Have you ever been involved in executing an exploratory analysis based on an integrated clinical trial database? If so, you've probably experienced firsthand how elaborate the initial phase of data access and data processing can be.

Market analysts estimate the ratio for preparing the data, compared to actually analyzing the information, is often 80:20. So under normal circumstances, the vast majority of your time is spent with data preparation activities instead of gaining meaningful insights.

Historically, data preparation has been a classic IT task, requiring time consuming interactions between the business departments and IT. The good news is that agile BI has ushered in a new way of gaining access to your information. Modern analytical tools give statistical programmers and project statisticians the ability to prepare data on the fly, providing data insight quickly and without the complex process of engaging external departments, such as IT.

Data visualization capabilities can provides analysts with easy-to-use tools to access and prepare data for further analysis. For example, SAS Visual Analytics includes a visual data builder module that makes it easy to prepare your data with a few clicks, from sources like CSV, Excel, SAS or a database system.

After the data is imported, you can combine it with existing information, such as a randomization table or patient demographics details. Everything is done using a graphical user interface, without having to write a single line of code or SQL.

Once you are satisfied with the result, you load the merged data directly into the in-memory processing engine and proceed with your data exploration or the preparation of the clinical reports.

Join Daniel Christen at PhUSE 2016 in Barcelona, October 12. Together with colleagues from Novartis Christen will lead a discussion on analytics speed and efficiency for the Good Programming Practice Discussion Club (11AM, Barcelona A-C, Mezzanine Level).