App Designers vs. App Developers

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Data Engineering Vs. Data Science - Key differences

Business Intelligence(BI) and Data Analytics are no longer buzzwords. Instead, enterprises are rapidly gravitating towards them to improve business performance. With adequate focus on data literacy, its collection, and data infrastructure, it is possible to accomplish results capable of enhancing revenue generation. Businesses generate a humongous amount of data today. This necessitates adopting intelligent and result-oriented data products to process the generated data and enhance its utility. The model "Data Science Hierarchy of Needs," suggested by Monica Rogati, further corroborates this. According to this model, Data Acquisition occupies the lowest level. It is succeeded by Data Engineering, Data Analytics, Business Analytics, Data Science, and AI (deployment and observability). Data engineering helps to connect data gathering with Data Science. Raw data cannot form the basis for building predictive models that establish trends and patterns. It needs to be converted into a usable or accessible form. This transformation is achieved using well-designed systems and pipelines. The designing, developing, testing, and maintenance of these pipelines and architectures fall under the purview of Data Engineering.Data Science deals with the extrapolation of knowledge and insights from transformed but noisy raw data, both structured and unstructured, and applying that knowledge to answer business-related queries for better decision-making and formulate metrics to improve implemented business processes.Data scientists achieve the above by using different scientific methods, algorithms, processes, and systems. Data engineers complement Data Scientists by providing them with the necessary framework and architecture. Data Engineering: Defining its scope and criticalityAnalysis of Big Data has completely changed the way of doing business. The collection and management of such a large volume of data require the development of an architecture that can handle structured and unstructured primary data and appropriately cleanse and transform it. The development and management of this data architecture is done by Data Engineers. They use different intricate methodologies to achieve this. Tools associated with the implemented technique range from AI to Data Integration. By choosing and employing the correct tools and techniques, Data engineers gather, clean and authenticate data to make it comprehensive and coherent for analysis by Data Scientists. Data Engineering is also important because it helps to refine SDLC(Software Development Life cycle), enhances data security, protect businesses from cyber attacks and cyber frauds and increase business domain knowledge. Its contribution to elongating the shelf-life of a business is indisputable. By converting unreadable data into readable form, Data Engineering empowers Data Scientists with secure data to generate accurate business insights. Data Science: Its meaning and definitionModern businesses are awash with data. With the expertise of professionals, it is possible to use available cutting-edge technology and tease actionable insights from the gigabytes of transformed data generated. These experts are Data Scientists. They add value to a business by providing enterprises with accurate analytics and insights for precise decision-making, deciphering trends to realign goals, improve workflows by focussing on its best practices and identifying growth and revenue-earning opportunities. Data Science is also used to provide quantifiable data-driven evidence, refine target audience and influence insightful talent acquisition. Data scientists are invaluable assets who analyze disparate data sources to generate meaningful insights that help businesses to grow, become profitable, and attain sustainability.Data Engineering vs. Data ScienceOften confused and thought to refer to the same thing, Data Engineering and Data Science are interwoven processes with distinct fundamental differences. Data engineering is the bridge that straddles the divide between data gathering and gaining value from data. It plays a critical role in the success of data science. Differences between the two primarily relate to:Data handling: Big Data can benefit businesses by creating multiple possibilities for improvement. An organization employs people skilled in Big Data management to maximize this advantage. Data engineers and Data scientists play a crucial role in this management.In the "Data Science Hierarchy of needs" pyramid, there is a clear distinction between the job roles essayed by Data engineers and Data scientists. Data engineers collect relevant data, transform it, and move it into pipelines so Data scientists can aggregate, optimize, test, and analyze it to generate real-time insights.  Data task classification: The work of a Data engineer is technically oriented as it involves three critical data actions, namely designing, building, and arranging Data "pipelines." They are Data Architects who design Big Data architecture and prepare it for analysis.Alternatively, Data scientists analyze, test, create and present data so enterprises can improve business decision-making and make it data-driven. Data engineers do technical work, while Data scientists are more business-oriented. Tools involved: Machine Learning(ML) and Deep Learning(DL) are to Data Science what ETL(Extract Transform Load) and ELT(Extract Load Transform) are to Data Engineering. ETL is the process of extracting, transforming, and loading the transformed data onto the original database.ML, a subset of Artificial Intelligence or AI, enables computers to forecast future scenarios automatically by using specific algorithms and existing information. DL uses artificial neural networks built on ML algorithms to allow the automatic learning of computers. Of algorithms and statistics: Data Engineering uses algorithms, but Data Science uses statistics. Algorithms comprise rules and processes that guide computers to carry out specific tasks. They deal with information retrieval, logical reasoning, and mathematical problems like calculus and linear algebra.Statistics involve the study and interpretation of numerical data. Other than using statistics to group, review, and analyze information, Data scientists also use it to apply quantifiable mathematical models to specific variables.ConclusionTo sum up, Data engineering plays a critical role in Data Science. But while they might occur together in almost all business applications, they are fundamentally different and require separate tools and skill sets for successful application.Data Engineering deals with data management, understanding, and extraction from big datasets. At the same time, Data Science is concerned with analyzing the cleaned and extracted data and using analytics to generate intelligent business insights. Together, they help businesses transition from average to excellent.

