The term technology stack has a broad definition. But the most simple one is a group of programming languages, libraries, frameworks, programs, platforms, and servers used to develop a product. It is very important to select the right one from the beginning or will find yourself having to migrate later on.

A technology stack is what will serve as the foundation of your startup. Also, remember to consider the front and back end when considering different technologies. For example, which programming languages you choose will determine many things, like the type of professionals you have to hire. You have to consider many factors before choosing the right stack.

Budget

Startups generally have a limited budget. That’s why you have to make good decisions on how you will spend that money. Part of the tech stack is the programming languages. Thus, you should decide if you will buy a license for a language or just go with open-source like Python and JavaScript. You should consider the differences between open-source and licensed and choose the one that adapts best for the startup’s future.

The programming language also depends on the type of product you are building. But you should choose something that is fairly popular, which will make finding a developer for it easier. That is another part of the budget. To develop the product you want, you will probably need a team of developers. And if you choose to work with a less popular or newer programming language, you will have to pay more to find the right developer.

If you choose popular languages, there would be more developers to choose from. To summarize, you can choose a popular programming language that is lasting. It will be terrible if the language becomes outdated too fast, and you have to rewrite or migrate your product completely.

Scalability

Another important factor to consider is scalability. You should build your startup with the future in mind. Will the tech stack hold if you have to manage 100,000 users? How about 10 million? Many startups have failed because their product crashes on launching day when they get more attention than expected. This isn’t a problem exclusive to startups.

Disney+ launched back in 2019, and it crashed on launching day when they got a higher demand than they were expecting. Thus, you should choose a scalable tech stack that can grow with the startup’s hopeful success. Also, having scalable technology is cheaper in the long run when you have to grow or scale down.

Time to Market

As mentioned before, startups have a limited budget. That’s why you have to consider the time when choosing a technology stack. For example, if you choose a programming language that your team isn’t familiar with, you will need more time to retrain your existing team or to hire new software developers.

If your budget lasts a long time, you could take the extra time with an unfamiliar language because the benefits outweigh the drawbacks. But if you take too long to launch your product, a competitor could do it first, and you lose your momentum. Thus, consider the time you have on your current budget when choosing the right stack.

Size and Type

Finally, the last thing to consider when choosing a tech stack is your project’s size and type. Startups should always focus on creating a minimum viable product first. Don’t try to build from the beginning a product for 10 million users. Instead, build the MVP with a good foundation for later growth.

The project’s type could be a marketplace, web application, mobile app, or whatever else your idea is. This factor is one of the most important when deciding which tech stack is right for your startup. A good strategy is to look for established companies that offer a similar product and see what they are using.

In Summary

The technology stack is the foundation for your startup. If you make a poor choice, it could mean the failure of your company. You should consider budget, scalability, time to market, and project size and type when choosing the right stack.

The budget will determine how much you can spend on programming languages, frameworks, cloud computing, and even your team. It will also define how long it can take to launch your product. But the project type is the most important factor when choosing the right set of technologies.

We are driving towards a mobile-first world and businesses worldwide. A total of 5.22 billion people use mobile and 4.66 billion people have access to the internet. Entrepreneurs around the world are scrambling to develop applications that are innovative and based on fresh ideas. All types of businesses across the scale have set budgets to develop the most compatible mobile applications to greet their customers’ needs and preferences.

At present, React Native and Xamarin are ruling the roost. These two heavyweights of cross-platform development, React Native and Xamarin, implement the functionality of “Write once and Deploy anywhere.” Both of these open-source cross-platform frameworks are endorsed by the development fellowship to build high-performing apps while saving coding energies and time.

But not anymore.

When asked which two biggies have an upper hand in the enterprise, people seldom answer. Both React Native and Xamarin are backed up by certain merits and pitfalls, creating a puzzling situation where choosing the best between the two becomes a tad tricky. So, we are listing some key features that unveil the contrasts existing between React Native and Xamarin.

What is React Native?

React Native is an open-source, cross-platform mobile app development framework created by Facebook in 2015. It is designed to enable developers to use JavaScript and React along with native platform capabilities to build mobile apps. That enables developers to develop mobile applications for Android and iOS devices with one tech stack. It is backed by the social media giant Facebook, with over 50 dedicated engineers working on the framework at present.

What is Xamarin?

Xamarin is a popular, open-source cross-platform app development framework. It came into existence in the year 2011 and was later acquired by Microsoft in 2016. It works through the Mono framework to communicate with the Application Program Interface (API) of common mobile device functions, leveraging a shared code to forge compatibility and usability across multiple platforms or operating systems. The framework is currently being used by more than 15,000 fellowships worldwide hailing from diverse enterprises such as energy, transport, and healthcare.

Comparison of the capabilities and key features of React Native and Xamarin:

1. Performance

Performance matters!

