Analytics is a topic area that has developed from Big Data and Data Mining. It consists of making behavioural observations. In the simplest case, this happens retroactively, but can also take the form of predictions.
Enterprises need to decide on a case-by-case basis to what extent an analytics solution can efficiently be implemented in the context of existing data, budget, and technology. The particular approach should be chosen to align with the enterprise’s corporate strategy in order to glean valuable insights from Marketing and Business Intelligence since these areas are often tightly linked.
Business Intelligence (BI) is a technology-driven process to analyse data and present exploitable information to help management, managers, and other end users make well-founded leadership decisions.
BI spans a multitude of tools, applications, and methods that enable companies to collect data from internal systems and external sources and prepare them for analysis, develop and carry out polls, and create reports, dashboards, and data visualisations to make analysis results available to both an enterprise’s decision-makers and operative employees.
These two terms are often used in the same context, making it difficult to view them as two separate areas. Big Data concerns especially large amounts of data that can’t be effectively processed with traditional methods. Data Mining, on the other hand, does often deal with large amounts of data, but isn’t limited to Big Data. Data Mining describes the actual process of analysing data in regard to relevant contexts and can also be used for small amounts of data.