Optimizing data visualization development

Data visualization has become a prominent force in the big data movement over the past several years. It's not enough anymore simply to have information - end users have to be able to convey insights in interesting, engaging and surprising ways. A bold or beautiful data visualization can go a long way, especially with enterprise leaders that may be less familiar with the concepts between data crunching and are more interested in something that looks nice or leaps off the screen. However, there is a fine line between a visualization that is "just right" and one that is overdoing it. It's important for developers and end users to work to find the sweet spot - visualizations that succeed on the strength of their aesthetics as much as the quality of their data.

So how to approach data visualization development? There are several things to consider. The first, of course, is what the visual tools are intended for. Are they mostly going to be deployed for number crunching and data querying by employees? They'll need to prioritize clarity above all. Will they be used in meetings with management and the C-suite? There may need to be a more intense focus on visual effects and insight appearance that can keep the viewer's attention without inundating them with numbers. Will these tools be shared between businesses along the supply chain or customer management network? Measures have to be taken to ensure that data can be understood with little additional explanation or context.

How big is your business?
Business size can also affect the ideal approach to data visualization development. Smaller and mid-sized companies often have much different considerations than larger enterprises. In many cases, concerns stem from smaller margins. A small business may be unable to afford a failure rate that a larger entity could live with. This puts more pressure on each investment, and can often hinder companies from getting involved in business intelligence, data visualization and ad hoc reporting. Street Fight Magazine contributor Stephanie Miles recently highlighted some considerations for SMBs exploring the development and deployment of data visualization reporting tools. These strategies can work for larger enterprises getting their feet wet in analytics as well.

• Start slow to avoid failure: Throwing money at an expensive software platform can halt business development before it even gets off the ground. This is especially true for businesses that are still in the process of onboarding programmers. These new employees may not be familiar with the company's objectives, which need to be reflected in a piece of software' business logic. It's important to make sure there is a firm foundation before investing in development tools.
• Do data right: Even the most sublime looking visualization will be effectively useless if businesses aren't using the right data. The end users querying the datasets may not be completely familiar with the concepts behind analytics, so it's important that the platform directs them to the appropriate information.
• Find vendors that care: There are many companies out there that offer programming tools and... not much else. The developer community thrives on collaboration, education and shared insights on a level that few other groups can approach. The best software tools proprietors offer education guides and forums to help their buyers take their implementation to the next level. Asking questions is imperative. Top vendors help a business come to the best conclusion.

The benefits of out-of-the-box functionality
One of the reasons a product like ActiveAnalysis makes so much sense for companies building their data visualization acumen is that it offers intuitive functionality that has an immediate effect. The built-in user interface and premium features enable developers to leverage online analytic processing and data visualization features without having to write code. Once they see what works, they can customize and modify their application accordingly to drive user productivity,