React Native

It provides near-native performance, meaning the apps built with it are fast. But keep in mind that true native performance can be achieved only with native languages such as Java, Objective-C, and Swift.

Xamarin

Like React Native, Xamarin also gives a near-native performance. But it utilizes stage explicit equipment quickening to give extraordinary application speed.

Xamarin wins!

2. Popularity

React Native

It is open-source. It has been basking in the victory especially for the developers when it comes to application development. It is more popular than Xamarin.

 Xamarin

It is closed-source and only maintained by Microsoft. but still, it’s a popular choice when it comes to demand for the best cross-platform development. It significantly contributes to rendering the native UI functionality.

React Native wins!

3. Development Environment

React Native

It gives developers a lot of flexibility. It lets them pick their improvement condition. It allows developers to choose the IDE/ text editor they love the most. Generally, Expo is used to debug and build React Native apps. The hot reloading feature of React Native is a plus that eliminates the need for full application reloads after any modification in the code.

Xamarin

On the flip side, Xamarin is more powerful and friendlier. The developers have to work in Visual Studio. That’s the only option available. It provides an Integrated Development Environment and gives many useful tools, controls, and layouts that make mobile app development simpler and smoother. It allows developers to write code for an iPhone app on Windows and compile it for Mac.

Xamarin wins!

4. Community Support

React Native

This framework has a huge network of developers globally. There is an immense number of learning materials accessible on the Internet for React Native. So you can learn it practically by utilizing the online courses, instructional exercises, and recordings accessible on the web. It came in 3rd place for the most wanted framework.

Xamarin

Though Xamarin is only two years younger than React Native, it doesn’t make any difference when it comes to great network support from the developer community. It came in 11th for the most wanted framework.

React Native wins!

5. Market Share

React Native

React Native is used by many great companies and startups. The well-known companies using React Native include Facebook, Facebook Ads Manager, Instagram, F8, Facebook Analytics, Skype, Pinterest, Bloomberg, Uber, Walmart, Tesla, Artsy, Chop, Discord, Vogue, etc.

Xamarin

Backed by Microsoft, Xamarin has a community of over 700,000 developers that come from 37,000 different companies. Some of the top companies using Xamarin are Honeywell, Samsung, Slack, BOSCH, Cognizant, JetBlue, etc.

It’s a tie!

Xamarin VS React Native: The Finishing Remarks

Winding up, the demand for cross-platform app development is seeing a huge surge. Both Xamarin and React Native reflect traits to be the perfect app development tool for businesses in 2021. Is React Native better than Xamarin? Please note that the choice between the two ultimately comes down to your business objectives, project requirements, and tech stacks. However, in today’s scenario, React Native has proven to be a promising framework. It has steady growth, flawless code structure as well as huge community support. It all boils down to your unique needs, and which one of these frameworks can fulfill them the best.

So are you looking for any of them for your next project? Our experienced developer will provide you with the best solution for your project, you just need to drop a line and we will be back within 24hrs of business days.

Most readers in the field know of SaaS (Software as a Service), IaaS (Infrastructure as a Service), and PaaS (Platform as a Service). But have you heard of XaaS?

Looking at today’s business models, As a Service (aaS) models are easy to spot. Once, we had cassette tapes and CDs. Today, we have online music subscriptions. Not only do you pay less with a music subscription service, you now have on-demand access to exponentially more content than you could afford if you had to buy each album individually. You are also no longer responsible for locally storing, organizing, and maintaining an enormous library of CDs.

Various as-a-service businesses are capitalizing on this by ‘servitizing’ products, such as customer relationship management (CRM )service provider Zendesk and Alibaba Cloud VMware Solution.

The popularity and proliferation of “as a Service” models have grown exponentially over the past few years but aren’t necessarily a new concept. Dating back to early computing days with “time-sharing” systems, businesses have been looking for ways to reduce hosting fees and eliminate the management of on-premise servers. The rise and popularity of cloud computing, along with the expansion of internet-connected devices, has accelerated the “as a Service” world we live in today.

It sounds like a lot to take in, but don’t worry—we’ll break it down for you. This blog will cover what XaaS is, and its features.

What is XaaS (Anything as a Service)?

Anything as a service” (XaaS) describes the delivery of anything as a service. It recognizes the vast number of products, tools, and technologies that vendors now deliver to users as a service over a network — typically the internet — rather than provide locally or on-site within an enterprise.

