As General Manager of Zebra Analytics, Guy is responsible for the growth, leadership strategy and customer success of the business unit. These days, it is not a question of whether companies are ...

The design of your study, the research questions you’ve posed, and types of data you’ve collected (e.g., quantitative, qualitative) are important considerations in determining the data analysis and ...

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 ...

In the humanitarian aid community, research methods have traditionally skewed toward the qualitative: Participant interviews, focus groups, and field surveys have been the predominant tools ...

In the age of big data and advanced analytics, much of the talk about how information can benefit companies focuses on gaining new insights about customers, market opportunities, trends, and other ...

Microsoft Excel for analysts skills include Power Query to trim spaces and merge columns, so you automate cleaning steps and ...

Biotech and life sciences companies operate on the cutting edge of science, but their finance teams often work with dated tools and processes. In addition, key stakeholders often include private ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

In today’s data-driven world, the ability to quickly and accurately analyze information effectively is a pivotal skill across a wide variety of different industries. If you have large amounts of data ...

One drawback of working for so long in the data industry is that I often misjudge what people think about when they think about data. Particularly, I've observed a common misunderstanding about ...