Data rarely comes in usable form. Data wrangling and exploratory data analysis are the difference between a good data science model and garbage in, garbage out. Novice data scientists sometimes have ...

Speeding up the exploratory data analysis process using flexible automation and consistent reporting allows analysts to deliver analyses quickly while ensuring precise, accurate results. In most ...

If you are using big data analytics for business, the use of data visualization tools can help you optimize the data processing and analysis of the captured information. Having too much data available ...

This second course of the Data-Driven Decision Making (DDDM) series provides a high-level overview of data analysis and visualization tools, preparing learners to discuss best practices and develop an ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

Area(s) of potential collaboration: Would like to collaborate with faculty who are interested in developing grant proposals that involve GIS and network analytics. Primary research focus: I study how ...

The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, ...