Elementary
Elementary DataReviews from AWS customer
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Best open source dbt native data observability tool
What do you like best about the product?
Smooth inegration with dbt, and great features like alerting, anomaly detection, observability report etc.
What do you dislike about the product?
I only have positive experience so far with Elementary.
What problems is the product solving and how is that benefiting you?
Tracking my dbt models and test run, failures, runtimes, complied code. Viewing the all in one place in EDR report.
Elementary Data - A game changer for proactive data quality and discovery in dbt
What do you like best about the product?
Elementary Cloud has been a game-changer, providing a seamless, minimal-effort implementation and direct integration with our dbt Core environment. Getting started with Elementary was incredibly straightforward, with no major configuration changes needed for our dbt project. After a simple package installation and granting basic read access to the Elementary schema in our warehouse, we were up and running the same day!
The integration with Slack has proven invaluable, as our team receives real-time alerts that keep us on top of potential data issues as they arise. Being able to collaborate with teammates within our primary communication tool makes troubleshooting faster and easier.
The platform’s UI is another standout feature. It's clean, intuitive, and perfectly balanced for both technical and non-technical users. And it includes column level lineage!!
And last but definitely not least, the Elementary support team is phenomenal! Their responses are timely, their recommendations impactful, and they genuinely listen to our needs. Love working with them!
The integration with Slack has proven invaluable, as our team receives real-time alerts that keep us on top of potential data issues as they arise. Being able to collaborate with teammates within our primary communication tool makes troubleshooting faster and easier.
The platform’s UI is another standout feature. It's clean, intuitive, and perfectly balanced for both technical and non-technical users. And it includes column level lineage!!
And last but definitely not least, the Elementary support team is phenomenal! Their responses are timely, their recommendations impactful, and they genuinely listen to our needs. Love working with them!
What do you dislike about the product?
Our dislikes are very few, especially knowing that upcoming feature enhancements will address these concerns.
But to call out something specifically...One dislike is that I'm not as creative as their marketing team! Love their "I want data, not your opinion!" slogan!
But to call out something specifically...One dislike is that I'm not as creative as their marketing team! Love their "I want data, not your opinion!" slogan!
What problems is the product solving and how is that benefiting you?
Enhancing data quality for our core board and company metrics, reducing the time spent on manual validation.
Building trust in data, which drives increased usage across the organization.
Strengthening data governance practices without compromising the speed of delivering high-quality data solutions.
Building trust in data, which drives increased usage across the organization.
Strengthening data governance practices without compromising the speed of delivering high-quality data solutions.
Easy to implement robust anomaly and data quality tests for DBT.
What do you like best about the product?
Elementary provides easy-to-setup and understand data quality and anomaly testing. I also really appreciate their Slack integration and daily reporting.
This simplifies the observing and reporting of our most vital data marts.
This simplifies the observing and reporting of our most vital data marts.
What do you dislike about the product?
Running entire column and table anomaly checks on wide tables could increase your dbt runs by a significant amount.
This is understandable, but users should know that thorough tests take time.
This is understandable, but users should know that thorough tests take time.
What problems is the product solving and how is that benefiting you?
When the number of data marts and your team is limited, Elementary helps you track anomalies. Its automated reporting makes our data engineers and analysts aware of issues with our data sets.
This improves data quality, response, and trust in our organization.
This improves data quality, response, and trust in our organization.
The way we can monitor datasets reliability and the ease of implementation
What do you like best about the product?
What I like most about elementary is:
- Easy to set it up, less than an hour
- Easy to understand, it works perfectly with dbt
- You can have a very clear high-level picture of the datasets (freshness, tests, runs)
- Slack community and support
- You can have daily alerts (based on your needs)
- Easy to set it up, less than an hour
- Easy to understand, it works perfectly with dbt
- You can have a very clear high-level picture of the datasets (freshness, tests, runs)
- Slack community and support
- You can have daily alerts (based on your needs)
What do you dislike about the product?
The only thing I don't like about Elementary Data, but it's not something that discourages me from using the tool, is the fact that after some major upgrades, some problems arose.
What problems is the product solving and how is that benefiting you?
Elementary Data tries to solve data quality problems. We can alert users with ease and ensure fast resolution, especially for high-priority issues.
Great tool for visualising dbt tests
What do you like best about the product?
Really nice integration with dbt core. Great UI for visualising data tests
What do you dislike about the product?
Downside - No way to test sensitivity of anomaly detection tests if you have multiple anomaly detection tests on a model. I use the where condition to set up tests on individual events in my data models and unfortunately there is no current way for me to monitor if my Z score is sensitive enough/too sensitive
What problems is the product solving and how is that benefiting you?
It has allowed me to set up anomaly tests which is awesome. It also gives my stakeholders a more user friendly UI to observe data tests set up with dbt.
Awesome, lightweight data observability tool that's dbt native
What do you like best about the product?
Most observability tools I've seen fall into two camps, either open source and really hard to use, or have total vendor lock in. Elementary straddles that line of being open source and built on top of your dbt stack, but is still very easy to set up and configure. The price point for elementary cloud is much more accessible for small startups to get started with data observability, which in my experience is walled off to enterprise-scale companies, despite often being needed in smaller company sizes.
What do you dislike about the product?
if you don't like dbt or don't have dbt set up, there's nothing to work with here. I think the company is still young and more edge cases are still being worked out, but otherwise, pretty happy so far.
What problems is the product solving and how is that benefiting you?
Anomaly detection, one view for all test failures, data lineage, pipeline health status
The way to speed up our datasets reliability in TUI Musement
What do you like best about the product?
The most that I like from Elementary is:
- Easy to setup, just in a few minutes
- Easy to understand, the UI and the integration with DBT is very smoothy
- Provides a clear high level picture of the datasets and models which you are working
- Nice alerts integrations
- Easy to setup, just in a few minutes
- Easy to understand, the UI and the integration with DBT is very smoothy
- Provides a clear high level picture of the datasets and models which you are working
- Nice alerts integrations
What do you dislike about the product?
Probably what I miss on the Elementary open version are some very useful features, such as the Catalog + the lineage at column level.
What problems is the product solving and how is that benefiting you?
At TUI Musement is the way that we have to track all our tests within our DBT models and have a clear and real picture of the reality of our datasets.
Great slack connect for dbt core setup
What do you like best about the product?
- Easy to play plugin
- Integration to slack
- Ability to send slack summary and individual data alerts
- Integration to slack
- Ability to send slack summary and individual data alerts
What do you dislike about the product?
- No modular APIs or customizations possible
- Ability to send alerts by threads for repeated failures
- Ability to send alerts by threads for repeated failures
What problems is the product solving and how is that benefiting you?
We are now able to alert users with data quality with ease and ensure fast resolution
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