17 Feb

Is Your Software Engineering Aimed at Quality Control and Data Scalability?

Quality Control and Data Scalability

Nowadays every business needs software and this makes the role of software engineering very critical in order to deliver customer satisfaction regardless of the industry segment. Software engineering has developed from its earlier avatar and today is rightly on the cusp of a major boom what with big data and cloud-based services promising to change businesses in hitherto unheard ways.

Any software developed today has to go through multiple quality checks in order to make sure it conforms to the explicitly stated standards and performance expectations of the clients. The most common drawback of any software is the presence of bugs that can show up at the most unexpected times and ruin the business prospects. Staying on top and eliminating these bugs is easier said than done.

Organizations now need software that has a special emphasis on speed. Thus celerity is a vital component of today’s software development life cycle. The agile methodology of software development perfectly fits the bill considering the excessive demands from clients all around. This ensures that software designers can better act on unexpected demands via repetitive and improved performance sprints. Deploying scrum is the most popular way of benefitting from agile development processes. Scrum is a way of stressing on better managing the team, encouraging practical feedback and rigorously testing the software increments in small iterative steps.


The software code quality is a highly sought-after feature since at the very fundamental level its job is to fulfill stringent business needs, provide customer delight and reduce the defective ingredients or portions in the software.  The quality is not something to look for at the end of the software development life cycle. The pursuit of quality begins at the very outset when the decision to build the software is undertaken.

Here are some ways to assure quality is top priority

  • Define the quality requirement to match the client’s needs
  • Cleary take into account the budget, time and resources needed
  • Put in place quality metrics to measure performance at every step
  • Raise a flag when quality falls short of expected standards
  • Set goals for the individuals and the teams alike for improved output

Due to the data explosion all around enterprises more often than not have to react to increased data needs. It could be in terms of a bigger input database, a larger number of end users, a bigger volume of participating servers in a distributed application software environment and so on. Search engines for example are built to scale for not just the number of searches on any particular day but the sudden deluge of data that comes online and which needs swift indexing and ranking.

Read more: Is your Software Development Life Cycle secure?

Today’s business milieu can get highly unpredictable. This means computer software applications have to cope with the sudden increase in performance expectations. The size or volume of data that is processed can increase without any prior notice. So software engineering has to take into special consideration the need for data scalability in the software end product. It’s not just a question of being able to function properly in an augmented scenario but to take the maximum benefit of the new environment to deliver exceptional results.


The way the software is designed has the greatest impact on how well it can scale to increased data demands. The resources have to be managed very smartly in order to get the maximum benefit. Scalability has to be looked at from every angle from improving the data storage facility to enhancing the end user interface of the software.

The software developer has to make the application versatile so that it is easy to port from one environment to the other. For that special emphasis has to be given to the processor cycles, parallel computing, batch processing, the total bandwidth available, database support and networking in order to meet data exigencies at short notice. So the software has to be a protean beast in order to increase in its size and capabilities as and when the situation demands.