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Average Ratings 0 Ratings
Description
Information such as instrument configurations, the most recent service date, the analyst's identity, and the duration of the experiment is currently not recorded. This results in the loss of raw data, making it nearly impossible to alter or rerun analyses without significant effort, and the absence of traceability complicates meta-analyses. The process of simply entering primary analysis outcomes can become a burden that hinders scientists’ efficiency. However, by storing raw data in the cloud and automating the analytical processes, we ensure traceability throughout. Subsequently, this data can be integrated into various platforms such as ELNs, LIMS, Excel, analysis applications, and pipelines. Moreover, we continuously develop a data lake that accumulates all this information. This means that all your raw data, processed results, metadata, and even the internal data from connected applications are securely preserved forever within a unified cloud data lake. Analyses can be executed automatically, and metadata can be appended without manual input. Additionally, results can be seamlessly transmitted to any application or pipeline, and even back to the instruments for enhanced control, thereby streamlining the entire research process. This innovative approach not only increases efficiency but also significantly improves data management.
Description
Kylo serves as an open-source platform designed for effective management of enterprise-level data lakes, facilitating self-service data ingestion and preparation while also incorporating robust metadata management, governance, security, and best practices derived from Think Big's extensive experience with over 150 big data implementation projects. It allows users to perform self-service data ingestion complemented by features for data cleansing, validation, and automatic profiling. Users can manipulate data effortlessly using visual SQL and an interactive transformation interface that is easy to navigate. The platform enables users to search and explore both data and metadata, examine data lineage, and access profiling statistics. Additionally, it provides tools to monitor the health of data feeds and services within the data lake, allowing users to track service level agreements (SLAs) and address performance issues effectively. Users can also create batch or streaming pipeline templates using Apache NiFi and register them with Kylo, thereby empowering self-service capabilities. Despite organizations investing substantial engineering resources to transfer data into Hadoop, they often face challenges in maintaining governance and ensuring data quality, but Kylo significantly eases the data ingestion process by allowing data owners to take control through its intuitive guided user interface. This innovative approach not only enhances operational efficiency but also fosters a culture of data ownership within organizations.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon Web Services (AWS)
No
Apache Spark
No
BiG EVAL
No
Elasticsearch
No
Hadoop
No
HashiCorp Vault
No
Microsoft Excel
Yes
MySQL
No
OpenText Data Privacy & Protection Foundation
No
Talend Data Preparation
No
Integrations
Amazon Web Services (AWS)
Yes
Apache Spark
Yes
BiG EVAL
Yes
Elasticsearch
Yes
Hadoop
Yes
HashiCorp Vault
Yes
Microsoft Excel
No
MySQL
Yes
OpenText Data Privacy & Protection Foundation
Yes
Talend Data Preparation
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Ganymede
Country
United States
Website
www.ganymede.bio/
Vendor Details
Company Name
Teradata
Founded
1979
Country
United States
Website
kylo.io
Product Features
Medical Lab
Audit Trail
No
Data Analysis Auditing
No
Data Security
No
EMR Interface
No
Fax Management
No
Lab Instrument Interface
No
Multi-Location Printing
No
Online Instrumentation
No
Physician Test Panels
No
Procedure-Based Billing
No
Sample Tracking
No
Product Features
Data Governance
Access Control
No
Data Discovery
No
Data Mapping
No
Data Profiling
No
Deletion Management
No
Email Management
No
Policy Management
No
Process Management
No
Roles Management
No
Storage Management
No
Data Lineage
Database Change Impact Analysis
No
Filter Lineage Links
No
Implicit Connection Discovery
No
Lineage Object Filtering
No
Object Lineage Tracing
No
Point-in-Time Visibility
No
User/Client/Target Connection Visibility
No
Visual & Text Lineage View
No
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No