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About

Profile, cleanse, match and deduplicate data in drag-and-drop rules studio. Lo-code UI means no programming skill required, putting power in the hands of subject matter experts. Add AI & machine learning to your existing data management processes In order to reduce manual effort and increase accuracy, providing full transparency on machine-led decisions with human-in-the-loop. Offering award-winning data quality and matching capabilities across multiple industries, our self-service solutions are rapidly configured within weeks with specialist assistance available from Datactics data engineers. With Datactics you can easily measure data to regulatory & industry standards, fix breaches in bulk and push into reporting tools, with full visibility and audit trail for Chief Risk Officers. Augment data matching into Legal Entity Masters for Client Lifecycle Management.

About

Automatically cover thousands of tables with ML-based anomaly detection and 50+ custom metrics. Comprehensive data and metadata monitoring. Exhaustive mapping of all dependencies between assets, from ingestion to BI. Enhanced productivity and collaboration between data engineers and data consumers. Sifflet seamlessly integrates into your data sources and preferred tools and can run on AWS, Google Cloud Platform, and Microsoft Azure. Keep an eye on the health of your data and alert the team when quality criteria aren’t met. Set up in a few clicks the fundamental coverage of all your tables. Configure the frequency of runs, their criticality, and even customized notifications at the same time. Leverage ML-based rules to detect any anomaly in your data. No need for an initial configuration. A unique model for each rule learns from historical data and from user feedback. Complement the automated rules with a library of 50+ templates that can be applied to any asset.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Data quality platform for businesses wanting to measure, match, report and fix data assets, delivering continuous data quality

Audience

Teams and companies requiring a solution to monitor their data assets, metadata, and infrastructure

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 4.5 / 5
design 5.0 / 5
support 4.0 / 5

Pros & Cons from Real Users

Pros

  • AI-based anomaly detection works flawlessly Easy data lineage visualization Customizable metrics for business-specific monitoring Smooth cloud integration
  • To call out some of the top features, they would be:- ✅ The ability to connect to multiple data sources; giving you great observability of data no matter what platform you use. ✅ The UI is clean, simple and easy to use. Setting up a new data source is easy, even uploading dbt manifest files via their API is a simple few commands. ✅ Their documentation on getting things set up and working is very easy to read; it’s not bloated and tells you exactly what you need to do. ✅Their communication with us has been a great experience. They’ve fixed bugs we’ve raised to them, informed us of new updates, and overall been very receptive of feedback.

Cons

  • Mobile interface could be slightly improved Initial setup requires some familiarization for complex pipelines
  • Sifflet are still developing some features, polishing existing ones and ironing out minor bugs (more like quality of life features). So there’s nothing major that would be a deal breaker. If I had to call out some points that need development they would be:- 🤔 Their ‘Domain’ feature (ability to put data assets into domains, then limit users to a domain) is still in it’s basic form. It works, but needs some tweaks before it can be a real sellable feature. 🤔Exploring the lineage of a very large lineage graph can be difficult due to the number of relationships/dependencies a model may have. This may be more of an issue with your own DAG architecture than Sifflet, but it’s worth keeping in mind if your models are inherently complex and coupled to one another. Thankfully, Sifflet are working on a new UI for their lineage graph and have demo'd it with us, so this should be a lot smoother in the near future.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Datactics
Founded: 1999
Ireland
www.datactics.com

Company Information

Sifflet
United States
www.siffletdata.com

Alternatives

MatchX

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datuum.ai

Datuum
DataMatch

DataMatch

Data Ladder
dbt

dbt

dbt Labs

Categories

Categories

Integrations

Microsoft Power BI
Tableau
Airbyte
Amazon EMR
Amazon QuickSight
Amazon Redshift
Amazon S3
Apache Airflow
Apache Hive
Apache Spark
Census
Datadog
Firebolt
Fivetran
Microsoft Azure
Microsoft Teams
PostgreSQL
SQL Server
Slack
Stitch

Integrations

Microsoft Power BI
Tableau
Airbyte
Amazon EMR
Amazon QuickSight
Amazon Redshift
Amazon S3
Apache Airflow
Apache Hive
Apache Spark
Census
Datadog
Firebolt
Fivetran
Microsoft Azure
Microsoft Teams
PostgreSQL
SQL Server
Slack
Stitch
Claim Datactics and update features and information
Claim Datactics and update features and information
Claim Sifflet and update features and information
Claim Sifflet and update features and information