Migrating to a Modern Data Stack

A centralized observability layer for your new environment

The Problem

With a modern data stack, your organization can reduce its data engineering costs by 90% or more. This cost reduction comes primarily from eliminating the need to create data pipelines that you need to maintain and monitor over time.

As data architects lay out the foundation for data ingestion, storage, ETL, and analytics, they look to serve their new architecture with high quality data and create a stack that can automate and observe the quality of data over time. 

The Solution

Centralized data observability for all data

The move to the modern data stack is often stemmed by the realization that data is not used to its fullest potential. Telmai works as a single layer on your entire data pipeline, monitoring data from structured sources such as data warehouses or delta lakes, streaming data, data ingested from data lakes and cloud storage systems, or coming from API calls. With a centralized observability layer, your modern data stack operates to its fullest potential.

Monitor the data, not the job runs

Telmai monitors data itself, its content and values. This is complementary to the infrastructure observability metrics provided by cloud data warehouses, data lakes, and delta lakes such as scheduled job statuses, current running jobs, start and finish run times, number of API calls, and other operational metrics.

Tap into your data without slowing it down

Telmai’s architecture decouples its compute layer from the underlying operational databases and data warehouses, providing you with monitoring capabilities without slowing your operational databases. 

Start your data observibility today

Connect your data and start generating a baseline in less than 10 minutes. 

Telmai is a platform for the Data Teams to proactively
detect and investigate anomalies in real-time.
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