Zaloni: Automated Data Governance and Observability

ve auto governance actions such as pseudonymizing data that is deemed to be classified based on our supervised machine-learning (ML) capability and recommend follow-on steps to execute further actions. The repetitive steps are automated with recommendations and guide users to ensure consistency.

The glossary capability allows data stewards to set up a business glossary relevant to the data domain with related datasets, reports, and applications and provide a consistent definition of attributes and KPIs.

Data citizens, the second persona in the platform, gain access to data sets without duplicating the data and can use it on their preferred tools. We also provide out-of-the-box sample data sets and sample rules that enable users to work on ready-made templates and modify them as required without creating anything from scratch. Arena brings the consumption metadata from those tools to provide data observability.

The Arena platform is highly scalable. Our customers catalog, access, and provision petabytes of data with our platform. Our implementation partners leverage APIs from 3rd party applications to fast track implementation. We provide a robust set of APIs for 3rd party applications to connect and authenticate via OpenID Connect.

From a deployment standpoint, we provide a multi-tenant capability that enables large enterprises to implement a data mesh architecture by a line of business or domain for each department and allows them to share rules and artifact templates with other teams.

Could you share with us a customer success story?

A financial services client is in the business of monetizing anonymized data products via a data marketplace. Their governance team used spreadsheets to categorize data domains and taxonomy, and downstream applications depended on manual updates of the spreadsheets. They were challenged with data integrity issues because the end user applications weren’t updated with the most recent information due to incomplete spreadsheets. After leveraging our platform, they migrated existing spreadsheets and data taxonomy and cataloged Tableau dashboards and reports to provide lineage between data domains, topics, and usage of the dashboards. It allowed them to track the consumption of their data products.

Another customer of ours, a major consulting client, faced challenges centralizing intellectual property (IP) created by thousands of consulting projects. Their goal was to find the right code base and project artifacts from prior engagements to get a head start on new projects and reduce duplication of effort. After onboarding Arena, the customer was able to catalog Github repos, code snippets, project plans, and BI reports in searchable UI. Additionally, it allowed them to quickly contact technical and business owners to get more details of those projects and enabled the company to provide the right level of access to IP assets.

What does the roadmap look like for Zaloni?

We are observing an increasing trend among companies to build user applications using metadata captured from various places and present metadata, consumption, and relationships in a social graph to provide better explainability and impact analysis.

We are also seeing significant traction in having native connectivity to the metadata layer of modern Lakehouse platforms such as Databricks and Snowflake and by leveraging the extensibility provided by those platforms. We plan to expand our reach to Google Cloud Platform (GCP) by the year-end. Lastly, from a geographical standpoint, we will continue to deepen our roots in the North American market and expand our footprint into the European market.