framework

• Lightweight
• MVC framework
• Robust pattern
• Highly modular
• Zero invasive receptors

Top brands using Blade Framework:

• Django
• Meatier
• Vapor

9. Jersey Framework

Jersey is a lightweight framework that makes it easy to build RESTful web services. It gets used in several high-profile projects, including Twitter's Bootstrap, Google App Engine, etc. Jersey also provides a simple JAX-RS client API for in-browser applications or other clients that access web services.

The complete source code for Jersey is available under an Apache 2 open source license, and there are no runtime dependencies on third-party libraries.

Advantages of Jersey Framework

• Lightweight
• Open-source
• Fast performance
• Personal APIs
• Additional features & Toolkits

Top brands using Jersey Framework:

• Bodybuilding.com
• SnapEngage
• Neko

10. OSGi (Open Service Gateway Initiative)

While other popular frameworks, such as Spring and Hibernate, we can't talk about modern Java frameworks without discussing OSGi. If you've been into Java development for a while, you've probably heard about OSGi. It is one of the most influential & flexible open-source frameworks for developing distributed applications.

The underlying framework allows components to communicate with each other in very flexible ways by enabling them to publish services for others to consume. This functionality has made it extremely popular among developers over time and makes it one of our top 15 best java frameworks list.

Advantages of OSGI Framework

• Supports rapid project development
• Rapid testing
• Service-oriented architecture
• Facilitates quick modifications
• Creates portable applications

Top brands using OSGI Framework:

• Liferay
• Business File Manager
• SYSTHEMIS AG

11. GWT

Google Web Toolkit (GWT) is a set of tools that allow you to use your favorite programming language to quickly build complex web applications without having to worry about configuring servers or writing JavaScript code. It also allows for high-speed development by compiling .java files into .gwt.HTML pages at run time.

Google Web Toolkit is handy when you're building AJAX applications with your favorite IDE ‘like IntelliJ IDEA, Eclipse, NetBeans, and more. GWT was initially designed for Google's internal use, but it was released as an open-source tool under Apache 2.0 license in 2006.

Advantages of GWT Framework

• Creates highly responsive web apps
• Built-in IDE support
• Standard Java static code
• Optimizes generated code
• Generates cross-browser code

Top brands using GWT Framework:

• SnapEngage
• Whatfix
• Navatom

12. Spark Framework

Apache Spark is a modern, lightning-fast framework that allows developers to work in a multi-paradigm and build fast and efficient programs in various languages such as Scala, Java, and Python. It has diverse functionalities in machine learning and data analysis, streaming data, etc., with high performance on Hadoop and non-Hadoop environments.

Additionally, Spark has high flexibility for Hadoop users because of its compatibility with other powerful technologies such as SQL and NoSQL databases. It enables programming in JVM languages such as Scala or Java with support for structured sources like Hive tables or SQL databases through RDD (Resilient Distributed Datasets).

Advantages of Spark Framework

• High processing speed
• Powerful Analytics
• Advance libraries
• low-latency in-memory data processing capability
• Supports dynamic development

Top brands using Spark Framework:

• Revolut.
• Payjinn.
• AfricanStockPhoto.

13. Vert. x

Vert. x is a tool for creating reactive web applications in Java and Scala. You can also use it to replace RESTful calls with no network latency, ideal for data streaming applications, NoSQL databases, and large-scale distributed systems.

Vert. x gives you all you need to build an event-driven application, allowing you to develop using asynchronous non-blocking input/output (NIO) APIs by utilizing many frameworks such as Netty or Jetty.

The Framework itself abstracts away thread management and synchronization issues, giving you a more straightforward way to work with concurrency issues in your code.

Advantages of Vert. x Framework

• Event-driven runtime
• High performance
• Scalable apps
• Reduces overheads
• Well suited to modern apps

Top brands using Vert. x:

• Bitpanda
• Trade Republic
• Braincube

14. Richfaces Framework

Richfaces is a popular Ajax-based UI framework incorporating many industry standards into its design, making it very attractive to developers. It supports rich AJAX for web pages, 3D charts and graphs, drag-and-drop capabilities, sortable lists, and data grids with live updates.

As a complete MVC solution, Richfaces works well with many Java applications. Since Richfaces is an open-source project hosted on Google Code, developers are encouraged to contribute to its development by reviewing existing code or submitting their additions.

Advantages of Richfaces Framework

• Open-source
• Adds ajax capabilities to JSF
• Enhances UI
• Facilitates custom rich components
• Multiple libraries

15. PrimeFaces

PrimeFaces is an open-source, highly customizable JSF (JavaServer Faces) UI component suite for building rich internet applications. PrimeFaces library includes 140+ UI components. It's easy to use, mobile-ready and tested across all major browsers with complete documentation.

The latest version of PrimeFaces is 5.1, released on July 9, 2017, along with seven more bug fixes and improvements since the previous release of the 5.0 version. Just like other frameworks available on the Java ecosystem, it's an extensible framework using a plugin system that employs more than 20 open source libraries like jQuery or Google Guava.

Advantages of PrimeFaces Framework

• Easy to use
• Open-source
• Adds Ajax capabilities to JSF
• Good Documentation
• Multiple libraries

Final Words

It's clear that there are many different frameworks for Java developers to use, but one stands out above all others. Spring offers developers a flexible environment that helps them build robust applications that can scale quickly as your company grows. Spring Framework 4 was recently released and brought many improvements over version 3.

For example, it's possible to write code once and run it on both Servlet containers and Web servers using the new JavaServer Faces technology introduced in version 4.

Also, with dependency injection to manage dependencies between classes, you can make adjustments easier by simply adding or removing components without disrupting existing logic.

Because of these features, we've decided to give Spring Framework 4 our highest recommendation as to the best Framework for creating enterprise-level web applications with Java.

