Generate Increased Stakeholder Confidence with Visual Data

The massive amounts of data that are generated by an organization’s databases and computing systems offer a wealth of information to be used in business planning and decision making. Correct use of this information can provide an enterprise with a competitive advantage through a better understanding of their customers, products, and the market in which they operate. The field of data analytics has evolved to assist companies to handle and make sense of this flood of data and use it to increase their business intelligence (BI). 

Presenting data in ways that all stakeholders and levels of management can make use of it can be challenging. Typically, there are many groups with diverse backgrounds that are involved in making decisions based on the data that has been collected. It can be difficult for all parties to exhibit the same level of understanding when faced with determining what the data means for the organization.

Visually depicting data to make complex information easier to understand is a widely-used technique for enterprises wishing to grow their business intelligence capabilities. Early data visualization tools such as charts and graphs exported from spreadsheet programs have been replaced by more sophisticated methods of presentation. Using these methods correctly can give you a huge advantage when communicating the value continued in the data.

Underlying Concepts of Data Visualization

Simply producing graphs or pictures created from your data can be counterproductive without fully understanding how you want the information to be used by your audience. The first step is to decide the broad category in which your data presentation falls.

  • Conceptual visualizations focus on ideas and concepts. The goal of the conceptual visualization is to simplify complex information and teach an audience about the subject under review. This type of visualization deals with qualitative data.

  • Data-driven visualizations concentrate on illuminating the information hidden in statistics to inform stakeholders concerning specific aspects of a business or organization. Quantitative data is the primary fuel for this kind of visual presentation.

Answering this question identifies the type of information that you have and leads to another choice regarding how you will use the data. Essentially, you are either declaring or exploring an idea or statistics in your visualization. You can make a point with a declarative visualization that may not be as easily comprehensible by simply assimilating the data behind it. An exploratory visualization can reveal trends or characteristics of the information that were not evident when looking at the raw data used in its creation.

Data Visualization in Action

Let’s take a look at how employing data visualization has been used by the pharmaceutical industry to improve their research and assist in developing new treatments and delivering them to the public.

The research and development efforts that go into bringing a new drug to market can entail 15 years and over $1 billion. Any way to minimize these expenditures in time and money are welcomed by the industry. Data visualization has proven to be an important tool in streamlining development efforts and making better use of the information that is generated throughout the multiple processes that go into introducing a new drug to the public.

Methods used in traditional data analysis do not provide a viable means of disseminating the large amounts of information that needs to flow between the different groups involved in pharmaceutical research. Conventional tools are not sufficient to address the diverse needs of the biologists, chemists, statisticians, and clinicians who comprise the audience for the insights provided by the data.

Pharmaceutical corporations require advanced data analysis techniques that furnish more easily understood information to all associated stakeholders. The type of analysis that provides the greatest benefits addresses these issues by the addition of three qualities to methods. The characteristics they seek in analysis tools should allow the data to be presented in a visual, interactive, and guided manner.

  • Visual data will enable the results of research to be understood by groups involved in making decisions.

  • An interactive data display enables researchers to query the data to answer questions and enable further discoveries.

  • A guided view of the compiled data makes use of the expertise of certain stakeholders to inform and educate their coworkers.

The ability to use advanced data visualization techniques has enabled them to use their data more effectively in research and clinical trials. One of the most important benefits achieved through the use of visualization is the ability to see how multiple variables are interacting which is critical to evaluating the success or failure of a new pharmaceutical product.

Data Visualization Tools

Performing sophisticated data visualization requires the right tool for the job. You need an application that can pull data from various repositories and present it in a variety of ways to address specific goals. Aqua Data Studio provides a versatile tool for creating data visualizations that will lead to increased confidence in the decisions made by the stakeholders in your audience.

Aqua Data Studio contains a powerful suite of features that facilitate visual data analytics. Custom dashboards can be created that offer an interactive view of data gathered from multiple databases. Simplify the study of trends and market fluctuations to make the important points that may lie buried in an overflow of numbers and statistics. Your audience will appreciate having the data in a more accessible format and it can result in more effective decision making throughout the organization.

Anonymous