Announcing Datrics v.1.2.6 Release: Governance, models reusability, outliers detection.
Announcing Datrics v.1.2.6 Release: Governance, models reusability, outliers detection.
No-code tool for analytics and machine learning
We reduce the time needed to create and deploy a model by at least 50% by introducing automation and templates
Does it feel familiar?
Almost every modern business process is more efficient with data analytics or machine learning
90% of the machine learning experiments fail to get to production
It takes months of work to take it from idea to experiment to production
Not only machine learning development is time-consuming and ineffective but regular spreadsheet analytics as well
Experts spend at least 1 of 3 hours manually process analytics and reports
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What you get
50% faster time to market for a report, use case or model deployment
3 times more models created by business analysts, domain experts and citizen data scientists
70% time economy via automation compared to manual spreadsheet work
Save 400h or $12,000+ per year per advanced data specialist using datrics!
3 times more models created by business analysts, domain experts and citizen data scientists
70% time economy via automation compared to manual spreadsheet work
Save 400h or $12,000+ per year per advanced data specialist using datrics!
Up in NO time
2 hours platform roll out time
5 working days for a first report or model as a part of usual business process
Built-in scheduler and analytics automation
5 working days for a first report or model as a part of usual business process
Built-in scheduler and analytics automation
On-Premise solution
Cloud-based solution
Datrics platform can be deployed on premises to ensure data security without any transition or exporting.
Datrics can also perform on the cloud and provide scalable opportunities for businesses.
Deployment options
WITHOUT DATRICS
10
6
people in the team: 2 data engineers, 1 BA, 2 data scientists, 1 DevOps engineer
weeks time to market
1-3
weeks time to market
WITH DATRICS
3
people in the team: 1 data engineer, 1 BA, 1 data scientist
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