XaaS in the cloud can be considered an umbrella of services that can be a perfect blend of both tangible and virtual. Some of the services it encompasses include:

• Analytics-as-a-Service
• Backup-as-a-Service
• Backend-as-a-Service
• Network-as-a-Service
• Content-as-a-Service
• Infrastructure-as-a-Service
• Software-as-a-Service
• Storage-as-a-Service
• Humans-as-a-Service (temporary and permanent staffing solutions)
• Monitoring-as-a-Service
• Testing-as-a-Service
• Blockchain-as-a-Service
• Platform-as-a-Service
• Marketing-as-a-Service
• Security-as-a-Service

Features Of XaaS

Considered the ultimate cloud computing model, Anything-as-a-Service adds the ‘X’ factor to business modernization in any sector that thrives on smart solutions. Companies that need new technology innovations or want to scale existent solutions can easily choose the right set of services to leverage for their needs and check their availability based on their budget.

The three key features that influence the success of the XaaS market include:

• Availability of the offer for users
• Declared levels of service
• Monitoring, measuring, and analysis systems

Nowadays, many firms are going towards Multi-Cloud and Hybrid solutions, which provide a useful platform for easy services in XaaS. So are you looking for any of the services then just drop a line and we will be back within 24hrs of business days.

In the last decade, many companies have started implementing Artificial Intelligence (AI) to improve their services and products. This has led to AI being improved significantly during the previous year. Nowadays, AI is capable of accomplishing a great number of tasks in different fields, just like skilled professionals. As a result, many jobs have been replaced by automated AI products.

AI has had a significant impact on the world we live in, which is making enabling a transition into tech more important.

Major companies are using AI to make self-driven cars, provide personalized experiences, and provide advanced help in certain industries. Now products such as smart refrigerators, automated emails, and intelligent virtual assistants have come to life.

AI has made significant changes that have allowed companies to grow faster. Here are some advantages we should consider concerning how AI is making tech transition crucial for some businesses.

1. Reduced Occupational Accidents

With the use of machine learning and AI, companies have been able to automate some of their processes. There has been a large decrease in the number of occupational accidents. This is mostly because machines are now being tasked with some of the more dangerous jobs at the workplace.

AI robots can accomplish tasks that cannot be done by humans without help. Some examples of this include going to Mars, exploring the deep ocean, or even defusing a bomb. However, these machines still depend on a developer who writes the code that adapts to the learning capability systems.

An AI machine with errors or bugs in its code could cause a disaster, such as an increase in workplace accidents. In that case, hiring Quality Assurance Engineers can be beneficial.

These engineers are responsible for making sure that the code from other developers meets specific standards. They guarantee that everything goes smoothly and the chance of human error is reduced.

2. All-day Availability

As AI machines and programs do not need to rest, they are available 24/7. With this in mind, many companies have been using AI and machine learning to increase productivity.

For example, the healthcare industry has been using AI-powered programs to register and organize queries. In the same way, many hotels are using AI chatbots to provide quick responses to customers all over the world. These chatbots have allowed companies to offer personalized and efficient services to their customers.

Now that there is no waiting time to get a response anymore, customers feel more engaged with the attention provided.

3. Helping with Repetitive Jobs

No matter how much you try to avoid it, repetitive tasks will always be a part of life. At work, we perform many of these tasks which can be quite time-consuming. This includes sending emails, organizing files, and verifying documents for errors. However, using AI-powered programs to take care of these tasks allow employees to focus on other areas of their job. Your employees’ performance will be higher as they now have more time.

Some Web Developers have been implementing AI on their websites to improve performance. Imagine an online help center full of requests submitted by its users. An individual would spend a great deal of time organizing and analyzing all of these requests. Instead, AI can efficiently take care of this in much less time so that the experts can focus on interpreting the gathered data.

4. Helping with Daily Tasks

AI and machine learning have allowed companies to increase their productivity and develop smart apps that help their consumers. Many of these life companion apps came from Mobile Developers from larger companies such as Apple, Amazon, and Samsung.

Some of the more frequently used apps—such as Siri, Alexa, and Bixby—can make phone calls, reply to emails, set appointments, and even control the user’s smart home.

A few years ago, using apps that could help you search for information and aid you in your daily life was unthinkable. However, today it’s more than possible thanks to machine learning and AI. Alexa, Siri, and Bixby are all able to learn from experience. This allows their performance to improve as long as you continue to use them.

Conclusión

AI has changed just about every aspect of our lives. It has been implemented in so many fields that enabling a transition into tech is mandatory. Future products and services will be able to combine the best of smart machines and the real world.

Soon, living in a world among human-like programs and machines will stop being a thing of science fiction.

Soft skills are more like your personal attributes and interpersonal skills. Beyond your raw talent, they’re the aspects of your personality that make people want to work with you.  Even if you’re a new designer, you can harness soft skills from your past life experiences and roles. Others might not come as naturally, but they can—and should—be worked on if you want to develop both professionally and personally.

To be a great designer, you need to be creative. But did you know that along with the slew of

technical design skills you might already possess (like composition, color theory, and software proficiencies) you need something called ‘soft skills? Yep, they’re a thing! And just like knowing your way around Photoshop, they’re critical to your success. Remember soft skills are an essential part of design careers because we are ultimately problem solvers and communicators.

