Guides and E-Books
Telmai is Named The Market Leader in GigaOm Radar for Data Observability
Telmai is recognized as a Leader in GigaOm Radar for Data Observability for 2023. The report states, “The platforms’ low-code functionality, considerable automation, and data pipeline support will go a long way with users, as will its attribute-level anomaly detection and support for open architecture.

The Ultimate Guide to Data Observability Tools
Presenting our latest evaluation guide, "The Ultimate Guide to Data Observability Tools." This guide is your one-stop resource, designed to simplify the selection process whether you're drafting an RFP or directly assessing platforms.

7 Key Considerations When Evaluating Data Observability
Assess data observability platforms based on essential parameters such as supported systems, depth of data quality features, scope of remediation, and different pricing models.

4 Types of Data Observability: Which One is Right for You
Understand different types of data observability tools, their pros and cons, and ideal use cases. Determine which one is right for you by seeing a side-by-side comparison of all four.
Case Studies

DataStax Builds Trust in Product Usage Data
Telmai's scalable and fully automated data observability empowers trust in product usage data across 36,000 clusters.

Clearbit Uses Telmai to Deliver Accurate Data to its Customers
Data Observability helps Clearbit bring reliable data to over 4.5 billion IP addresses without a need to increase engineering resources.
Webinars

Product Demo @ Data Demo Day with Solutions Review
Telmai's centralized data observability monitors your data across all formats, across structured, semi-structured, and streaming. Check out our product demo by our Co-Founder/CTO and see for yourself.

How to Build Data Quality as a Product
Many data product managers are tackling data quality issues on a daily basis. In this talk, Clearbit’s Data Product Manager, Ale Cabrera, and Telmai’s CEO/Co-Founder, Mona Rakibe, discuss how to solve this universal problem pragmatically.
Featured Blogs

3 Levels of Data Freshness and Which One is Right for You
Freshness can be categorized into:Table-level Freshness, Record-level Freshness, and Entity-level Freshness. Read our blog to learn more.

Data Quality vs. Data Observability
Data quality and data observability are two important concepts in data management, but they are often misunderstood or confused with one another. Understand the what, why, and how of each.

5 Reasons to Consider Centralized Data Observability
Data Observability has become a critical component of any modern data stack to monitor the stack and ensure data reliability. Learn about centralized data observability and why you should use it.