Anomalo Data Quality

What do you like best about the product?

The biggest benefit for me has been the time savings. Instead of manually monitoring datasets or waiting for someone to notice an issue in a dashboard, Anomalo flags unusual patterns proactively. It has helped us catch data problems before they impacted reporting, which has increased confidence in our data.

What do you dislike about the product?

I would appreciate more customization options in specific dashboards and reporting views. The current functionality is effective, but added flexibility would allow for a more tailored experience to meet the needs of individual teams.

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

Anomalo is assisting us in addressing challenges related to data reliability and quality. By proactively detecting anomalies and data issues, it facilitates faster troubleshooting and prevents inaccurate data from reaching our dashboards and business users. This allows us to spend less time on reactive investigations and instills greater confidence in our analytics.

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.

What do you like best about the product?

+ As an administrator it was really easy to setup Anomalo on our existing infra and get it up and working quickly. This means that we could start finding value really quickly. We set Anomalo up with our k8s infra and it was fairly easy
+ Anomalo conistently finds small issues in our datasets and helps us identify the cause even before vendors detect them. We've pushed issues upstream multiple times when the data producer isn't aware of the issue yet
+ In the past, we've explored many different solutions for this problem and Anomalo has worked much better than all of our home grown solutions in terms of adoption as well as value-added
+ Anomalo UI is extremely easy and awesome to use. This makes it much easier for data analysts and non technical teammates to onboard and add custom checks vs creating a code change.
+ Anomalo's team has been incredibly responsive and helpful

What do you dislike about the product?

- Checks are not very configurable. If a dataset gets a sudden increase in rows which is expected, Anomalo will alert 2-3 days before it learns the new normal
- Anomalo's out of the box tests can be expensive(in runtime + cost of computing metrics). They scan all columns even the ones which might not be used anywhere resulting in some wasted work
- Alerts can be noisy and its up to the team to make sure they have a process to work through each alert

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

Anomalo helps us figure out if our datasets are actually correct and match what we expect the data to be.This gives the data teams a lot more control over our datasets and allows us to scale how many datasets we work on without needing more engineers.

What do you like best about the product?

Anomalo is a great tool for monitoring general data quality. Beyond the default metrics, like data freshness and availability, it's excellent to be able to configure custom verifications. To highlight some awesome features, the anomaly history is very useful for understanding the main variations in column statistics. In the custom possibilities, being able to configure alerts using multiple columns, multiple tables or SQL brings several monitoring configurations.

What do you dislike about the product?

One limitation that can be mentioned is the impossibility of configuring a BigQuery wildcard table as one single table. The Google Analytics integration with BigQuery is an example; the data is saved in a wildcard table but monitoring the data quality of users' interaction with our website is essential, so it would be great to have this feature in Anomalo.

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

We usually use Anomalo for monitoring our main tables, which contain extremely important data that is used for financial purposes, for instance. It's extremely important to ensure the quality of our sales data because errors can cause problems for the company. We also use Anomalo for monitoring data that is used to feed our ML models, also to assure quality and be able to act over problems quickly.

What do you like best about the product?

Slack alerts visualization
Built in checks

What do you dislike about the product?

Admin page is very not user friendly
Many bugs
Tables are not immediately updated in the system
Team does not respond to feature requests or bug reports
UI is bad

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

Finding anomalies in data helps identify issues in pipeline

What do you like best about the product?

Integration with AWS Athena / Glue
Good API for running operations and getting stats
Very good visuals for non-technical people
Helpful staff

What do you dislike about the product?

Relatively early in their development
Problems with nested structs / objects (not arrays)
Possibly attempting too many integrations, some can be a bit buggy

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

Data quality issues at the cell level, helping us with our customers

What do you like best about the product?

Easy to use UI, reliable scheduling and great support from the Anomalo team.

What do you dislike about the product?

It's somewhat limited in what datasources checks are supported on.

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

Catching issues before they're noticed by stakeholders is essential to our success.