Web applications are out there in the market since the emergence of cloud services. With booming high-speed data communication channels, more players are jumping in to cloud business with AWS as the market leader which roughly supports 40% of the internet today. Low-cost cloud services, cross-compatibility of web apps and data analytics are stagnantly increasing the adoption of web apps.
A rapid pace in Web application development can be achieved with parallel development as these applications are divided into two parts i.e. frontend that runs on users’ system and backend that runs on the server where most of the functionality resides. Therefore, backend and frontend developers can work simultaneously). Web applications are also cheaper because of the following reasons:
Web applications run on web browsers and every operating system provides good support to web browsers. So, you only need to make the web application responsive to make it cross-platform compatible. Whereas native applications are platform-dependent and it is extremely expensive to separately develop applications for all the operating systems, platforms and devices.
Since web application runs on web servers and is rendered from there to end user’s device it is easy to release new features. Once new features are developed, they are integrated with the present application in a testing environment thereafter the procedure of bug fixing runs until web application starts working flawlessly. Finally, the new version of web application (war file of the web app) is released on the production server which then stars rendering new version on end user’s device. In case of a similar procedure is followed therefore web applications provide a better experience to users.
Now a day’s web applications run on shared hosting services where subscribers have to pay according to their usage, which is maintained by hosting service providers. It is almost impossible that your service provider will run out of hardware resources to support the random surges in a number of users. There’s also AWS S3 service which deploys older version (older war file) of web applications if the newly deployed version fails on servers. All the above-listed facts ensure that end-users experience almost zero downtime.
Since web applications run on web servers and UI is rendered on a web browser on the user’s end, therefore, the end-user doesn’t require an expensive device to the web application. He/she just need a device that could smoothly support a powerful device hence web applications can reach out to a larger customer base.
As we know web applications run on servers but what we don’t realize is those are not low-end hardware devices that would narrow down the horizons of performance. Usually, these web servers save web applications on SSDs and run the application with high power CPUs and GPUs. The graphical oriented processing is done by GPUs, even detailed searching like elastic search is provided as a service by AWS. All you can conclude is native applications cannot beat web applications in computing-intensive tasks.
SAP, IBM, Oracle, Zoho and Microsoft are the biggest providers of these kinds of industry-specific enterprise-level software, the only problem with this software is that they are expensive and are developed in a generalized manner to support a wide customer base. There are also cheaper options provided by mid and small scale companies, on the other hand, there are service-based companies who can develop customized software solutions for you.
Light Directory access protocol (LDAP) is generally used in enterprise-level software. LDAP saves information like databases but they record information more descriptive information on directories. The type of information which is supposed to have much more reading cycles than writing cycles is recorded in LDAP and this information is widely replicated to provide low response time. Vendors offer LDAP support with web applications so that their customers can easily integrate the software into their ecosystem. Companies usually approach web application development companies to build a customized software solution from where they can monitor all the work that is being done on different software used in their organization.
When a single web application is being used by users throughout the organization then it generates tons of data. The data from past and present is a valuable asset for companies as it helps them to map the activities of the organization and know the path on which they are heading.
All the gathered data is enormous and it is not possible to read word by word to know the aspects of performance and conclude from it. A statistical representation of this data is the only way analyse the data in glimpses and use them to create and modify business strategies to perform well with every business decision you make. There are dozens of open source and proprietary Business Intelligence tools available in the market which can easily integrate on to databases where organizations have saved their data.
The data gathered by organizations is usually beheld for a quarter but after that most of it remains idle. So, companies periodically send the data from all the web applications and software to a data centre where data scientists and business analytics tools try to find the relation between data to know users and customer behaviour. The study of data provides businesses with a detailed report of user behaviour which influences the business decisions to boost sales and improve the company’s performance in every possible field. When old data is fed to predictive modelling engines, they predict the future on the basis of past performance. Data analytics is the reason why supermarkets keep on rearranging the displayed products, a study says a person who wants to buy milk is likely to buy bread, butter, eggs, tea and coffee that’s why most of the supermarkets showcase them close to each other.
Organizations use dozens of software and web applications to automate their work process and improve efficiency. The web applications and software they use are most likely connected to different databases where large chunks of data are getting stored. When organizations try to send this data to data warehouses to preserve and deploy business analytics tools, they face incompatibility issues among the data and databases. Then ETL tools are used to resolve this problem which does data cleansing to organize the data into a format supported by data warehouses.
ETL tools liberate organizations from dependencies as they take input data from mongo dB, MySQL, SQL, PostgreSQL etc. and sends it to data warehouses (which might be using Hadoop) after processing also the vice versa is possible. Therefore, organizations are free to migrate on new tools and technologies without worrying to compromise on dumping their old data.
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