The 10 important characteristics and properties of (Big) Data you should know to prepare for both, the challenges and opportunities of Big Data initiatives.
CRISP-DM is a common standard for machine-learning projects and remains one of the most widely used data mining/predictive analytics methodologies.
Boxplot is a method for graphically depicting groups of numerical data through their quartiles. They summarize data from multiple sources and display the results in a single graph.
Quartiles are especially useful when you’re working with data that isn’t symmetrically distributed, or a data set that has outliers.
Data onboarding—the preparation of unfamiliar data from disparate sources, both internal and external to the organization—is a complex process.
The process of manual data cleansing prior to data analysis is known as Data Munging, also known as Data Wrangling.
We live in an exciting yet challenging time for data visualization. As we enter the information age, it’s both exciting and terrifying to imagine what the future holds in store for us.
Data storytelling requires a structured approach for organizing and communicating the insights from data using three core components - data analysis, visualization, and narrative.
Cohort Analysis is one of the most powerful and demanded techniques available to marketers for assessing long-term trends in customer retention and calculating life-time value.