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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

In the current landscape, forward-thinking companies are utilizing data to outperform competitors, enhance customer satisfaction, and identify new avenues for growth. However, they also face the complexities posed by industry regulations and strict data privacy laws that put pressure on conventional technologies and workflows. The importance of data quality cannot be overstated, yet it frequently falters before reaching business intelligence and analytics tools. Wiiisdom Ops is designed to help organizations maintain quality assurance within the analytics phase, which is crucial for the final leg of the data journey. Neglecting this aspect could expose your organization to significant risks, leading to poor choices and potential automated failures. Achieving large-scale BI testing is unfeasible without the aid of automation. Wiiisdom Ops seamlessly integrates into your CI/CD pipeline, providing a comprehensive analytics testing loop while reducing expenses. Notably, it does not necessitate engineering expertise for implementation. You can centralize and automate your testing procedures through an intuitive user interface, making it easy to share results across teams, which enhances collaboration and transparency.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Microsoft Excel
PostgreSQL
Snowflake
Amazon S3
Apache Tomcat
Collibra
Dropbox
Google Chrome
Hadoop
Informatica Data Quality
Mozilla Firefox
MySQL
Oracle Cloud Infrastructure
Red Hat OpenShift Streams
SAP Data Services
SQL Server
Tableau
Teradata VantageCloud
WhereScape
X (Twitter)

Integrations

Microsoft Excel
PostgreSQL
Snowflake
Amazon S3
Apache Tomcat
Collibra
Dropbox
Google Chrome
Hadoop
Informatica Data Quality
Mozilla Firefox
MySQL
Oracle Cloud Infrastructure
Red Hat OpenShift Streams
SAP Data Services
SQL Server
Tableau
Teradata VantageCloud
WhereScape
X (Twitter)

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
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

Wiiisdom

Country

United States

Website

wiiisdom.com/wiiisdom-ops/overview/

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

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

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