DEV Community: Marvellous D. Amos

Getting Started With React

Marvellous D. Amos — Thu, 23 Feb 2023 18:20:06 +0000

Introduction

This article intends to provide you with all you need to know to get started with React. Here, you will understand the power of a front-end framework, and the concepts needed to assist you to begin building scalable applications with React.

What is React

React is a JavaScript library for building user interfaces.

It is popular for being declarative, efficient, and flexible. It lets you build complex user interfaces from small, isolated code called components.

Why React

The 2022 Stack Overflow Developer Survey shows React to be one of the most effective and popular web frontend frameworks.
This is a result of the following React features:

Declarative: React allows you to define the final state of your desired user interface.
Component reusability: React allows you, as a developer, to create components only once and reuse them throughout your application. This reduces code duplication and shortens the development process guaranteeing uniformity across the entire application.
SEO friendly: React has a positive impact on SEO (Search Engine Optimization) since it creates SPAs (Single Page Applications) that need JavaScript to display content so that it gets rendered.
Open-source support: due to its popularity, React is well supported and maintained by the open-source community.
Design flexibility: React is not opinionated, so it won't compel you to adhere to any particular design patterns, project organizational framework, or logical reasoning. Everything of it is up to you.
Smaller learning curve: Compared to other Frontend libraries and frameworks, React is easier to learn, especially when familiar with JavaScript and HTML fundamentals.

Getting started

To get started with React, you need to understand one of the major pillars of React, Components.

Components

React makes use of reusable components in building its applications. A simple React application is divided into several independent and reusable pieces.

React provides two types of components:

Function components: Components defined using JavaScript functions


function App() {
   return <div className="App">Hello World!</div>;
}

Class components: Components defined using JavaScript classes


class App extends Component {
   constructor() {
       super()
   }

   render() {
       return (
           <div className="App">
               Hello World!
           </div>
       )
   }
}

Read this article for more about React Components

Now, let's get to a more practical approach to learning React.

Installation

create-react-app is the official way to create single-page applications with React.

To create a React application,

Run the command below on a terminal.

npx create-react-app my-first-react-app

The above signifies that the application has been created successfully under the directory my-first-react-app

Navigate into the applications directory using the command below.

cd my-first-react-app

The directory looks like this:

Let's discuss each folder in detail:

node_modules: This folder contains all installed dependencies and packages the React application needs. In essence, the packages you wish to import into your application are stored here.
public: This folder contains a variety of files but the major ones to consider are the index.html and the manifest.json files. Here,
- the index.html file serves as a template for generating the main file which gets rendered on the browser.
- the manifest.json file contains metadata which determines the icons, names and branding colours to use when a user adds the applications to their home screen.

Visit this web app manifest guide to get a better understanding of how this file affects the user experience.

src: This folder serves as the heart of the application's interface, containing all major components and styles created to run the application. It includes major components like:
- index.js, which serves as the entry point to the React application. It contains some syntax including the <App> component as a React element and the DOM element, root, as the supplied container. This root DOM element is referenced from the index.html.
- App.js which serves as the root component of the application. A typical React application structure would be to build React components and use this App component as a host to render them to the browser.
package.json This file includes a list of the packages your project can use and the versions of those packages on which it depends. Together with the package-lock.json, it makes your build repeatable and simpler to share with other developers.

Run The Application

To run your application

Ensure you are in the application's directory in your terminal

That is C:\users\...\my-first-react-app>

Run the command npm start
Open the http://localhost:3000 local server to view the application.

Congratulations! You have created your first React application.

Conclusion

This article has given you a rundown of the React frontend web library and its basic setup and structure. Now get creative and begin creating applications with React.

Visit the React Documentation to get more tutorials and content on React

Design Quality software with the SDLC

Marvellous D. Amos — Sat, 15 Oct 2022 13:11:52 +0000

Table of content

Introduction
What is the SDLC
Brief history of the SDLC
Advantages of the SDLC
Phases of the SDLC

Introduction

It is the wish of every software Organization and development team to produce quality software that exceeds customer expectations, meets customer deadlines and is cost-effective.

