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Data & Business Intelligence encompasses the strategies, technologies, and practices for analyzing and utilizing data to support business decisions.
This segment covers deriving and applying analytics and metrics to support decision-making. It includes analysis types, aggregation and segmentation logic, comparisons and trend views, and interpretation frames for results. The focus is on structuring evaluations and ensuring metrics are traceable, independent of how results are visualized or organizationally adopted.
An analytical approach for evaluating groups of users over a specific time period.
A workshop to define and establish KPIs that make business success measurable.
A structured method for visualizing and analyzing metrics.
Business Intelligence (BI) includes technologies, applications, and practices for analyzing data and providing actionable insights.
KPI is a measurable number that evaluates the success of a company or a specific activity.
An analysis of the differences between leading and lagging indicators in performance evaluation.
Metric hierarchies are a structured system for organizing and visualizing metrics and their relationships.
OLAP (Online Analytical Processing) is a technology that allows for fast complex queries on large datasets.
Time series databases are specialized data stores for storing and analyzing time-ordered data.
Apache Superset is a modern data visualization tool that provides a user-friendly interface for data analysis.
Looker is a data analytics and business intelligence platform.
An open-source tool for data visualization and analysis.