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Get familiar with these 5 Best PHP Frameworks for Modern Web Development

Web Application development is quite a complex and prolonged process.  But, with the right PHP framework, Sun Dew Solutions can ease out the process and minimize the time required for development. PHP, also known as Hypertext Preprocessor is one of the most powerful and popular server-side scripting languages which provides a wide gamut of frameworks that build complex applications and enterprise-class websites easily.PHP Frameworks come in all categories of form and sizes and have targeted developers with different levels of experience, application needs, hosting capabilities, and development time-frames. One should always consider picking the modern PHP Framework that provides well organized, reusable and maintainable code. It’s also important to understand why PHP 5 and 5.6 became obsolete, since outdated versions can create major security and compatibility issues for web projects. Most modern PHP frameworks follow the Model-View-Controller pattern that ensures the separation of presentation and logic and support modern web development practices.Look at the 5 best PHP Frameworks that increases productivity and makes web development streamline-1.    LaravelLaravel PHP framework is comparatively new and it is one of the most robust and popular tools which is been used extensively by a large number of experienced web developers. The framework is designed with lightweight template processor called ‘Blade’ elegant syntax that makes task simple and enables frequent chores such as authentication, caching, sessions, Restful routing, and queuing easier for developers. Laravel also includes a local development environment called homestead that is a packed Vagrant box.2.    SymfonySymfony is the second most popular PHP Framework after Laravel. It is a reliable and high performing framework developed for creating websites and applications.  Symfony is also built on similar web architecture design patterns like Laravel which includes components such as Drupal, EZ Publish and phpBB.  It’s hard to determine which is superior among Laravel and Symfony as they both have common and excellent features and are among the most popular framework used in website development.3.    PhalconPhalcon is another popular framework among the developers because it is fast with low overheads and it is written in C and C++ to attain the highest level of performance. Phalcon not only speed up the execution process but it also decreases resource usage.  Phalcon framework is equipped with advanced features like auto-loader, asset management, caching, security, translation and many more. It is definitely worth a try! 4.    CakePHPCakePHP is great for commercial web applications and is packed with cool features such as database access, caching, validation and so on. Even though it a decade old framework, but it is still counted as one of the popular PHP frameworks. However, the latest version CakePHP Framework 3.6 upgraded the session management, modularity and enhanced the ability to create more standalone libraries. CakePHP has been used by many big brands like BMW, Express and Hyundai for developing their websites.  5.    CodeignitorCodeignitor is a developer friendly framework with the simple installation process and minimalistic configuration setup which can save you from a lot of hassle. It is an ideal choice if you want to avoid PHP version conflict and works fine on almost all shared and dedicated hosting platforms.  As Codeignitor is not built on MVC development pattern, it gives developers a great freedom where they can use their own code and naming conventions. Being one of the lightweight frameworks, it gives developers an opportunity to add third-party plugins to perform more complex functionalities.Each framework has its own perks and flaws, however choosing the right one depends on various factors like speed, ease of use, security, scalability, documentation and hosting sources. Along with that, the skill sets of the developer and the project they will be working on also come into consideration. Just be sure to check the company behind the development of each framework to be certain, it is actively maintained and has long-term support which will ensure that it remains updated in the future.

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How to Install SSL Certificate in XAMPP For Local Development?