This article will help development teams and software organizations archive this by giving a basic understanding of the SDLC and how to apply its phases in producing quality software products

What is the SDLC

The SDLC or Software development lifecycle is a systematic process taken to develop quality software. It defines tasks performed at each phase of the software development process which leads to the production of software that meets stipulated requirements.

It also serves to improve the quality and the development process of the software

Brief history of the SDLC

Due to the growing complexity of software development projects, in the mid-1960s, there came a need for these projects to take a more detailed approach toward their development. This need resulted in the birth of the Software development lifecycle

Advantages of the SDLC

The advantages of Utilizing the SDLC include

Each team member has a well-defined role, thus, reducing complexity and overlapping responsibility
problem-solving methods are incorporated early in the design /process
It improves efficiency and reduces the risk of failure
It enables team members to know what aspect of the project they are to work on and when
It provides room for interaction, making it possible to respond to changing requirements
It facilitates communication among stakeholders

Phases of the SDLC

There are 6 phases involved in the SDLC. These include the;

planning
Design
Development
Testing
Deployment and
Maintenance phases

Planning Phase: During this phase, the team gathers, analyzes, documents and prioritizes the software requirements. Factors influencing the software such as resource allocation, risk identification, purpose, users, legal compliance, input/output data, quality assurance and project scheduling are considered during this phase.

Labour time, teams and roles are also identified and allocated in this phase.

All requirements identified in this stage are then documented in an SRS(Software Requirement Specification) document.

Design Phase: During this phase, the requirements gathered in the SRS document are used to develop the architecture of the software. A Design document is then created.

Development Phase: Here, the designers use the design document to decide on and assign coding tasks. The software developers in the team then begin building upon the design architecture.

Testing Phase: Here, the testers carry out tests on the software to ensure that the stability, security and other SRS requirements are met.

Various levels of tests are carried out during this phase including unit, integration, system and acceptance tests.

Deployment Phase: During this phase, the application is released into a production environment and made available to users.

Maintenance Phase: During this phase, later requirements, user interface issues, bugs and code enhancements are identified and rectified.

Conclusion

This article has introduced you to;

the software development lifecycle(SDLC)
the history and need for the SDLC
the advantages of the SDLC and
the general phases involved in the SDLC

Understanding Big Data

Marvellous D. Amos — Sun, 18 Sep 2022 15:23:51 +0000

Get To Know: Big Data

Data is a term referring to facts and statistics collected together for reference or analytical purposes.
In this digital world, everyone leaves a digital footprint. Be it through lifestyle documentation, entertainment media, content creation or even posts on social media, the number of internet-connected devices we interact with daily record vast amounts of data about us and our environment.
This "vast amount of data" has been tagged Big Data.

Defining Big Data

Big Data, is a term used to describe large, hard-to-manage volumes of data. It refers to large, fast and complex data that is difficult, if not impossible, to process using traditional methods. It requires new and innovative ways to be collected, stored, processed and exploited.

Characteristics of big data

The innate characteristics of big data include;

value
variety
volume
velocity
veracity

These characteristics are often referred to as the 5v's of big data

Value: this refers to the benefits collected data possess. It relates to what organizations can do with acquired data and is the major reason organizations spend time and effort studying big data.

Variety: this refers to the type and nature of the data. Data today could be in various formats(text, image, video or audio). Variety aims at the diversity of data and its sources (such as people, machines and organizations).

Volume: this refers to the scale or increase in the amount of collected and stored data. It is the basis of BIG data as it refers to the size and amount of data collected.
The volume of big data is mainly composed of data gotten from sensors, devices, social media, enterprise data and voiceovers.

Velocity: Daily, data is being generated at a fast rate in a never-ending process. The speed, at which this data is being generated and processed is referred to as velocity. This is a very important aspect for companies that need their data flowing as quickly as possible.