Soft skills are the traits and behaviors that make a job candidate a well-rounded employee. Soft skills include characteristics that can be hard to measure, like creativity, good communication, and critical thinking. Because these skills apply to careers in many different industries, they’re sometimes referred to as transferable skills.

5 skills will take you beyond the eyes of your clients, and they are:

• Creativity and innovation

This one may seem a little obvious, but it also illustrates your entire career. As a graphic designer, you’re expected to come up with original ideas, think critically, and have a creative eye. They must think outside the box to develop innovative ideas and design concepts. You’ll be asked to make various versions of the same thing, to finish something quicker than you anticipated, and to create something you’ve never tried before. It sounds like a lot of squeezes because it is. But if you can be innovative in your thinking and your execution, it lessens the weight you might be feeling on your shoulders. All of this involves creativity, as well as creative problem-solving skills.

• Aesthetics
• Attention to Detail
• Balancing Artistry with Audience Appeal
• Perceptivity
• Visually Representing Ideas
• Sketching
• Brainstorming
• Communication

As a designer, it’s your job to communicate your client’s perception in a graphic that’s aesthetically attractive and functional. While that sounds straightforward, you’ll find a lot of hiccups along the way despite your expertise. The design is not the only thing that should be communicating clearly but you should know how to communicate efficiently with others.  This is a soft skill that is becoming just as essential as many technical skills in the designer’s toolbox and a vital part of getting ahead in design.

A graphic designer’s skill set would be incomplete without the ability to communicate well. Stay ahead of the curve by hone your pitch or conveying an idea for a design with a friend.

• Confidence
• Consultation
• Customer Service
• Establishing Rapport
• Interpreting Artwork for the General Public
• Understanding Clients’ Artistic Preferences
• Interpersonal
• Active Listening
• Receiving Constructive Criticism about Artwork
• Sales
• Verbal Communication
• Collaboration
• Written Communication

• Problem-solving

One of the key soft skills a graphic designer must possess is the art of problem-solving. Problem-solving doesn’t always take comprehensive brainpower. It may be as simple as changing a shade of green to make it a little lighter. Most of the issues while dealing with a stubborn client can be resolved simply by being open-minded to accommodate their requests. Regardless of how big or small the challenge is, remember to stay calm, open-minded, and creative.

• Time Management

The designers who work as part of a team need to have excellent time management skills to ensure that the different design projects they are tasked with are all completed in good time. This also includes problem-solving skills allowing you to respond quickly to urgent requests or tasks that might come up mid-project. This is where good time management comes in. After all, even if your portfolio promises great things, great design requires some time.

• Critical Thinking
• Deadline Management
• Decisive
• Design Strategy
• Organizational Skills
• Multitasking
• Prioritizing
• Problem-solving
• Flexibility

• Technology

Graphic designers have to master assorted forms of technology in today’s world. Firstly, they need to be comfortable with design software, such as Quark, InDesign, and Adobe. The skills mentioned are just the tip of the iceberg. These skills are the basic stepping stones you need to capture as you climb the ladder of a professional graphic designer. A graphic designer’s technical skills should relate to their ability to physically complete the task at hand.

Conclusion

Of course, these are not the only skills a graphic designer needs, but they’re a good foundation. Essentially, you should be able to use your creativity, problem-solving skills, and communication to create gorgeous designs with the technical skills that you’ve acquired over time as a designer. If you’ve got these skills down, you’re definitely on your way! So are you looking for a graphic designer who has all these soft skills, then just drop a line and will provide you the best graphic designer within 24hrs of business days.

Blockchain technology has recently effectively gained widespread attention for innovating business processes. It is shifting the paradigms of our business world at a rapid rate. Even though there are some mixed feelings toward this technology, no one can entirely underestimate its role in the global economic landscape. It is poised to dramatically transform commerce across every industry from financial to legal services, agriculture to healthcare, and more.

The technology first came into the spotlight with the creation of Bitcoin in 2009. This technology that underpins Bitcoin is finding applicability across a wide variety of use cases. The form of technology allows digital information to be exchanged without any external users or middlemen. It is an imaginary data structure that is composed of “packets” or “blocks” of information. In the case of the analogy, these blocks are represented by the bills.

Wondering why Blockchain has gained so much popularity in recent years. Here we bring the top Blockchain features that make it popular!

What is Blockchain?

Blockchain technology is most simply defined as a decentralized, distributed ledger that records the provenance of a digital asset. Each block in the chain contains several transactions, and every time a new transaction occurs on the blockchain, a record of that transaction is added to every participant’s ledger.

Let’s dive a little deeper into the features of blockchain!

