Analyst Perspectives

Analytics processes are all about how organizations use data to create metrics that help manage and improve operations. Yet, the discipline applied to analytics processes seems to be lacking compared to data processes. I’ve pointed out that the weak link in data governance is often analytics. Organizations can also do a better job tying AnalyticOps to DataOps and do more to define and manage metrics. Our research has shown that creating and managing metrics in a semantic model improves analytics processes.

Some analytics software vendors are starting to tackle this problem, offering semantic models, semantic layers, metrics stores and headless business intelligence. Kyligence is among those vendors. The company recently expanded its portfolio to include Kyligence Zen, which it refers to as a metrics platform. Zen includes four key components: a metrics catalog, metrics automation, goals and an application programming interface (API).

The metrics catalog enables organizations to define and manage metrics, including the ability to import metrics definitions from business intelligence systems and data warehouses. Kyligence and its partners also provide a set of metrics templates which serve as a starting point for specific types of analyses. Metrics automation, another component of Zen, uses artificial intelligence and machine learning to extract information from usage logs, SQL history, data warehouses and data lakes to automatically generate and maintain entries in the metrics catalog. It’s a form of augmented intelligence, designed to make analytics processes easier. We assert that by 2025, 9 in 10 analytics processes will be enhanced by AI and machine learning to streamline operations and increase the value that can be derived from data.

The goals portion of Zen focuses on a key aspect of metrics: comparing the value of a metric to its associated target. The goals module also aligns specific metrics with goals of the organization. These goals can be structured in a hierarchical fashion with subgoals, helping to drive overall goals. The API for Zen enables headless BI operations – in other words, programmatic access to the metrics that don’t require human intervention. For example, you may have metrics on cloud cost management that are monitored continuously to shift workloads from one type of resource to another in order to optimize costs.

The metrics catalog at the core of Zen provides consistency and trust through a single repository for the various metrics shared across an organization. The value of Zen could be enhanced through further integration with more catalogs and business intelligence tools, extending the consistency across more data and analytics processes.

Organizations need to be more disciplined about metrics processes, which deliver significantly increased satisfaction with analytics and better governance capabilities. Kyligence Zen provides a metrics platform that enables that discipline. I recommend that organizations looking for better management of metrics consider Kyligence Zen.

Regards,

David Menninger