Veracity: this refers to how trustworthy the sources of data are. It accounts for the quality and origin of data, conforming to facts and accuracy. Attributes such as consistency, completeness and integrity play a huge role in determining the veracity of data.

Benefits of Big Data

Big data comes with a handful of benefits which include:

improved operational efficiency
improved problem-solving approaches
optimized product development
enable smart decision making

Application of Big Data

By combining big data with high-performance analysis, certain business tasks can be addressed. These include:

Early detection of fraudulent activities
Calculation of risk portfolios
predictive maintenance of machines and equipment
improved customer experience through user specification and advanced client interaction

Challenges of big data

Like every other field, big data is not without its challenges and limitations. It is important to understand these challenges to avoid getting stuck at the initial stages of big-data-driven projects due to a lack of awareness or capacity to tackle their challenges.

Some of these challenges include;

Inadequate storage capacity for big data: This is a pressing challenge for industries and individuals alike as the amount of data stored in data centres and databases continues to increase exponentially.
Rapid change of big data technologies: keeping up with the latest data technology could prove to be a challenge to certain individuals who have already familiarized themselves with certain methods of processing data.
Lack of data professionals: Data professionals such as data scientists, data analysts and data engineers who are experienced in working with appropriate data management tools are of great importance to a data-driven industry. However, these professionals are currently in short supply.

conclusion:

This article has allowed you to understand;

the definition of big data and what differentiates it from normal data.
the characteristics of big data and how they affect an industry
the benefits and applications of big data and lastly,
the current challenges and limitations faced by big data professionals and industries.

If you are aware of any other challenges, or better still, possible solutions to the challenges listed above, share your thoughts using the comment section below

Laying the foundation: Data Engineers

Marvellous D. Amos — Fri, 09 Sep 2022 05:22:39 +0000

Getting into the field of data engineering, you must have the basic yet conceptual knowledge of the field as this would provide you with a solid foundation to develop further.

In this article, You will understand the steps in which data flows within an organization, who are data engineers, and their responsibilities.

Data Workflow

A workflow is a series of activities performed to do a specific task. Data workflow involves the steps in which data flows through an organization.

There are four general steps involved in this process:

data collection and storage,
data preparation,
exploration and visualization and finally,
experimentation and prediction

Data collection and storage: In this step, data professionals collect data from various sources such as surveys, browser history, social media etc. Due to the massive amount of data generated daily in various formats and from various sources, this task becomes a daunting one. After this collection, the data is stored in its raw format.

Data preparation: In this step, data is cleaned to enable the discovery of instances of missing or duplicated values. This step also involves the conversion of data into a more organized format. This leads to the next step

Data exploration and visualization: In this step, statistical techniques are used to identify and describe the structure of the data, the relationship between different data values and other crucial concepts which would enable the creation of visual aids (such as dashboards and diagrams) for tracking and comparing changes in datasets.

This step enables you to gain a good grasp of your data before you move on to the final step

A dataset is a collection of related data.

Experimentation and prediction: In this step, it is assumed you have a good grasp of your data and are thus ready to perform certain tasks such as running experiments or building predictive models.

Data Engineers

Having understood the flow of data in an organization the answer to the question of the role of a data engineer becomes clearer.

Data engineers are responsible for the first step of the data workflow, which involves collecting and storing data.

They are the foundation of the data workflow process as they lay the groundwork for other professionals such as data analysts, data scientists and machine learning engineers who would prepare, explore and experiment with the data. Data engineers ensure that correct data is delivered efficiently, in the right format and to the right people.

Data engineers ingest data from various sources, optimize the databases for analysis, and manage data corruption. They develop, construct, test and maintain architectures such as databases and large-scale processing systems to process and handle the massive amount of data gotten from different sources.

In simple terms, they collect data from many sources and manage it for other data professionals to access and use.

Conclusion;

data engineers are responsible for the first step in the data workflow, collecting and storing data
they lay the groundwork for data analysts, data scientists and machine learning engineers ensuring that data is not scattered, corrupted or difficult to access.