Enterprise AIOps

Chapter 4. Data: Your Most Precious Asset

When it comes to your organization’s data, you can’t manage what you don’t see, and you certainly can’t protect what you aren’t tracking.

AI relies on large volumes of historical data and advanced ML methods to generate insights. Data is the starting point for AI development. It’s critical you establish data management as a fundamental competency, ensuring your teams have the tools needed to properly handle and curate data.

The amount of data available today is exploding as organizations continue to accumulate information at an exponential rate. This growth complicates our ability to understand what data exists, where it exists, who can use it, and how it can be used to generate better outcomes.

It’s critical that your organization find and develop the technologies, implement appropriate policies, and help train employees to adapt to the changing data-centric environment.

Data’s Role in AIOps

An AI project’s success depends on data readiness (e.g., is the data cleansed in a standard format? is incomplete data removed/filled? etc.) both for training AI models and operationalizing AI capabilities. Data readiness for AI can be measured through the key drivers of availability, accessibility,¹ timeliness, accuracy,² usability,³ form, quality,⁴ provenance,⁵ and security.⁶

Accuracy

The degree to which data correctly describes the “real world” object or event being described.

Usability

A measure of how reliable the data is. Data that ...