• Immutability

Immutability is undoubtedly one of the most significant blockchain features. Immutability means something that can’t be changed or altered. Once you have agreed on a transaction and recorded it, it can never be changed. You can subsequently record another transaction about that asset to change its state, but you can never hide the original transaction. This gives the idea of the provenance of assets, which means that for any asset you can tell where it is, where it’s been, and what has happened throughout its life.

• Decentralized System

This is one of the key features of blockchain technology that works perfectly. Decentralized technology gives you the power to store your assets in a network which further accessed by the means of the internet, an asset can be anything like a contract, a document, etc. Through this owner has direct control over his account by the means of a key that is linked to his account which gives the owner the power to transfer his assets to anyone he wants.

Blockchain technology proves to be an effective tool for decentralizing the web. It does possess the power to bring massive changes in industries.

• Enhanced Security

Blockchain technology has better security because there is not even a single chance of shutting down the system. There’s no way to crack the code. Furthermore, if anyone wants to change any value in the block, it will generate a completely different outcome that won’t be linked to the original change. Additionally, every block comes with a unique hash ID. However, changing the hash ID is impossible.

Also, to make a blockchain transaction, you’ll need help from both public and private keys. Figuring out other users’ private keys is also impossible.

• Distributed Ledger

Another cool feature of blockchain is the distributed nature of the system. In reality, all the nodes maintain the ledger, and so the overall computational power gets distributed among them. Thus, promoting a good outcome.

In the case of the public blockchain, everyone can see the ledger without any issues. However, in private, things change a bit, but still, it’s viewable. Due to the nature of the technology, it’s more efficient and offers other benefits as well –

• High response time for any malicious activity because any change in the ledger is detectable relatively faster. So, it’s easy to track what’s the issue.
• The nodes act as the verifiers, and so it offers them a role of participation.
• It gets rid of any favors in the network. And so, everyone will get an equal amount of privileges in the system.

• Consensus

Consensus is a crucial factor when it comes to blockchain. Without consensus, the blockchain system won’t work. In reality, consensus algorithms help the network make decisions. Without any consensus, no blockchain can make a fair judgment of the blocks being added. Before one can execute a transaction, there must be an agreement between all relevant parties that the transaction is valid. For example, if you’re registering the sale of a bike, that bike must belong to you or you won’t get an agreement. This process helps keep inaccurate or potentially fraudulent transactions out of the database.

Conclusion

Blockchain technology isn’t just another hype that people forget after a few days. With all its blockchain features and applications, we can safely assume that it’s here to stay. All the blockchain’s important features are making a whole nother level of impact on the web.

And why wouldn’t it? It’s infused with all sorts of new techs. Although blockchain is giving rise to a lot of controversies, still if people can utilize the ideology behind all benefits of blockchain they can make a brighter and shinier future for everyone. Not to mention, Blockchain can change the world. So if you are looking for any kind of service, just drop a line and be back within 24hrs business days.

Databases are evolving. As the market is flooded with many types of databases and this creates a dilemma for architects to choose one that gratifies the project’s requirement. The ‘One size fits for all’ approach is no longer applicable. Developers need to judge the relevance and applicability before adopting any of the databases.

But as the emphasis on big data grew, developers started to shift their focus from the structured to unstructured approach. The different databases i.e traditional SQL with modern NoSQL are scrutinized below to understand when to implement them.

Let’s spill the bean!

What is SQL?

SQL stands for Structured Query Language. SQL lets you access and manipulates the database. It’s an ANSI (American National Standards Institute) standard. A query language is a kind of programming language that’s designed to facilitate retrieving specific information from databases, and that’s exactly what SQL does.

Advantages of SQL:

• Faster Query Processing
• No Coding Skills
• Standardized Language
• Emergence of ORDBMS
• Portable

Disadvantages of SQL :

• Complex Interface
• Partial Control
• Expense

What is NoSQL?

NoSQL stands for Not Only SQL. The term NoSQL was first coined by Carlo Strozzi in 1998 to name his lightweight, open-source, non-relational database that did not expose the standard SQL interface. Then the term was reintroduced by Eric Evans in early 2009. They are widely popular today owing to their ability to scale out or scale horizontally and adeptness at dealing with a rich variety of structured, semi-structured, and unstructured data.

Advantages of NoSQL:

• Elastic scalability
• Cheap, easy to implement
• Doesn’t required pre-defined schema
• Replication
• Easy to distribute

Disadvantages of NoSQL:

• Less Community Support
• Standardization
• Interfaces and Interoperability

SQL Vs NoSQL: Which one to choose?

