Ultimate Guide for Data Observability

Telmai Named a Leader in GigaOm 2023 Radar Report for Data Observability

The Ultimate Guide to Data Observability Tools

Navigating the intricate world of Data Observability and Data Quality tools can be challenging. Amidst a sea of solutions, each promising the perfect fit, finding the best tool can seem like looking for a needle in a haystack.

However, choosing the right tool for your ecosystem is pivotal. We have consolidated our learnings from hundreds of conversations with Data practitioners and augmented it with market research into this easy-to-adopt evaluation guide.Our evaluation guide simplifies the evaluation process and guides you through your needs.

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.
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Our comprehensive guide walks through critical areas of consideration like:

Integrations like Data lake, Data warehouse, BI tools, etc
Data Quality Reporting
Data Quality Rules

Data Monitoring
Anomaly Detection
Notification/Alerting and API access

Remediation

Scale/Performance and Deployment Considerations
Total Cost of Ownership (TCO) and Time to Value

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The Leader in Data Quality

Telmai has been named a High Performer in the G2 Data Quality Report. Checkout our 5 star reviews.

About the Author of the Ultimate Guide:
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Mona Rakibe, our Co-Founder and CEO, is the driving force behind business growth, corporate strategy, and operations at Telmai, is a seasoned leader in the Data Management space. With over 15 years of experience propelling product innovation and growth strategies in startups and enterprises like Reltio, EMC, Oracle, and BEA, she has a wealth of insight to offer. In her previous role as a founding product manager at Reltio, Mona was instrumental in steering the product strategy and growth from its early stages to hyper-success. Acknowledged as an industry thought leader, Mona was a nominee for the Silicon Valley Women Data Leader award in 2019. With her robust expertise and relentless drive, Mona is setting new benchmarks in the data management landscape.

Integration

Trusted by

Quick time to value

Telmai's out of the box data quality metrics, ML-based automation, and a low-code, no-code user interface provides you and your team engineering productivity and faster time to value.

70%

Faster detection and resolution of data quality issues by using ML

10X

Cost reduction vs. maintaining data quality rules over time

The Leader in Data Quality

Telmai has been named a "High Performer" in the G2 Data Quality Grid Report of Spring 2023.

Checkout our 5 star reviews.

Customer testimonials

“Our customers deserve the best possible data to make their business grow. Telmai's Data Observability enables us to show the quality of the data that we are delivering to our customers. With Telmai we are able to build data quality KPIs that reflect our data's freshness, completeness, and accuracy to keep and extend the trust that our customers have put in us.”

Harlow Ward

CTO, Clearbit

"When dealing with data sets comprising million of records, Telmai quickly becomes an incredibly useful tool, saving a lot of time and ultimately increasing data quality."

Maria Grineva

SVP Engineering, Dun & Bradstreet

“We chose Telmai because of its flexibility and architecture. Telmai will remain our data observability platform as our data landscape changes. Telmai has lots of adapters in place to quickly integrate with various data sources across cloud providers. In addition, it supports real time API integration for automated decisions in complex workflows.”

Kishore Damodara

AVP of Cloud and Data Engineering, Merkle

"Data anomaly investigations that used to take hours now take minutes and give us more time to focus on the business needs."

Darius Kemeklis

EVP, Myers-Holum

“In searching for data quality and observability, we looked at a few solutions. They were limited to tracking just the data volumes, row counts, completeness, and uniqueness. That was not enough for us. We needed to look inside each attribute and each record to see if our data is drifting or its patterns are changing. Telmai was the only solution that empowered us to do so.”

Alejandra Cabrera

Data Product Manager, Clearbit

“To prepare data for product usage analysis we needed data quality metrics beyond monitoring operational data pipelines and job status checks. While we continue to monitor the quality of the pipeline, we chose Telmai to detect the quality of the data that moves through the pipeline.”