Articles

The business world today is breathing a complex amalgamation of traditional and new age technological solutions, used in absolute coalesce to derive the best of market yields. The convergence of cognition, human and machine have brought off a new era of cross-functional advancement that has allowed business leaders to achieve immeasurable feats across their target realms.

Agile, with all its development benefits, has transformed the team’s capability to better work efficiency and higher ROI. When combined with DevOps, agile teams can deliver faster build cycles with reduced risk of inaccuracies and held up deliveries. Because agile development promotes rapid bug-free deliveries during the entire project span, in-house development teams can rather quickly enforce newer functionalities without affecting the timeline of the project completion. It is especially very applicative in today’s hyper-converged development scenario, where customers wish to stay ahead of their league with more efficient and effective work solutions on their sides.

Product excellence has gained massive momentum in modern-day product development domain. Following the world trend, development firms are, therefore, trying to bring in innovative tech-driven strategies to create remarkable value-based products and services for their end-users without compromising the quality of the product. Enhanced development speed, along with quality addition, has emerged as the critical element to match up with user expectations and help enterprises maintain good market lead within this intensified competition.

Publilius Syrus, the great Roman writer, said, ‘It’s a bad plan that admits of no modification.’ Project managers shall agree to these centuries-old words completely. Qualified development teams emphasize that it’s not possible to build a project from tip-to-toe at one go. Most roadblocks cannot be accounted for in advance. One is required to change the approach as per the requirements of the development in the project.

Mobile application security has become a prime issue today, especially when the majority of businesses are investing considerable resources in making their workforce more active and productive. The trend of Bring Your Own Device (BYOD) has undoubtedly benefitted organizations by offering higher work efficiencies and employee comfort but has also brought along an inevitable downside in the form of peppy vulnerabilities that organizations need to address promptly.

The red-line between Business Intelligence and Business Analytics has always been blurry. It’s hard to differentiate between BI and Business Analytics because they ride on a similar behavioral pattern.

We can’t foresee the future events and analyze their outcomes, but what we can do is use all of our current digital capacities to gather and analyze past-data to draw insights into the future. In data science terminology, this process is termed as predictive analytics, and it is now widely adopted in sizeable heterogeneous business networks for greater transparency.

The best optimists are those who have a contingency plan for everything that can go wrong. For this risk mitigation planning is paramount to ensure control over the project development process and its success. Risk mitigation equips project managers with the right approach, tools, and resources to face the worst of eventuality, which if not accounted, can slow down project pace.

Test development has been a long-standing issue in the modern software development realm. Today, when almost every development team faces the challenge of building an ideal market application with better accuracy and speed, test automation becomes more of a compulsion than just a time-saving practice. Today’s user needs are fickle and ever-changing; therefore, it makes the work taxing, especially for the test engineers.

It is relatively reasonable to state that the modern business world primarily builds upon the power of data to bring desired upgrades into their work process. With the world becomes more data affluent, technological evolution would result in enhanced productivity of business data. This in return would also help decision makers to transform their work models into better production engines with data tech acting as its driving fuel.

Big Data is a vast collection of organizational data, which modern enterprises are turning into decisive insights via analytical means. Every data bit is necessary when it comes to putting big data analytics at work. This data comes from a variety of organizational sources, ranging from clickstreams, social media interactions, operational data points or functional logs. By applying analytical algorithms and automation tools, an organization can use its data goods to derive actionable insights and make informed market decisions.

With the advent of technology, users started experiencing the functionality of desktop computers on their hand-held devices, giving rise to smartphone usage. The population of smartphone users have started growing rapidly, so much that mobile devices have started dominating over the traditional desktop computers. It is common to see mobile apps becoming ubiquitous in our life.