Key

SQL

NoSQL

Database Relational database Non-relational, distributed database Model Relational model Model-less approach Scheme Pre-defined Schema Dynamic schema for unstructured data Based Table based databases Document-based or graphed or wide column store or key-value pairs databases Scalable Vertically scalable Horizontally scalable Usage Uses SQL Uses UnSQL (Unstructured Query Language) Datasets Not preferred for large datasets Largely preferred for large datasets Hierarchical data  Not best fit for hierarchical data Best fit for hierarchical data Follows Emphasis on ACID properties Follows Brewer’s CAP theorem Community  Excellent support from vendors Relies heavily on company support Supports Supports complex querying and data-keeping needs Doesn’t have good support for complex querying Consistency  Can be configured for strong consistency Few support strong consistency Examples Oracle,DB2, MySQL, MS SQL, PostgreSQL,etc MongoDB, HBase, Cassandra, Redis, Neo4j, CouchDB, Couchbase, Raik, etc.

Conclusion

There are plenty of decisions to be made when thinking about your cloud data storage. One of the most important decisions is whether to go with a SQL or NoSQL database as your primary database and whether you may need both to meet your needs. We hope this blog helps clear the air on what you need to think about when selecting your database, and the options that are available to you. If you are looking for any services that match your requirements then just drop a line and we will be back within 24hrs.

At first glance, the most important thing in developing a new product is gathering requirements. Though spending tremendous time and resources on development, there can be a mismatch between the required product and the final product. Many times requirements gathering is underestimated on multiple levels. When budgets are thin, timelines are tight, and scope is creeping, requirements documentation tends to be the first deliverable to go and the last deliverable to be considered.

There’s a common refrain that gets uttered at the end of unsuccessful projects: “The requirements weren’t clear.” Fingers start pointing, blame gets thrown around, and no one ends up happy. Thankfully, there’s a simple way to alleviate that problem, and it’s as obvious as it is challenging: requirements gathering.

What is Requirements Analysis?

Requirement analysis is significant and essential activity after elicitation. We analyze, refine, and scrutinize the gathered requirements from the stakeholders to make consistent and unambiguous requirements. After the completion of the analysis, it is expected that the understandability of the project may improve significantly. This is always done in the early phase of any project to ensure that the final product conforms to all the requirements.

This process often involves a set of activities including:

• Requirements elicitation: communicating with customers and users to determine what their requirements to understand user needs
• Requirements modeling: codifying that information in the form of user stories, such as natural-language documents, use cases, user stories, or process specifications.
• Analyzing requirements: determining whether the stated requirements are unclear, incomplete, ambiguous, or contradictory, and then resolving these issues.
• Review and retrospective: Team members reflect on what happened in the iteration and identifies actions for improvement going forward.

Requirements Analysis Techniques:

There are different techniques used for business Requirements Analysis. Below is a list of different business Requirements Analysis Techniques:

1. Business process modeling notation (BPMN)

2. UML (Unified Modeling Language)

3. Flowchart technique

4. Data flow diagram

5. Role Activity Diagrams (RAD)

6. Gantt Charts

7. IDEF (Integrated Definition for Function Modeling)

8. Gap Analysis

Let go into detail

1. Business Process Modeling and Notation (BPMN)

Business Process Model and Notation is used to create process flowcharts, although BPMN has its symbols and elements. These graphs simplify understanding the business process. BPMN is widely popular by business analysts as a process improvement methodology. The biggest profit of using BPMN is that it is easier to share, and most modeling tools support BPMN.

2. UML (Unified Modeling Language)

UML consists of an integrated set of diagrams that are created to specify, visualize, construct and document the artifacts of a software system. It is a useful technique while creating object-oriented software and working with the software development process.  In UML, graphical notations are used to represent the design of a software project.  UML also helps in validating the architectural design of the software.

3. Flowchart technique

A flowchart depicts the sequential flow and control logic of a related set of activities. They are in different forms such as linear, cross-functional, and top-down.  The flowchart can represent system interactions, data flows, etc. Flow charts are easy to understand and can be used by both the technical and non-technical team members. The flowchart technique helps in showcasing the critical attributes of a process.

4. Data flow diagram

This technique is used to visually represent systems and processes that are complex and difficult to describe in text. Data flow diagrams represent the flow of information through a process or a system. It also includes the data inputs and outputs, data stores, and the various sub-processes through which the data moves. DFD describes various entities and their relationships with the help of standardized notations and symbols.  By visualizing all the elements of the system it is easier to identify any shortcomings. These shortcomings are then eliminated in a bid to create a robust solution.

5. Role Activity Diagrams (RAD)

A Role-activity diagram (RAD) is a rule-oriented process model that represents role-activity diagrams. Role activity diagrams are a high-level view that captures the dynamics and role structure of an organization. Roles are used to grouping together activities into units of responsibilities. Activities are the basic parts of a role. An activity may be either carried out in isolation or it may require coordination with other activities within the role.

