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 ...

Innovative technologies of the Fourth Industrial Revolution (4IR) are transforming and modernizing the way data is generated, collected, and analyzed across different industries and fields of study. 1 ...

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 ...

What if you could transform the way you analyze data in just 12 minutes? Picture this: a mountain of raw numbers and spreadsheets that once felt overwhelming now becomes a treasure trove of actionable ...

In this technology cast study, we’ll examine MeritData, Inc., a leading big data analysis technology and service provider in China. The company’s product is called Tempo, a big data platform that has ...

In the fast-paced world of financial services, data analysis plays a crucial role in solving complex business problems and extracting valuable insights. Excel, a powerful and versatile tool, has ...

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 ...

Which is more important – understanding what happened to your business last week or understanding what's happening right now? Well, both can provide useful insights that you might be able to use to ...

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 ...