Anomalo Data Quality

What do you like best about the product?

Users praise Anomalo most for its powerful, AI-driven anomaly detection that automatically monitors data without extensive manual configuration. Its automated root-cause analysis is also a key strength, saving significant time during data incidents

What do you dislike about the product?

Customers report that the data quality platform Anomalo has several notable drawbacks, including a high volume of unhelpful alerts, a non-transparent pricing structure, and a lack of certain advanced capabilities.

What problems is the product solving and how is that benefiting you?

Anomalo solves data quality problems for enterprises, particularly with large volumes of unstructured text, by using AI to automatically detect anomalies and their root causes, improving trust in data, accelerating AI/ML projects, and reducing operational burdens and costs associated with poor data quality. The benefit to users is increased confidence in their data, which leads to better decision-making, more reliable AI models, and freed-up resources for innovation rather than data firefighting.

What do you like best about the product?

We like that we can pick precisely what we want to watch and how we want to monitor it, all credit goes to the tool's capability to build up our own tests.

What do you dislike about the product?

Anomalo does not give us a clear understanding of the costs involved in running validations on the Data Warehouse.

What problems is the product solving and how is that benefiting you?

Anomalo has improved cooperation and involvement among our teams and provided us with insightful data that even non-technical business users can comprehend and apply.

What do you like best about the product?

Nice platform with useful features that gives a lot of anomaly detection flexibility

What do you dislike about the product?

sometimes there are to much features, would be nice to have a guided question to set test rules and validations

What problems is the product solving and how is that benefiting you?

Anomalo gives us the ability to see if there increase in nulls or drops in specific column and etc

What do you like best about the product?

It's easy to set up new tables with automatic checks and for stakeholders to dive into the data.

What do you dislike about the product?

Some of the automated outlier detection models don't work very well. For example, predicting bounds outside of possible value ranges.

What problems is the product solving and how is that benefiting you?

We are able to spot data issues much closer to real time. Previously data quality issues could go days or even weeks without notice.

What do you like best about the product?

It's the best data quality/validation tool for engaging business users and developers. The Root Cause Analysis features provide us with better arguments when approaching developers and less work digging into what is causing data quality problems.

What do you dislike about the product?

Customization needs to be more present. For use cases outside of the original tool, things can become infeasible. Also, it does not provide a precise view of collateral cost running validations of the Data Warehouse (which can be a problem in big projects with large tables).

What problems is the product solving and how is that benefiting you?

We are detecting data quality issues and communicating them to engineering and business users. It benefits us by providing more engagement and collaboration among teams (product, data, engineering) to interpret and solve data incidents.