Sold by: AnomaloÂ
Deployed on AWS
Anomalo's Data Quality Monitoring uses automated AI to detect data quality issues and understand their root causes, before anyone else. Detect, root cause, and resolve issues found in the data driving your business.
Overview
Go beyond data observability with deep data quality monitoring you can trust.
- Powerful data quality checks that use unsupervised machine learning
- Automatically identify missing and anomalous data
- Easy for everyone, API or no-code configuration
- Deep monitoring that looks inside your tables
Highlights
- Powerful data quality checks that use unsupervised machine learning
- Automatically identify missing and anomalous data
- Easy for everyone, API or no-code configuration
Details
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Deployed on AWS
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Dimension | Cost/12 months |
|---|---|
units | $1.00 |
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Customer reviews
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41 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Ashish T.
Tailored to our requirements.
Reviewed on Jun 11, 2023
Review provided by G2
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.
Internet
Using anomalo for anomaly detection
Reviewed on May 22, 2023
Review provided by G2
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
Health, Wellness and Fitness
Anomalo has been a lifesaver for catching data issues early
Reviewed on May 18, 2023
Review provided by G2
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.
Lucas R.
Best tool for actionable insights directly interpretable by business users
Reviewed on May 18, 2023
Review provided by G2
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.
Shashwat S.
Anomalo is the best batteries included data monitoring solution we've come across
Reviewed on May 17, 2023
Review provided by G2
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
+ 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
- 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.