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What is Raynet One Data Hub?
Are your IT initiatives hindered by business shortcomings resulting from inadequate or erroneous data?
Organizations often struggle to consolidate their IT asset information and extract meaningful insights from it. While data collection is feasible, the challenge lies in normalizing and enriching that data effectively. In fact, research indicates that 90% of the time, organizations can gather data but fail to convert it into clear visibility or actionable insights through effective aggregation and normalization.
With the Raynet Unified Data Platform, you gain uninterrupted access to high-quality, validated, and trustworthy data that supports informed decision-making in IT asset management. This data platform equips you with the essential insights needed to oversee and optimize your IT landscape efficiently. By using such a platform, businesses can significantly improve their operational capabilities and enhance overall performance.
What is Ascend?
Ascend delivers a highly efficient and automated platform tailored for data teams, streamlining the processes of ingesting, transforming, and orchestrating their entire data engineering and analytics operations, achieving speeds that can be up to ten times quicker than before. By removing the bottlenecks faced by teams, Ascend empowers them to surmount obstacles and proficiently construct, manage, and optimize the increasingly complex data workloads they encounter. With the aid of DataAware intelligence, Ascend works tirelessly in the background to maintain data integrity while enhancing workloads, potentially reducing maintenance time by up to 90%. Users can easily design, fine-tune, and implement data transformations via Ascend’s adaptable flex-code interface, which allows for interchangeable use of SQL, Python, Java, and Scala. Furthermore, vital insights—including data lineage, profiles, job and user logs, system health, and key workload metrics—are readily available to users in a single, user-friendly dashboard. Ascend also features seamless connectivity to a growing selection of widely-used data sources through its Flex-Code data connectors, ensuring smoother integration experiences. This all-encompassing strategy not only enhances how teams utilize their data but also cultivates a dynamic and innovative culture within their analytics methodologies. Ultimately, Ascend positions teams to respond more adeptly to the evolving demands of their data-centric environments.
Integrations Supported
SQL Server
Amazon Redshift
Amazon S3
Apache Airflow
Apache Kafka
Azure Event Hubs
Databricks Data Intelligence Platform
Delta Lake
Google Ads
Google Cloud BigQuery
Integrations Supported
SQL Server
Amazon Redshift
Amazon S3
Apache Airflow
Apache Kafka
Azure Event Hubs
Databricks Data Intelligence Platform
Delta Lake
Google Ads
Google Cloud BigQuery
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$0.98 per DFC
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
Raynet
Date Founded
1999
Company Location
Germany
Company Website
raynet.de/raynet-one-data-hub/
Company Facts
Organization Name
Ascend
Company Location
United States
Company Website
www.ascend.io
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
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
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
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control