6. Gantt Charts

Gantt charts are used in project planning as they provide a visual representation of tasks that are scheduled along with the timelines. The Gantt charts help to know what is scheduled to be completed by which date. The start and end dates of all the tasks in the project can be seen in a single view.

7. IDEF (Integrated Definition for Function Modeling)

The integrated definition for function modeling (IDEFM) technique represents the functions of a process and their relationships to child and parent systems with the help of a box. It provides a blueprint to gain an understanding of an organization’s system

8. Gap Analysis

Gap analysis is a technique that helps to analyze the gaps in the performance of a software application to determine whether the business requirements are met or not. It also involves the steps that are to be taken to ensure that all the business requirements are met successfully. Gap denotes the difference between the present state and the target state. Gap analysis is also known as need analysis, need assessment, or need-gap analysis.

Summary

For the success of a project, it is of utmost importance to analyze project requirements at the time gathering as well as throughout the lifecycle of the project. It helps to keep the requirements in line with the needs of the business. A good project requirements analysis process will render a software application that caters to the objectives of the business set forth. Hope this blog was useful and are you looking for such kind of analysts for your next project just drop a line and we will be back within 24hrs.

In recent times, the JavaScript world is moving faster than ever before, and as a prominent software development company. A plethora of frameworks and languages are taking place day by day and we can’t keep up with all of them of this era. More important i.e. Gen Z is the great witnessing of great speed in technological advancements. If the language is considered the alphabet, the framework can be thought of as the phrasebook, enabling the developer to construct sentences and communicate.

Being a tech geek, your most treasured hobby must be looking for state-of-the-art and intriguing technologies to develop more user-engaging applications. If you like coding, you will be going to love the concept of Vue.js. You can implement Vue incrementally and it can work in conjunction with other libraries. There’s a high level of flexibility here that opens up a world of possibilities. Yes, Vue is experiencing a huge amount of growth.

Let’s buckle up!

What is Vue.js?

The Vue.js story begins in 2013 when Evan You was working at Google creating lots of prototypes right within a browser. Evan used handy practices from other frameworks he worked with and released Vue.js officially in 2014. VueJS is an open-source progressive framework for JavaScript used to develop interactive web interfaces. It’s not just for web interfaces, but it is also used both for desktop and mobile app development with the Electron framework.

Vue.js is one of those new software technologies that are being widely used across the world for web development.

So let’s take a closer look at the Power of VueJS!

1. Gentle learning curve

Vue’s gentle learning curve steals the hearts of beginners and state-of-the-art developers. Its high accessibility helps fast-paced dev teams get all their creative juices going without having to spend a lot of time familiarizing themselves with additional syntax extensions. Simply you can go ahead and start making your first Vue app—no prior knowledge of ES2015, TypeScript, JSX, or build systems required. Even though there aren’t many Vue developers on the market yet, developers have started delivering value within more or less a week.

2. Rich Ecosystem and Versatility

Vue comes with a rich collection of libraries and a set of tools facilitating development, the Vue world has everything a developer needs. The more notable tools that amplify coding experience are the excellent Vuex for state management and Vue-routing for routing and mapping your single-page app states to respective URLs. It has its DevTools, which come in the form of a browser extension. Its incrementally adaptable ecosystem scales between a library and a framework, which makes it an optimal solution for any development project.

3. Reactivity

Data in various HTML elements renders dynamically in modern web apps. Vue is equipped with its proprietary reactivity mechanism that refreshes the user interface automatically. This approach delivers a lot of time and additional lines of code that the developer can use to focus on introducing other features and be more productive.

4. Lightweight

Vue.js is light weighted and weighing around 20KB, and offers an insane act at warp speed. Vue is the fastest framework. Its rendering layer was rewritten with the help of a lightweight Virtual DOM implementation forked from the snabbdom. All dependencies in Vue.js are tracked during render, the system regulates which component needs to reflect the changed state. It allows Vue to know which parts of the view need to be re-rendered and leaves the rest intact, significantly speeding up application reactivity.

More than 700 popular brands trust Vue.js for their development needs some of the most important are: Xiaomi, Alibaba, and Gitlab.

Summing up

Vue makes it easy for developers to adapt and implement the elements. Working with Vue.js is a pleasure. It is also supported by a growing community of dedicated developers who can offer help and advice when needed. I hope you have this blog useful but still if you are not clear about the requirements or you have any idea in your mind, we can help you! Yes, we are making digital transformation easier for the majority of the industry. We ensure that there will be the right choice of framework according to your needs. We have skilled developers who keep themselves updated with the newest tools and technologies. So what are you waiting for? Drop us a line or call us to discuss your next endeavors.

With the evolution of the Internet, the ways businesses, economies, stock markets, and even governments function and operate have also evolved, big time. It has also changed the way people live.  Lately the term ‘Big Data’ has been under the limelight, no more a new term, and almost everyone knows something about it. Before the past couple of years, most of the data was stored on paper, film, or any other analog media; only one-quarter of all the world’s stored information was digital. But now everything is digital.

