What are Structured, Semi-Structured, and Unstructured Data? — Analytics uses data. There are many types of analysis and three main types of data. Using the data for analysis requires knowing and adapting to the way it is organized. …

Happiness as a Data Story — Exploratory Data Analysis is an important type of analytics. This provides a summary of data to give understanding of contents. The summary includes counts of columns and rows, and statistics. …

Top Machine Learning libraries for Data Analysis and Data Science. — Data Science and Data Analytics are strongly interlapping. Performing analysis can require advanced analytics that are easier to program for better control of variables than use an interface. Python is a language with many libraries for pre-built function for advanced analysis using machine learning where all variables can be selected…

Not just Security, but Efficiency — For any data project, collecting the needed facts requires research and placing into a file. Most times, this means either a spreadsheet or plain text file. Basic projects, such as recording sales inventory by transaction, are many lines, but small in size due to associated fields. building datasets for more…

Similar but not the Same — There are four types of analytics: Descriptive, Diagnostic, Prescriptive, and Predictive. Selecting the right type requires knowledge of analysis and the needs of finding information to problem solve. Most analysis is gathering information and generating knowledge in response to a need usually based on a problem. With four types, each…

Finding value in selecting for requirements For service lifecycle, there is a flow from inception to delivery and after. Starting with requirements, creates a phase that makes guidance for the project. Deciding the needs and goals of a project is important for a service same as with a product. …