Measuring Up: Kyligence Offers New System For Developing Data Analytics Metrics
The Kyligence Zen intelligent metrics platform, now generally available, addresses the problem of inconsistent data metrics throughout an organization that can hinder data analysis initiatives.
Kyligence is boosting the capabilities of its data analytics offerings with the general availability of Kyligence Zen, an intelligent metrics platform for developing and centralizing all types of data metrics into a unified catalog system.
Kyligence Zen provides a way to build a common data language across an organization for consistent key metrics and what data managers call a “single version of the truth.”
A common data analytics problem within businesses is a lack of shared definitions for key metrics in such areas as financial and operational performance.
“Organizations struggle with inconsistent metrics, which impacts trust and slows down decision making,” said Luke Han, Kyligence co-founder and CEO, in a statement.
Kyligence Zen is designed to tackle that problem by providing unified and intelligent metrics management and services across an entire organization. “Kyligence Zen provides a new way to build a single source of truth based on a metrics catalog and introduces AI-augmented capabilities to automate data processing, modeling and insights,” Han said.
Kyligence Enterprise, the company’s flagship multi-dimensional analytics platform is designed to analyze massive datasets with its data modeling, query and processing capabilities. Kyligence Enterprise is based on the open-source Apache Kylin distributed OLAP engine that was developed by Kyligence’s founders. The platform is offered for on-premises deployment and for public and private clouds.
A key component of Kyligence Zen is the Metrics Catalog, which provides a central location where business users can define, compute, organize, and share metrics. The intelligent metrics store component of Kyligence Zen has been in private beta since June 2022.
Within many large organizations, operational divisions and business units maintain their own data tools and data stacks, including data metrics and semantics. And that can lead to “misunderstandings or chaos” when managers and employees across a company try to exchange or match data, said Kai Liu, who leads North America for Kyligence, in an interview with CRN.
“With this unified metrics catalog, we can solve this kind of issue because everyone actually uses the same [data] definition in this catalog and it’s a single source of truth,” Liu said.
Also available in Kyligence Zen are Metrics Templates with dozens of pre-defined standard metrics, many tailored for specific industries, that eliminate the need to develop metrics from scratch.
The platform includes Zen Metrics Language (ZenML), a low-code/no-code YAML-based descriptive language that data engineers can use to define metrics, dimensions and the underlying relational datasets. It also provides open APIs to popular business analytics tools such as Tableau and Microsoft PowerBI.
ZenML acts as a semantic layer that converts technical data into business metrics, enabling non-technical users to understand, explore, and get insight out of traditional data warehouses, according to Kyligence. ZenML encourages the separation of data modeling and data visualization and facilitates a central definition of business data language for all downstream data consumers.
Also part of the Zen platform is Auto Root Cause Analysis, new functionality that helps users uncover concealed patterns in metrics and better comprehend statistical anomalies. Also new is Kyligence Connector for Excel, a drag-and-drop tool for analyzing metrics defined in Kyligence Zen using Excel.
Kyligence Zen is being offered on both a software-as-a-service and platform-as-a-service basis, Liu said, as well as packaged with Kyligence Enterprise and Kyligence Cloud. Current Kyligence customers can add Kyligence Zen to their existing implementations.
Kyligence, based in San Jose, works with a range of service partners including systems integrators, implementers and consultants. While Kyligence Zen works with data stored in Amazon Web Services S3, Liu said partners can help integrate the system with other data platforms, such as Snowflake and Databricks, applications and database systems. And solution providers with vertical industry expertise can help clients develop business metrics for their specific industries.
“Because we only focus on the metrics layer, we still need partners to build a whole [data] ecosystem,” Liu said. “I can see a lot of opportunities to work with our partners – solution providers – to get a better total solution.”