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What is ZinkML?

ZinkML serves as an open-source platform for data science that eliminates the need for coding, enabling organizations to utilize their data more effectively. Its user-friendly and visual interface is tailored to ensure that individuals without extensive programming knowledge can engage with data science, thus broadening accessibility. The platform simplifies the entire data science workflow, covering everything from data ingestion to model building, deployment, and monitoring. Users can easily create intricate pipelines by dragging and dropping components, visualize their data, or develop predictive models—all without any coding skills. With features like automated model selection, feature engineering, and hyperparameter optimization, ZinkML significantly speeds up the model development process. Furthermore, ZinkML fosters collaborative efforts by providing tools that enable teams to work together seamlessly on their data science initiatives. By making data science more accessible, ZinkML empowers organizations to derive greater value from their data and enhance their decision-making capabilities, ultimately leading to improved business outcomes. This shift towards democratized data science is crucial in a world where data-driven decisions are becoming increasingly vital.

What is SAP Agile Data Preparation?

Elevate your analytics, data migration, and master data management (MDM) initiatives with the SAP Agile Data Preparation tool. This innovative application empowers users to transform their data into valuable insights, enhancing their ability to navigate and comprehend various data shapes, ultimately boosting productivity and agility to previously unattainable levels. The Cloud Service's Usage Metric is determined by the number of Users, who are characterized as individuals engaged in preparing, managing, and supervising data sets or executing data stewardship responsibilities within the service. To access this tool, customers are required to purchase an annual foundation subscription, which is available in increments of 64 GB of memory per year, allowing for a maximum annual capacity of 512 GB. This systematic approach not only facilitates the effective scaling of organizational data requirements but also ensures that high performance and efficiency are consistently achieved. As organizations increasingly rely on data-driven decision-making, the SAP Agile Data Preparation tool becomes an indispensable asset in their strategic toolkit.

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Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure

Integrations Supported

APSentra
Acterys
Data Secure
GrowMAX BI
Neptune DXP
SAP Joule
Splunk User Behavior Analytics
Uptempo
Weagree
iGEO ERP

API Availability

API Availability

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

Not specified

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

ZinkML Technologies

Date Founded

2023

Company Location

India

Company Website

zinkml.com

Company Facts

Organization Name

SAP

Date Founded

1972

Company Location

Germany

Company Website

assets.cdn.sap.com/agreements/product-use-and-support-terms/cls/en/sap-agile-data-preparation-supplement-english-v2-2016.pdf

Categories and Features

Data Analysis

Not specified

Data Classification

Not specified

Data Cleansing

Not specified

Data Collaboration

Not specified

Data Mapping

Not specified

Data Modeling

Not specified

Data Science

Not specified

Data Visualization

Not specified

Categories and Features

Data Cleansing

Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation

Data Preparation

Not specified

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