FAQs

Question: What is a framework?

Answer: A software framework is an abstraction in which software providing generic functionality can be selectively changed by additional user-written code, thus offering application-specific software.

Programs written in a low-level language, such as C, often lack pre-existing software libraries that provide proper functionality. In other cases, programmers may find it challenging to utilize existing libraries because of political reasons or simply a compatibility issue with different library versions.

In both cases, using a framework allows one to develop applications without reinventing or customizing core services or common infrastructure.

Question: How can I choose the best Java Framework?

Answer: The purpose of a framework is to simplify development by standardizing components that are complex or time-consuming to create. Developers can focus on what makes their application unique rather than reinventing wheels every time they start a new project.

Each Framework has its strengths & weaknesses, but here are some things you should consider when making your choice: platform support, community, accessibility, documentation, ease of use, longevity, and maintenance.

Some frameworks work better for enterprise applications, while others are more appropriate for smaller businesses with fewer technical resources. A few aren't even geared toward business applications at all – they're targeted for use in particular markets like gaming or robotics.

When it comes to using frameworks, ask yourself these questions:

• What does it bring to my team?
• Do I have time for it?
• Is my current process streamlined enough to make room for another framework?

And finally, if you're looking into new technology or processes in general (even something simple like replacing an older printer with a newer one), talk with your team and get their buy-in before implementing anything new.

Question: How many Java frameworks are there?

Answer: There are more than 30 frameworks for the Java programming language. However, most of them are compatible with other programming languages besides Java.

Question: Why have frameworks become an invincible part of the development projects?

Answer: A framework is a way to structure your code. It's a sort of skeleton, with all of its joints already put together for you. If you're working on a non-web project, several good frameworks for various languages will help keep your code organized and help you develop more quickly.

In my experience, they also enable teams of developers to work together more effectively by providing a standard set of protocols and procedures across each member.

Question: Is Spring an open-source framework?

Answer: Yes, Spring is an open-source framework. The project was created by Rod Johnson in 1999 and hosted on SourceForge. It went fully open source in 2005, after which it quickly became one of the most popular frameworks for enterprise applications development. And since then, it has only enhanced its relevance and popularity within organizations both large and small.

The post Top 15 Java Frameworks to Use in 2022 appeared first on Datafloq.

Today, more than ever before, web development focuses incredibly on user experience (UX). Aiding this change are revolutionary technologies like Artificial Intelligence (AI) and Machine Learning (ML). The underlying idea behind these technologies is to make machines think and work like humans so that they can cater to the needs of humans comprehensively.

This article will take a look at how the power of AI aids the web development process. We will particularly focus on three main aspects of development – coding, user experience, and testing.

Simplify Coding

Codes create the anatomy of a website. Although an interesting and important aspect of web development, coding is quite complicated and requires much time, attention, and effort. With the implementation of AI, much refinement can be brought to coding. By leveraging the benefits of AI, codes can be made fast, error-free, and optimized.

Self-learning algorithms can assist in identifying, correcting, and updating errors in codes without human intervention. AI can also automate performance improvement by finding code segments that are slowing down the services and tweaking them to improve the code quality. Moreover, several AI-powered low-code tools allow for development that requires minimal or no coding, yet delivers outstanding results. This means, even if you are not an expert in web development languages, you can create functional websites.

Improve User Experience

To render an exceptional user experience for a website, several prospects need to be considered. Some aspects that influence UX- like customer analysis, content development, and customer experience- can greatly improve with the implementation of AI.

In customer behavior analytics, AI-powered tools can contribute significantly towards gathering insights and delivering reports regarding user expectations and browsing patterns. Using cognitive analysis and statistical analysis can help you predict users' experiences and serve them according to their interests.

The role of content in delivering a great user experience is often underlooked. Content is a powerful aspect- one that can even single-handedly create an impactful user experience. AI is revolutionizing content development with tools that can automatically generate content that is relevant, data-driven, and of top quality. With minimal input from humans, the AI content tools can create unique content in all formats- from web content, blog posts, to even meta descriptions.

The customer experience (CX) and UX intersect in areas like customer service, sales analysis, product delivery, etc. The use of AI-powered chatbots is proven to have a monumental impact in these areas. AI Chatbots provide fast, accurate, and personalized responses to user queries. They interact with users naturally, thereby eliminating the feel of communicating with machines (which is what AI is all about!)

Automate Testing

Testing is a crucial part of any development process. To ensure that a website is functioning as expected and there are no glitches, developers spend an inordinate amount of time conducting quality assurance and testing. Although AI cannot eliminate the need for human intervention in testing as of now, it can minimize the involvement.

By automating the basic testing processes that are mandatory for every development using AI-driven tools, human effort can be directed towards conducting advanced testing. AI-powered basic testing will save developers huge amounts of time, which they can utilize for more comprehensive bug-hunting.

Summing Up

Web development is constantly evolving and keeping pace with the shifts can be challenging, at times. But with AI providing extensive support for the web development process and even promising more contributions in the future, the challenges can be navigated quite smoothly.

• AutoML, a machine learning software developed by Google can create self-learning code and is found to be better at coding than the researchers that created the software!
• Web development frameworks can be integrated with AI libraries (for example, the Django-ai library for Django framework) to leverage the data from a project and integrate statistical models in it.
• AI content generators (like Jarvis) can build high-quality, SEO-optimized content in different languages and various formats.
• AI-powered testing tools (like TestCraft and Functionalize) can meet the needs of continuous integration and delivery.

Implementing AI strategies in web development is proving to deliver faster and better results. AI algorithms are getting better every day, hinting at a future that is greatly promising not just for web development but for the digital ecosystem as a whole.

The post How Artificial Intelligence is Influencing Web Development appeared first on Datafloq.