Let’s move forward more about Big Data!

What is Big Data?

Every day, we create 2.5 quintillion bytes of data so much that 90% of the days in the world today have been created in the last two years alone.

This data comes from everywhere:

• Sensors used to gather climate information
• Posts to social media
• Digital transaction  pictures and videos,
• Purchase transaction records
• Cell phone GPS signals to name a few
• This is Big Data
• Today, Twitter generates 12TB of data every day
• Airbus A380 generates 10TB every 30 minutes of flight
• NYSE generates a Tb of data every month.

Big Data is similar to small- data but bigger.

Definition

No single Standard definition.

Big Data is data whose scale, diversity,y, and complexity required new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden. Big Data is a high-volume, high velocity, and high variety of information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision-making. It spans three dimensions volume, velocity, and variety.

Big Data is widely classified into 3 main types

1. Structured data

2. Semi-structured data

3. Unstructured data

Let’s walkthrough

1. Structured data

Any data that can be stored, accessed, and processed in the form of a fixed format is termed “structured data. Throughout time, talent in computer science has achieved great success in developing techniques for working with such kinds of data and also deriving values out of it. However, nowadays, we are foreseeing issues when the size of such data grows to a huge extent, typical sizes being in the range of multiple zettabytes.

Source of structure data

• RDMS like Oracle, MySQL,  DB2, QL server, etc
• Spreadsheets
• OLTP  system

Examples

• Relation/tables
• MS Access
• MSExcel

2. Semi-structured data

Semi-structured data can contain both forms of data. We can see semi-structured data as structured in form but it is not defined with e.g table definition in relational DBMS.

Source of semi-structured data

• XML
• JSON
• Other markup languages

3. Unstructured data

Any data with an unknown form or structure is classified as unstructured data. In addition to the size being huge, unstructured, data is a heterogeneous data source containing a combination of simple text files, images, videos, etc. Nowadays organizations have a wealth of data available with them but unfortunately, they don’t know how to derive values out of it since this data is in its raw form or unstructured format.

Source of unstructured data

• Web pages
• Images
• Free-form text
• audio/video
• Body of email
• Chats
• Social media data
• Word document

Characteristics of Big Data

1. Volume

The name Big Data itself is related to its enormous size. The size of data plays a very crucial role in determining the value of data. Volume is the amount of data generated that must be understood to make data-based decisions. A text file is a few kilobytes, a sound is a few megabytes while a full-length movie is a few gigabytes. An extremely large volume of data is a major characteristic of big data

E,g Amazon handles 20 million customers’ clickstream user data per day for recommended products.

2. Velocity

Velocity measures how fast data is produced and modified and the speed with which it needs to be processed. An increased number of data sources both machine and human-generated drive velocity. Big Data Velocity pack with the speed at which data flows in from sources like business processes, application logs, networks, social media, sensors, Mobile devices, etc. The flow of data is massive and continuous. The extremely high velocity of data is another major characteristic of big data.

E.g. 72 hours of video are uploaded to youtube every minute at this velocity.

3. Variety

Variety defines data coming from new sources i.e both inside and outside of an enterprise. It can be structured,semi-structured, unstructured, or even in different formats such as text format, videos, images, and more. So, storing and processing unformatted data through RDBMS is not easy. Variety is one of the important characteristics of big data.

• Structured data – Traditional transaction processing systems and RDBMS.
• Semi-Structured data – HyperText Markup Language, Extensible Markup Language (XML).
• Unstructured data- Unstructured text documents, audio, video, email, photos, PDF, and social media.  3. Variability

4. Variability

Variability refers to the inconsistency which can be shown by the data at times, thus hampering the process of being able to handle and manage the data effectively. Data available can sometimes get messy, anomaly, and maybe difficult to trust. Data flows can be highly inconsistent with periodic peaks. With a wide variety of big data, types generated quality and accuracy are difficult to control.

E.g A Twitter post has hashtags types and abbreviations.

5. Veracity

Veracity refers to biases, noise, and abnormality of data. This means the degree of reliability that the data has to offer. Big data, as large as it is, can contain wrong data too. The key question here is “Is all the data that I am analyzing trustful”.

6. Volatility

The volatility of data deals with, how long is the data valid? And how long should it be stored? Some data is required for long-term decisions and remains valid for a longer period. However, there are also pieces of data that quickly become obsolete minutes after their generation.

Conclusion

To conclude, the above-mentioned 6 characteristics of big data indicate that each character is associated with some advantages. However, they are not beyond challenges. Besides, these characteristics determine the root of failures or defects in data on a real-time basis. I hope you have enjoyed this blog, for more information just drop us a line and we will be back within 24hrs.