Setting up SSL in XAMPP ensures your local development environment mimics real-world, secure HTTPS deployments. Learning how to install SSL certificate in XAMPP is a key step to building secure web applications in a local environment. This isn’t just a best practice but often a prerequisite for enabling critical functionalities. Without HTTPS, many modern web features such as APIs, service workers, and secure cookies won’t function as intended, even in a local environment. With this guide, you’ll set up HTTPS using either OpenSSL or the easier and trusted mkcert utility, ensuring your development mirrors real-world conditions.Step-by-Step Guide on How to Install SSL Certificate in XAMPPThere are two straightforward ways to get SSL running in your local XAMPP setup, using the built-in OpenSSL utility or the more user-friendly mkcert tool. Both approaches help you simulate a secure environment for development.Using OpenSSL utilityStep 1: Create a minimal config fileStep 2: Generate the private key and certificate using the minimal config fileStep 3: Configure Apache to use the certificateStep 4: Review SSL configurationStep 5: Verify Apache configuration and check for syntax errorsStep 6: Restart ApacheUsing mkcert utility (Recommended)Step 1: Install mkcert by following the instructions hereStep 2: Generate the certificatesStep 3: Configure Apache to use the generated certificatesStep 4: Review and verify Apache configurationStep 5: Restart ApacheThere are a few browser APIs that require the web page to run in a secure context. For that, we need SSL. Here is how we can configure SSL for Apache in XAMPP. There are two ways to configure the SSL - either using openssl or mkcertUsing OpenSSL utilityThis method works properly. However, you won’t be able to see the green padlock icon even after following the steps below. This is intended behavior. To get a green padlock without warnings, you need to add your certificate to the trusted root certificate authorities.Step 1: Create a minimal config fileCreate a new file named openssl_minimal.cnf and add the following content:Make sure to replace the placeholder variables with actual valuesSave this file in a convenient location, such as C:\xampp\apache\conf\openssl_minimal.cnfStep 2: Generate the private key and certificate using the minimal config file2.1 Open terminal and navigate to the OpenSSL directory. 2.2 Generate a private key. The following command will generate a private key name private.key . Feel free to use any name of your choice.2.3 Create a Certificate Signing Request (CSR) file using the minimal config file created earlier. The output file name can be customized.2.4 Generate a self-signed certificate file using the minimal config file. The parameters can be customized.Step 3: Configure Apache to use the certificate3.1 Copy the generated files to a convenient location inside the Apache folder.3.2 Open the httpd-ssl.conf file located in xampp\apache\conf\extra and update the paths.The paths are relative to the Apache installation folder.3.3 Ensure that the following lines are un-commented in the httpd.conf file.Step 4: Review SSL configurationReview the VirtualHost setup in the SSL configuration file. Here is a sample of what it might look like.Step 5: Verify Apache configuration and check for syntax errors5.1 Navigate to xampp\apache\bin5.2 Check for syntax and other configuration errors using the following command5.3 If everything is correct you would get the message Syntax OKStep 6: Restart ApacheUse the XAMPP control panel to restart Apache. Now try accessing localhost via HTTPS. The browser might show a warning about the certificate being self-signed. You may ignore the warning and proceed.Using mkcert utility (Recommended)mkcert is a tool to make trusted certificates for local development without any configuration.Step 1: Install mkcert To get started with, first install mkcert by following the instructions here.Once mkcert is set up, run the below command to install the trusted root store.Step 2: Generate the certificatesThe above command will generate two files - localhost.pem and localhost-key.pemStep 3: Configure Apache to use the generated certificates3.1 Copy the generated files to a convenient location inside the Apache folder.3.2 Update the httpd-ssl.conf file located in C:\xampp\apache\conf\extraStep 4: Review and verify Apache configurationReview and verify the Apache configuration using the steps mentioned above (Step 4 and Step 5 of OpenSSL installation).Step 5: Restart ApacheRestart Apache, and you are good to go. When opened in the browser, the green padlock icon will be visible.Summing It UpNow you have two reliable methods to set up HTTPS in your local environment: OpenSSL for a manual approach and mkcert for a quicker, trusted solution. Understanding how to install SSL certificate in XAMPP localhost not only helps you avoid browser security warnings but also ensures that your development environment aligns with modern web standards. Secure by default is now the new norm, and that applies to local development too, especially for APIs and full-stack work.