Data input: Determine the requirements and collect the data. This involves a bit of investigatory work like talking to stakeholders, finding out who the data keepers are, and gaining access to the data itself.
Data preparation: The strategy and tactics of preparing data for its ultimate purpose of producing analytic insights. This includes cleaning and consolidating raw data into well structured, analysis-ready data. This also includes testing the outcomes at each part of the preparation process to ensure the analysis is yielding the desired outcomes.
Data exploration: Data exploration, or exploratory data analysis, is the process of surveying and investigating a large dataset through sampling, statistical analysis, pattern identification, visual profiling, and more. The methods are not necessarily scientific or conclusive, but rather, they serve to build understanding that leads to more informed data transformation.
Data enrichment: Enrich and augment data with additional inputs and datasets to further inform an analysis. This step in the data analytics process is crucial for revealing novel insights by looking at data from a new perspective.
Data science: The application of more advanced data methods for deeper, harder-to-extract meaning and insights that are largely unobtainable through more rudimentary modalities of data processing. This includes algorithms, model training, machine learning or ML, artificial intelligence or AI, to name a few.
Business intelligence: The combined outcomes of an organization's data, software, infrastructure, business processes, and human intuition. The results deliver actionable insights through reports, dashboards, and visualizations to help inform business decisions.
Reporting: The outcomes of data analytics need to be shared in an effective way that preserves the knowledge gained. Reporting is organizing that knowledge and its outcomes in an easy-to-comprehend format.
Optimization: As variables change over time, models need to be optimized and improved to continue to fulfill their initial purpose or to evolve from this purpose based on new inputs or changing characteristics.