Visual analytics for data scientistsSarah Battersby
Integrate KeyLines to add visual analytics Typically, users embed KeyLines into a web application to create an interactivegraph analyticstool. We can do the same with Jupyter Notebooks because, although it’s designed for Python, it supports JavaScript too. This gives data scientists advanced graph...
Description:Databox offers a business analytics platform for KPI dashboards that pulls organizational data into one place so users can track performance and discover insights in real-time. The product lets you mix and match metrics from different sources into one dashboard. Databox features a DIY...
Research findings in biomedical science are often summarized in statistical plots and sophisticated data presentations. Such visualizations are challenging for people who lack the appropriate scientific background or even experts who work in other areas. Scientists have to maximize knowledge dissemination by...
Software-wise, some stages of the pipeline have been designed in a decoupled plug-and-play way, so that future researchers and data scientists can extend it to their needs. 3.1. Deep Learning (DL) module In the Deep Learning (DL) module, an input time series dataset is loaded, processed...
Epiviz exposes a fully-featured JavaScript code dialog which scientists can use to define complex ways in which these transformations can be applied. 3. The extension of user workspaces to include user-defined code customizations. Reproducibility is an essential aspect of genomics data analysis ...
sensors Article A Visual Analytics Approach for Station-Based Air Quality Data Yi Du 1, Cuixia Ma 2, Chao Wu 3, Xiaowei Xu 1, Yike Guo 3, Yuanchun Zhou 1 and Jianhui Li 1,* 1 Department of Big Data Technology and Application Development, Computer Network Information Center, Chinese ...
SAS� Visual Analytics has two add-on offerings, SAS� Visual Statistics and SAS� Visual Data Mining and Machine Learning, that provide knowledge workers and data scientists an interactive interface for data partition, data exploration, feature engineering, and rapid modeling...
Never before in history data is generated and collected at such high volumes as it is today. As the volumes of data available to business people, scientists, and the public increase, their effective use becomes more challenging. Keeping up to date with t
Ocean scientists often run an ocean–atmosphere model with different settings to study the complex ocean process. Therefore, each run of the model will generate a time series of spatial field composed of multiple physical variables at each location of the field, which is called an ensemble. A ...