Name: Datrics
Author: Datrics

Help Desk

Web and Video Conferencing

Customer Support

Beta Testing

Continuous Integration

Development

Alumni Management

Education

Business Intelligence (BI)

Collaboration

Contract Analysis

Demand Planning

Emissions Management

Knowledge Management

Online Notary

Payment Facilitation

Enterprise

Accounting

Travel Management

Finance and Accounting

Applicant Tracking

Corporate Learning Management

HR Management

HR Service Delivery

Payroll

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

AIOps

API Design

App Development

Cloud Storage

Data Center Backup

Data Center Networking

Data Center Outsourcing (Canada)

Data Integration

Data Replication

Database-as-a-Service (DBaaS)

Enterprise Printing

Fraud Detection

Integration Platform as a Service (iPaaS)

Managed Detection and Response (MDR)

Mobile Data Security

Network Performance Monitoring

Secure Access Control

Service Virtualization

Value Stream Management

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Content Management

Content Marketing

Creative Management

Ecommerce Personalization

Email Marketing

Market Research

Marketing Automation

Marketing Resource Management

Social Media Analytics

Social Media Management

Survey & Forms Building

Web Analytics

Marketing

Project Management

Professional Services

Customer Onboarding

Customer Relationship Management (CRM)

Point of Sale

Predictive Sales Analytics

Sales Consulting

Sales Dialer

Sales Incentive Compensation Management

Sales Training

Sales

Virtualization Security

Security

Financial Services CRM

Hospital Management

Medical Office EMR & EHR

Revenue Cycle Management (RCM)

Shipping

eDiscovery

Vertical-Specific

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Datrics is a no-code platform designed to facilitate analytics and data science processes. According to the vendor, it caters to small to large companies across various professions and industries, including data analysts, business analysts, data scientists, financial services, e-commerce and retail, and blockchain analytics. With its user-friendly interface and advanced capabilities, Datrics aims to empower businesses to leverage data and make informed decisions effortlessly.

## Key Features

**Connect to data sources**: According to the vendor, Datrics allows users to easily integrate different data sources into their analytics pipeline, enabling access and analysis of data from multiple points.

**Prepare your data easily**: The vendor claims that Datrics simplifies and automates the data preparation process through a highly visual and repeatable drag-and-drop interface. Users can build data pipelines that can be reused for future experiments.

**Explore your data**: Datrics offers advanced exploratory data analysis functionality, allowing users to dive deeper into their data. According to the vendor, users can perform feature selection and engineering for machine learning tasks.

**Get predictions in minutes**: The vendor states that Datrics provides AutoML models that require no setup, enabling users to obtain instant predictions for data science tasks. Users can customize advanced settings or add custom models for more powerful machine learning capabilities.

**Visualize or use in production**: Datrics allows users to create on-demand or scheduled dashboards to visualize and evaluate results. Additionally, the vendor claims that successful machine learning models can be deployed to production with a single click, seamlessly integrating data science and engineering.

**Accelerate Your Financial Services with Intelligent AI-Powered Growth Solutions**: According to the vendor, Datrics empowers fintech companies to overcome challenges, drive success, and maximize business potential. The vendor claims that it enables faster market solutions, ML model deployment in minutes, and ensures 100% privacy compliance.

**Empowering Fintech Companies to Overcome Challenges, Drive Success, and Maximize Business Potential**: The vendor states that Datrics provides AI-powered growth solutions for fintech companies. It aims to help overcome complexities in data collection and preparation, integrate AI seamlessly with existing systems and infrastructure, ensure data privacy and protection, mitigate bias, and adapt AI strategies to changing market dynamics.

**Make better business decisions and elevate your risk management**: Datrics offers advanced algorithms to uncover hidden patterns in data, enabling more precise credit risk models and personalized credit score assessments. According to the vendor, users can predict loan defaults, optimize daily routines, maintain compliance with regulations, and discover business opportunities faster.

**Automate social media data collection and visualization to make data-driven decisions**: Datrics allows users to customize analytics across multiple social media platforms, track relevant key performance indicators (KPIs) for their business, and automate data collection and visualization processes.

**Zedosh's Attention Exchange® Engine Powered By Datrics For Purpose-Driven Advertising**: The vendor claims that this feature aims to change the landscape of online advertising for a post-cookie internet. It enables targeting ads using a sophisticated ML-powered framework.

Qlik Sense® is a self-service BI platform for data discovery and visualization. It supports a full range of analytics use cases—data governance, pixel-perfect reporting, and collaboration. Its Associative Engine indexes and connects relationships between data points for creating actionable insights.

Qlik Sense Enterprise on Windows

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Qlik Sense

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Business Tier

Enterprise Tier

Free Tier

Anaconda

Datrics

Machine learning tools are algorithmic applications of artificial intelligence that give systems the ability to learn and improve without ample human input; similar concepts are data mining and predictive modeling. They allow software to become more accurate in predicting outcomes without being explicitly programmed. The idea is that a model or algorithm is used to get data from the world, and that data is fed back into the model so that it improves over time. It’s called machine learning because the model “learns” as it is fed more and more data.

Machine Learning

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