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What is Datumize Zentral?

To successfully adapt to changing environments, organizations need to demonstrate flexibility and agility in their data strategies while also upholding strong data governance standards. Datumize Zentral (DZ) acts as a holistic self-service management platform that facilitates the creation, configuration, testing, deployment, and oversight of data pipelines, agents, and third-party integrations. Its user-friendly interface and API are designed to meet the diverse needs of both clients and partners. Additionally, DZ offers versatile hosting options, enabling deployment on Datumize Cloud, various other cloud services, or even on-premises servers. This adaptability allows businesses to customize their data solutions to align with their unique operational demands, ultimately enhancing their overall efficiency and effectiveness. Moreover, the platform’s comprehensive features empower organizations to optimize their data management processes seamlessly.

What is Data Lakes on AWS?

A multitude of Amazon Web Services (AWS) users are in search of a data storage and analytics option that outperforms traditional data management systems in terms of flexibility and agility. The emergence of data lakes has proven to be a groundbreaking and increasingly popular approach for data storage and analysis, allowing businesses to manage a wide array of data types from multiple sources within a single repository that supports both structured and unstructured data. AWS Cloud offers vital elements that empower customers to develop a secure, versatile, and cost-effective data lake. These elements include AWS managed services that facilitate the ingestion, storage, discovery, processing, and analysis of diverse data formats. To support clients in building their data lakes, AWS presents a thorough data lake solution that acts as an automated reference implementation, laying out a highly available and economical data lake architecture on the AWS Cloud, complemented by a user-friendly console for searching and accessing datasets. Additionally, this solution not only improves the accessibility of data but also simplifies the entire data management process, ultimately leading to enhanced operational efficiency for organizations. As a result, companies can leverage these advantages to make more informed decisions based on their data insights.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

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
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Datumize

Date Founded

2014

Company Location

Spain

Company Website

www.datumize.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/solutions/implementations/data-lake-solution/

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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