From Caterpillars to Butterflies, Experiments to Lab Data Analysis: Transformation in the Age of Big Data
In the past few years, technological revolutions in material and software engineering have made collecting large amounts of data significantly easier.1 In fact, the term “big data”2 is specifically used to describe data sets that are massive in volume with both unstructured and structured components that can pose a difficulty for interpretation and data analysis.3 And yet, despite the significant amount of time devoted to uncovering how researchers can improve big data analysis, the analysis and interpretation of this data remains challenging, while scientists are increasingly convinced that hidden within these large datasets is information that could very well transform the ways in which we understand, interpret and consolidate scientific knowledge. For companies, big data analysis can transform their business approaches from those based on reactive practice to those that are proactive4 in that understanding trends and knowledge from big data can serve as a predictor for future trends or as a means to understand how markets or customers are changing and, consequently, how a company might alter its own strategy.
How Big Data Analysis Is Essential for Turning Experiments into Products
There are various ways in which scientists can use lab data analysis to carefully mine their experiments and one novel way is topological data analysis.5 Topological data analysis is an analytics tool that provides scientists with the flexibility to fit their experimental data to represent all types of shapes. Thus, instead of relying on a linear regression analysis to identify the relationship between two variables, topological data analysis enables researchers to identify novel associations between multiple data sets and in visualizing it, determine relationships that might have not been apparent using traditional tools. And how can scientists and organizations ensure that they collect enough and the right type of data to enhance topological data analysis?
BIOVIA EKB: Taking Experiments from Data Points to Topological Data Analysis
Tools such as BIOVIA EKB are a powerful means to collect large amounts of data, organize it and begin to assess how all the collected information can undergo topological data analysis—or if this mode of analysis is necessary. Here are specific ways in which BIOVIA EKB does so:
Visualization: BIOVIA EKB facilitates data analysis by presenting data in a single platform that can be visualized topologically, even before any analytics are applied. This process can be done in real time, thus enabling researchers to more quickly mine data and extract the relevant knowledge from this process.
Integration: The EKB platform enables researchers to integrate its functionalities with existing machinery thus enabling data analysis to be done more quickly. Part of the problem with “big data” is the speed with which information is accumulated. As data accumulates, researchers become less inclined to actually analyze the information; important results can thus be neglected or experiments repeated unnecessarily. By integrating machinery with BIOVIA EKB’s platform, researchers can more quickly visualize experimental results, increasing the likelihood that each experiment will result in an important conclusion, be it negative or positive. Additionally, machine calibration is an essential component to sensitive processes in materials science. By integrating this information in a single platform, researchers can ensure that the results they accumulate and analyze are correct, saving on expensive experimental repeats.
Efficiency and Organization: Simply put, using the BIOVIA EKB platform can enable researchers to more quickly and efficiently complete their work. Having information about machines, past experiments, future workflows and more in a single platform that can be accessed by all workers is an important component of how this system is able to increase productivity, improve accuracy and quality, while also helping to ensure that individuals adhere to regulatory compliance. Users of BIOVIA EKB have seen a 90% reduction in regulatory reporting times, while also observing 30% reduction in errors and reworks to the benefit of all. In the fast-paced environment within many labs, these improvements cannot be underestimated.
Increasingly, individuals in all fields are realizing that big data and the data deluge is here to stay. In order for companies to stay ahead of the curve and to not be swallowed by the thing they hope to conquer, they will need tools such as BIOVIA EKB to ensure experiments are completed, data is analyzed and lab data analysis tools are applied to the right problem. To learn more about BIOVIA EKB and other products, please visit our website today.
- “The data deluge,” February 25, 2010, http://www.economist.com/node/15579717 ↩
- “What is Big Data Analytics,” http://www-01.ibm.com/software/data/infosphere/hadoop/what-is-big-data-analytics.html ↩
- “big data,” http://www.webopedia.com/TERM/B/big_data.html ↩
- “Why is big data analytics important?”, http://www.sas.com/en_us/insights/analytics/big-data-analytics.html ↩
- “Why Topological Data Analysis Works,” January 6, 2015, http://www.ayasdi.com/blog/bigdata/why-topological-data-analysis-works/ ↩