Reporting tools development is at a critical stage. As their use expands in organizations across disparate industries and more value is placed on the results of sophisticated reports, expectations are higher. Companies are increasingly aware that there are substantial gains in productivity and profitability waiting in the creation and use of specialized apps. Organizations are abandoning the one-size-fits-all mentality, seeking to gain leverage over the competition through the use of data analysis tools. To make that happen, companies require a programming team dedicated to developing applications that not only seamlessly fit into company processes, but spur innovation in data-driven decision making.
The changing nature of the use cases and expectations for reporting tools contributes to several trends with widespread impact on programming processes, design and development. Here are five of the most important:
1. JavaScript MV frameworks replace JavaScript files: Starting from scratch is no longer en vogue for programmers. The evolution of HTML AJAX apps has eliminated the need to make something out of nothing, wrote InfoWorld contributor Peter Wayner. By relying on existing MVC frameworks, programmers can quickly establish the foundation of their apps and reporting tools and cultivate higher levels of functionality and performance.
"Long ago, everyone learned to write JavaScript to pop up an alert box or check to see that the email address in the form actually contained an @ sign," Wayner wrote. "It's simpler to adopt an elaborate framework and write a bit of glue code to implement your business logic."
Demands for more efficient development and rapid deployment of reporting tools can be easily met with the advanced frameworks available today.
2. Hybrid languages for data science: Customization is integral to enterprise reporting tools development. The main advantage in having tailored apps is that they fit a company's business logic exactly. Today's sophisticated frameworks improve compatibility between programming languages, components and frameworks, facilitating the integration of widely disparate elements that could not have fit together previously. Additionally, focus on the need for the average end user places more importance on simplification. Both of these phenomena are apparent in the shifting positions of the R and Python programming languages, observed ReadWrite contributor Matt Asay.
"This new, early majority of 'data scientists' is far more likely to use Python than R," Asay wrote. "It's comparatively simple to use, and they've likely been able to use it in another project already. As in other markets, the tool you already know or is easy to learn is far more likely to win than the powerful-but-complex tool you'd really rather avoid if possible."
As emphasis on quick deployment and rapid engagement of reporting tools continues to drive development-related decisions, the simpler option will continue to win out over the complex one.
3. Mobile Web apps growing in prominence: Most companies are dealing with some degree of compatibility issues related to the ascension of mobile devices to the top of the IT heap. These issues should not extend to reporting tools and apps. Native mobile app development is being phased out, Wayner wrote, because the time and energy needed to write different versions for each operating system can be much better dedicated to another pursuit. A programmer can now build a single reporting tool or app on HTML5, with the assurance that it will function correctly on all device operating systems.
"Now that the HTML layer is getting faster and running on faster chips, this approach can compete with native apps better on even more complicated and interactive apps," Wayner wrote.
Effective enterprise reporting tools depend on best practices for programming. Any process that makes app development more efficient, reliable and interoperable is likely to see continued adoption.
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