By Bill Kelly

October 24, 2018 -- Every day, mankind creates 2.5 quintillion bytes of data. The rate of our data production is so great that 90% of the world’s data today was created in the last two years alone. This information flows from many sources; climate sensors, investing algorithms, music videos and social media posts all contribute to the formation of a worldwide data repository of immense volume.

Cataloging such a quantity of information, let alone interpreting it, seems an insurmountable task. The high volume of large data sets often renders them inaccessible for human processing. Even on a smaller scale, sifting through a particular set of data to identify a trend or metric of interest can be a laborious task with great capital costs. The field of genetics and genomics, for instance, has become increasingly intertwined with computer science for this very reason. The increasing amount and complexity of data drive the need for innovative and computationally efficient software, such as new programs, packages, and algorithms for sequence alignment, genome assembly, and genome-wide analysis.

Scientists, researchers, and business personnel value methods to communicate these findings more clearly. In both the business and scientific realms, efficient and accurate data analysis is essential to workflow. It is for this reason that top companies and institutions are shifting away from traditional methods of data interpretation and toward data visualization and dashboards. Rather than acreage of spreadsheets or a desktop cluttered with formulas and charts, data dashboards display all the essential information in real time in one place. Whether for personal research, board meetings or company-wide collaboration, data dashboards replace the rigors of analysis and presentation with a sleek and accessible platform.

What are your thoughts on data visualization? Would it assist you or your lab in research? Let us know in the Forums.


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Last Updated sv 10/24/2018 12:13:15 PM



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