Reporting & Alerts:
Most common use of BI includes: simple or production-ready reports, parameter-driven reports, drill-down reports or alerts. Alerts signal monitoring events or data values sent via email or messaging app.
Ad-hoc analysis, but queried from a multi-dimensional (OLAP) cube. Users can drill down a dimensional hierarchy or drill across multiple dimensions (pivot), or both.
A type of advanced analytics, which is commonly employed by data scientists to create predictive models or forecasts. These models can be used in visualizations or data discovery. Sometimes referred to as data mining or machine learning, proper usage of which will help business leaders gain insights into trends and subtle business patterns, optimize decision making, and assess risks.
Measures business in key areas (or KPIs) at regular intervals to identify trends and detect problems. Performance management is typically a management tool for leveraging BI to manage and improve business processes.
A type of ad-hoc analysis to create a mashup of data visualizations and dashboards to present data. Recent excitement in this BI style comes from innovative tools such as Tableau and Qlik Sense, which incorporates a self-service graphical user interface (UI) to ease the data selection and BI mashup.
Data visualization, inclusive of dashboards, is a visual communication of data through charts, plots, tables, and statistical models to convey custom information effectively to information consumers.
Big Data Analytics:
This is BI for large sets of data, both structured and unstructured. Current relational databases and BI applications deal well with structured data, regardless of the size. Nevertheless, alternatives to current relational databases and BI tools are often necessary to analyze textual data apart from social media content, email messages, phone records, sensor data collected from the Internet of Things (IoT), etc.