Description: Guided Analytics is a data analysis method that provides users with step-by-step instructions to effectively explore and understand their data. This approach focuses on facilitating decision-making by offering an intuitive and accessible interface, allowing even those without technical experience to perform complex analyses. Through interactive visualizations and automated recommendations, Guided Analytics helps users identify patterns, trends, and anomalies in their data. Its relevance lies in the growing need for organizations to leverage large volumes of data to gain valuable insights, optimize processes, and improve strategic decision-making. This type of analytics is often integrated into various analytics platforms, where users can perform ad hoc analyses and generate customized reports without relying on IT teams. In a cloud environment, Guided Analytics becomes an essential tool for observability, enabling companies to monitor and analyze the performance of their applications and services in real-time, thus facilitating a quick response to any issues that may arise.
Uses: Guided Analytics is primarily used in the field of business intelligence to enable users to perform data analyses without the need for advanced technical knowledge. It is applied across various industries, such as finance, healthcare, and retail, where analysts can explore historical and real-time data to make informed decisions. Additionally, it is used in cloud observability, helping companies monitor the performance of their applications and identify issues before they affect end users.
Examples: An example of Guided Analytics is the use of tools that allow users to create interactive dashboards and perform data analyses through a graphical interface. These platforms provide tutorials and guides that facilitate data understanding and the creation of customized visualizations. Another example is the use of data visualization tools that enable users to connect different data sources and generate visual reports easily.
