
+ 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 Review collected by and hosted on G2.com.
- 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 Review collected by and hosted on G2.com.
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