Variety
The degree to which data are available from different data sources.
- •Richer insights and more robust models from integrating diverse data types and sources (structured, unstructured, internal, external).
- •More comprehensive understanding of complex phenomena by considering multiple perspectives.
- •Enhanced innovation and discovery through the combination of previously siloed information.
- •Improved resilience of analytical models by training on a wider range of data scenarios.
- •Limited analytical capabilities and potentially biased insights if relying on a narrow set of data sources.
- •Missed opportunities that could be uncovered by combining different types of data.
- •Difficulty in creating a holistic view of customers, markets, or operations.
- •Models that are not robust or generalizable to new, unseen data types.
Story
Logistics: Combining data from the Terminal Operating System (TOS), vessel AIS feeds, weather services, gate camera OCR, and customs systems provides a comprehensive and robust operational picture for decision-making.
Market Analysis: Integrating internal sales data with external market research reports, economic forecasts, social media trends, and news feeds to build a more accurate and holistic market model.
Customer Insights: Creating a 360-degree customer view by consolidating data from CRM, e-commerce transactions, website analytics, support tickets, social media interactions, and satisfaction surveys.
Logistics: Relying solely on manual input from operators for recording operational status (e.g., equipment breakdowns), without cross-referencing system logs, sensor data, or maintenance records.
Market Analysis: Basing market trend predictions only on internal sales data without considering broader economic indicators, competitor activities, or industry reports.
Customer Insights: Understanding customer sentiment only through direct complaints, without analyzing social media mentions, survey feedback, or product reviews.