Author: Frank Z

Logs often take up the majority of a company's data assets. Examples of logs include business logs (such as user activity logs) and Operation and Maintenance logs of servers, databases, and network or IoT devices.

Logs are the guardian angel of business. On the one hand, they provide system risk alerts and help engineers quickly locate root causes in troubleshooting. On the other hand, if you zoom them out by time range, you might identify some helpful trends and patterns, not to mention that business logs are the cornerstone of user insights.

A unified analytic database is a holy grail for data engineers, but what does it look like specifically? It should evolve with the needs of data users.

Vertically, companies now have an ever-enlarging pool of data and expect a higher level of concurrency in data processing. Horizontally, they require a wider range of data analytics services. Besides traditional OLAP scenarios such as statistical reporting and ad-hoc queries, they are also leveraging data analysis in recommender systems, risk control, customer tagging and profiling, and IoT.