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Description
Every CXO wants one view of the enterprise: costs, revenue, and growth, in one place, in real time.
SCIKIQ powers that enterprise 360, in detail, on governed data.
SCIKIQ is an enterprise data fabric platform that unifies data integration, data quality, data governance, and master data management and makes data AI-ready through a semantic layer built on ontologies and knowledge graphs.
Instead of moving data into yet another warehouse, SCIKIQ connects to systems where they are and applies governance, lineage, and business context on top.
No migration. No rip-and-replace.
What's inside:
167+ pre-built connectors — SAP, Snowflake, Oracle, Kafka, and more
Data catalog with automated data lineage and active metadata
No-code ETL, orchestration, and data quality management
Semantic layer with ontologies and knowledge graphs for AI-ready business context
Agentic AI and conversational analytics — business users query governed data in plain language
Data Product Factory and internal data marketplace — package governed datasets into reusable data products
Data observability — catch schema changes, quality drift, and pipeline failures before they hit reports
Security and compliance: role-based access, column- and row-level security, audit trails, and policy automation for GDPR, India's DPDP Act, and regulated industries like banking and healthcare.
Deploys cloud-agnostic — AWS, Azure, GCP, or on-premises, and works alongside existing investments in Power BI, Tableau, and dbt rather than replacing them. API access included.
Live in 30–90 days.
Recognized by Forrester as a Top 34 AI Platform globally. NASSCOM League of 10.
Trusted by enterprises in banking, financial services, retail, manufacturing, and supply chain.
Description
iceDQ, a DataOps platform that allows monitoring and testing, is a DataOps platform. iceDQ is an agile rules engine that automates ETL Testing, Data Migration Testing and Big Data Testing. It increases productivity and reduces project timelines for testing data warehouses and ETL projects. Identify data problems in your Data Warehouse, Big Data, and Data Migration Projects. The iceDQ platform can transform your ETL or Data Warehouse Testing landscape. It automates it from end to end, allowing the user to focus on analyzing the issues and fixing them. The first edition of iceDQ was designed to validate and test any volume of data with our in-memory engine. It can perform complex validation using SQL and Groovy. It is optimized for Data Warehouse Testing. It scales based upon the number of cores on a server and is 5X faster that the standard edition.
API Access
Has API
API Access
Has API
Integrations
Amazon S3
Apache Kafka
Cloudera
Dropbox
Hadoop
IBM Db2
Jenkins
Microsoft Excel
MySQL
Oracle Cloud Infrastructure
Integrations
Amazon S3
Apache Kafka
Cloudera
Dropbox
Hadoop
IBM Db2
Jenkins
Microsoft Excel
MySQL
Oracle Cloud Infrastructure
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$1000
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
SCIKIQ
Founded
2023
Country
India
Website
scikiq.com
Vendor Details
Company Name
iceDQ
Founded
2005
Country
United States
Website
icedq.com
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics
Catalog Management
Catalog Creation
Content Library
Content Management
Cross Selling Functionality
Custom Product Attributes
Customizable Catalogs
Desktop Publishing
Pricing Management
Product Comparison
Search
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
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 Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
PIM
Content Syndication
Data Modeling
Data Quality Control
Digital Asset Management
Documentation Management
Master Record Management
Version Control
Product Features
Automated Testing
Hierarchical View
Move & Copy
Parameterized Testing
Requirements-Based Testing
Security Testing
Supports Parallel Execution
Test Script Reviews
Unicode Compliance
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
