Advanced augmented analytics (Do You Know)

“Do You Know” is a comprehensive suite offering a range of no-code, AI-powered analyses designed to empower users to execute intricate analytics tasks effortlessly. Positioned as an advanced augmented analytics engine, it actively seeks anomalies and patterns within datasets, presenting findings in insightful visualizations.

Key Features

Predictive Analytics:

Harnessing the power of machine learning algorithms, “Do You Know” performs predictive analytics by analyzing historical data to forecast future outcomes. This functionality finds applications in diverse domains, including sales forecasting, inventory management, and risk assessment.

Continuous Learning:

“Do You Know” operates as a dynamic system, perpetually learning and deciphering data intricacies. Its adaptive nature ensures ongoing improvement in analysis precision and relevance.

User-Friendly Insights:

The suite is tailored to serve users in the most user-friendly manner possible. It distills complex data insights into an understandable format, facilitating a nuanced understanding of the data landscape.

Automated Data Discovery Methods

“Do You Know” encompasses the following automated data analysis methods, each designed to unravel specific insights:

Trend Analysis:

Identifying and analysing trends over time enables users to discern patterns and make informed decisions.

Outlier Analysis:

Detecting outliers within datasets is crucial for maintaining data integrity and identifying anomalies that may impact statistical analyses.

Correlation Analysis:

They evaluate the strength of relationships between selected Key Performance Indicators (KPIs) and provide insights into how variables are connected.

Forecast Analysis:

Predictive analytics involves using historical data to predict future trends or outcomes. This helps make bold decisions by foreseeing what might happen in the future based on patterns and insights derived from past information.

Classification Analysis:

This process involves organizing data into specific categories or groups, which helps recognize and understand the recurring patterns and trends present within datasets.

Text Analytics:

Text analytics refers to the process of analyzing and extracting valuable information and insights from textual data. It involves using various techniques and tools to process, interpret, and derive meaning from unstructured text data.

Regression Analysis:

Investigating relationships between variables, offering insights into the impact of one independent variable on another dependent variable within a dataset.

Clusters:

A cluster refers to a group of data points or observations with similar characteristics, patterns, or features. The goal is to group data points together based on their similarities and form clusters.

Lumenore’s “Do You Know” module combines advanced analytics capabilities with a user-friendly interface, providing a sophisticated yet accessible platform for users to derive meaningful insights from their data.