Average Ratings 2 Ratings
Average Ratings 0 Ratings
Description
Rapidminer Monarch is a Siemens self-service data preparation platform that enables business users and data teams to extract, clean, transform, and export data without coding. It is built to work with a wide range of sources, including complex PDFs, Excel files, spreadsheets, text reports, databases, and other enterprise systems. The software helps organizations convert unstructured or difficult-to-use information into structured data that can support reporting, analytics, machine learning, and business operations. Rapidminer Monarch is especially useful for teams that regularly reconcile reports, audit data, migrate legacy information, or prepare data from non-tabular files. Its no-code environment allows users to build repeatable workflows through drag-and-drop tools, reducing dependence on manual cleanup and IT support. The platform increases trust by maintaining data lineage, reconciliation configuration, and change histories for every transformation. Users can also access thousands of pre-built apps for systems such as ADP, Dayforce, Fiserv, Visa, Meditech, and SAP. Rapidminer Monarch Server helps centralize, govern, and operationalize data preparation workflows for enterprise-scale deployments. By automating repetitive preparation tasks, Rapidminer Monarch helps teams improve accuracy, speed up analytics, and make better use of data from across the business.
Description
Sliq is an innovative platform powered by artificial intelligence that swiftly cleans up disorganized raw datasets, making them ready for analysis within minutes by automatically identifying and resolving prevalent quality concerns such as format discrepancies, absent values, schema variations, and formatting mistakes. This efficiency allows analysts and engineers to minimize time spent on tedious maintenance tasks and focus more on deriving insights and building models. By utilizing context-sensitive intelligence, Sliq comprehends the semantic context of the uploaded datasets—whether they pertain to finance, e-commerce, or healthcare—and devises a customized cleaning strategy tailored specifically for each dataset instead of relying on generic solutions. Users have the flexibility to either upload files directly or connect programmatically with existing workflows, and Sliq is compatible with popular data formats like CSV, JSON, and Parquet, ensuring smooth integration into current data environments. Additionally, this platform enhances productivity by streamlining the data preparation process, allowing teams to drive more impactful decision-making through improved data quality.
API Access
Has API
API Access
Has API
Integrations
Apache Parquet
Google Sheets
JSON
Microsoft Excel
Polaris
Rapidminer
Rapidminer Knowledge Studio
Rapidminer Panopticon
Rapidminer SLC
Vertica
Integrations
Apache Parquet
Google Sheets
JSON
Microsoft Excel
Polaris
Rapidminer
Rapidminer Knowledge Studio
Rapidminer Panopticon
Rapidminer SLC
Vertica
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$30
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Siemens
Founded
1847
Country
Germany
Website
www.siemens.com/en-us/products/rapidminer/monarch/
Vendor Details
Company Name
Sliq
Country
United States
Website
sliqdata.com
Product Features
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
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
Product Features
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation