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SCIKIQSCIKIQ is one of the most innovative AI-native Data & Intelligence platforms for enterprises, built to make enterprise data AI-ready in weeks, not years. Recognized by Forrester among leading AI-augmented data platforms, NASSCOM League of 10, YourStory Tech30, Inc42 and DataIQ, SCIKIQ is trusted by leading global enterprises across the USA, India, UK and UAE. SCIKIQ brings Data Integration, Data Quality, Data Governance, Metadata Management, Data Lineage, Semantic Intelligence, Knowledge Graphs, Conversational Analytics, Generative AI, Data Products and AI Agents together in one unified platform. Unlike traditional data platforms that require enterprises to move or rebuild their technology stack, SCIKIQ works with what you already have. Connect SAP, Salesforce, Oracle, Snowflake, Databricks, AWS, Azure, GCP, data lakes, warehouses and enterprise applications through 200+ pre-built connectors, with no rip-and-replace. What makes SCIKIQ different is Contextual Intelligence. SCIKIQ doesn't just connect data; it helps AI understand its business meaning. Its semantic layer combines business terms, KPI definitions, metadata, lineage, ownership, rules, ontologies and relationships to create a trusted foundation for enterprise AI. Business users can talk to their data in natural language, investigate KPIs, discover root causes and generate insights without SQL. Data teams gain enterprise-grade governance, quality, lineage and control. AI teams get trusted, contextual data for building GenAI applications and intelligent AI agents. Why enterprises choose SCIKIQ AI-ready in 3–6 weeks | 167+ connectors | 99.9% availability | Multi-cloud | No-code | No vendor lock-in | No replatforming Proven production deployments across Manufacturing retail, airlines, logistics, BFSI, Healthcare and others
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Teradata VantageCloudTeradata VantageCloud: The Complete Cloud Analytics and AI Platform VantageCloud is Teradata’s all-in-one cloud analytics and data platform built to help businesses harness the full power of their data. With a scalable design, it unifies data from multiple sources, simplifies complex analytics, and makes deploying AI models straightforward. VantageCloud supports multi-cloud and hybrid environments, giving organizations the freedom to manage data across AWS, Azure, Google Cloud, or on-premises — without vendor lock-in. Its open architecture integrates seamlessly with modern data tools, ensuring compatibility and flexibility as business needs evolve. By delivering trusted AI, harmonized data, and enterprise-grade performance, VantageCloud helps companies uncover new insights, reduce complexity, and drive innovation at scale.
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AnalyticsCreatorAnalyticsCreator helps Microsoft data teams turn governed design into deployable data solutions without introducing a proprietary runtime layer. Teams use AnalyticsCreator to define warehouse structures, transformation logic, historisation rules, relationships and dependencies in a central model. From that model, the application can generate native implementation assets for technologies such as SQL Server, SSIS, Azure Data Factory, Microsoft Fabric and Power BI. The approach is designed for organisations that want to standardise how data warehouses and data products are engineered while keeping full control of the resulting code and project artefacts. Generated outputs can be integrated into existing Git, Azure DevOps and CI/CD workflows for versioning, review and controlled deployment across environments. AnalyticsCreator supports dimensional, 3NF and hybrid modelling as well as common engineering patterns including delta loading, Slowly Changing Dimensions, snapshots and historisation. Documentation, lineage and dependency information are maintained alongside the project design, making it easier to assess the impact of proposed changes and keep implementation aligned with the underlying model. The AnalyticsCreator Governed Control Model provides the foundation for this process by keeping business meaning, technical structures and implementation logic connected. Design Intelligence builds on that context by making governed project metadata, lineage, dependencies and design rules available to authorised AI tools and agents. Typical use cases include modernising SQL Server and SSIS estates, building Microsoft Fabric solutions, standardising Power BI delivery and creating repeatable data warehouse and data product engineering processes.
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DataHubDataHub stands out as a dynamic open-source metadata platform designed to improve data discovery, observability, and governance across diverse data landscapes. It allows organizations to quickly locate dependable data while delivering tailored experiences for users, all while maintaining seamless operations through accurate lineage tracking at both cross-platform and column-specific levels. By presenting a comprehensive perspective of business, operational, and technical contexts, DataHub builds confidence in your data repository. The platform includes automated assessments of data quality and employs AI-driven anomaly detection to notify teams about potential issues, thereby streamlining incident management. With extensive lineage details, documentation, and ownership information, DataHub facilitates efficient problem resolution. Moreover, it enhances governance processes by classifying dynamic assets, which significantly minimizes manual workload thanks to GenAI documentation, AI-based classification, and intelligent propagation methods. DataHub's adaptable architecture supports over 70 native integrations, positioning it as a powerful solution for organizations aiming to refine their data ecosystems. Ultimately, its multifaceted capabilities make it an indispensable resource for any organization aspiring to elevate their data management practices while fostering greater collaboration among teams.
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DataBuckEnsuring the integrity of Big Data Quality is crucial for maintaining data that is secure, precise, and comprehensive. As data transitions across various IT infrastructures or is housed within Data Lakes, it faces significant challenges in reliability. The primary Big Data issues include: (i) Unidentified inaccuracies in the incoming data, (ii) the desynchronization of multiple data sources over time, (iii) unanticipated structural changes to data in downstream operations, and (iv) the complications arising from diverse IT platforms like Hadoop, Data Warehouses, and Cloud systems. When data shifts between these systems, such as moving from a Data Warehouse to a Hadoop ecosystem, NoSQL database, or Cloud services, it can encounter unforeseen problems. Additionally, data may fluctuate unexpectedly due to ineffective processes, haphazard data governance, poor storage solutions, and a lack of oversight regarding certain data sources, particularly those from external vendors. To address these challenges, DataBuck serves as an autonomous, self-learning validation and data matching tool specifically designed for Big Data Quality. By utilizing advanced algorithms, DataBuck enhances the verification process, ensuring a higher level of data trustworthiness and reliability throughout its lifecycle.
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Google Cloud PlatformGoogle Cloud serves as an online platform where users can develop anything from basic websites to intricate business applications, catering to organizations of all sizes. New users are welcomed with a generous offer of $300 in credits, enabling them to experiment, deploy, and manage their workloads effectively, while also gaining access to over 25 products at no cost. Leveraging Google's foundational data analytics and machine learning capabilities, this service is accessible to all types of enterprises and emphasizes security and comprehensive features. By harnessing big data, businesses can enhance their products and accelerate their decision-making processes. The platform supports a seamless transition from initial prototypes to fully operational products, even scaling to accommodate global demands without concerns about reliability, capacity, or performance issues. With virtual machines that boast a strong performance-to-cost ratio and a fully-managed application development environment, users can also take advantage of high-performance, scalable, and resilient storage and database solutions. Furthermore, Google's private fiber network provides cutting-edge software-defined networking options, along with fully managed data warehousing, data exploration tools, and support for Hadoop/Spark as well as messaging services, making it an all-encompassing solution for modern digital needs.
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JscramblerJscrambler is the leader in Client-Side Security, protecting the code, data, and digital interactions that power modern web applications. As organizations increasingly adopt AI-generated code, third-party software components, and AI-powered agents, more critical application logic and sensitive data are exposed within the browser. Jscrambler provides the security and governance layer for this environment, giving enterprises visibility and control over what happens at runtime. The Jscrambler Client-Side Security Platform is powered by a Behavioral Enforcement Core that continuously monitors and enforces how application code, including AI-generated code, third-party scripts, AI agents, and sensitive data behave in the browser. By enforcing software integrity and data governance at runtime, Jscrambler helps organizations prevent client-side attacks, protect sensitive data, and maintain control over digital experiences. Trusted by organizations across financial services, retail, travel, healthcare, and other industries, Jscrambler helps enterprises address client-side security and compliance requirements including PCI DSS, GDPR, HIPAA, CIPA, CCPA, and the EU AI Act.
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FerootFeroot Security is a global authority in AI-driven website and web application compliance, security, and digital risk management. Feroot AI helps organizations gain continuous visibility into how data moves across their websites and applications, protecting users from hidden threats while enforcing compliance with PCI DSS 4.0.1, HIPAA rules governing online tracking technologies, CCPA/CPRA, GDPR, CIPA, and more than 50 international laws. The Feroot AI Platform transforms compliance and security from a manual, reactive process into an automated, always-on control layer. Tasks that traditionally require months of coordination between engineering, legal, privacy, and security teams can be activated in minutes, producing real-time protection and audit-ready evidence without disrupting development workflows. Feroot consolidates essential capabilities into a single unified platform, including advanced JavaScript behavior analysis, continuous website compliance scanning, third-party script oversight, consent and preference enforcement, and data privacy posture management. The platform is purpose-built to detect, prevent, and eliminate modern web threats such as Magecart, formjacking, e-skimming, and unauthorized data collection, especially on sensitive surfaces like checkout pages, authentication flows, embedded iframes, and healthcare portals. By monitoring runtime behavior rather than static code alone, Feroot ensures that every script and data interaction aligns with regulatory and security requirements at all times. Trusted by Fortune 500 enterprises, healthcare organizations, retailers, SaaS providers, payment service providers, utilities, universities, and public sector institutions, Feroot safeguards hundreds of millions of users across web and mobile environments worldwide. Feroot AI solutions include PaymentGuard AI, HealthData Shield AI, AlphaPrivacy AI, CodeGuard AI, and MobileGuard AI. Visit feroot for more information.
What is MANTA?
Manta functions as a comprehensive data lineage platform, acting as the central repository for all data movements within an organization. It is capable of generating lineage from various sources including report definitions, bespoke SQL scripts, and ETL processes. The analysis of lineage is based on real code, allowing for the visualization of both direct and indirect data flows on a graphical interface. Users can easily see the connections between files, report fields, database tables, and specific columns, which helps teams grasp data flows in a meaningful context. This clarity promotes better decision-making and enhances overall data governance within the enterprise.
What is Axon Data Governance?
Empowering your teams to make well-informed decisions hinges on the availability of dependable and consistent data. You can achieve this by implementing a comprehensive, automated, and intelligent data governance framework that functions at scale. Axon Data Governance acts as a collaborative hub and data marketplace, which is vital for executing effective and scalable data governance strategies. Additionally, it simplifies the task of identifying stakeholders while promoting knowledge sharing across different communities, enabling teams to benefit from each other's insights. By creating an organized data marketplace, you ensure that teams can quickly find, access, and understand the data needed for generating analytical insights. Leveraging governed data can drive key initiatives, such as improving customer experiences, while also guaranteeing that your organization produces reliable and consistent outcomes. It is crucial to incorporate data governance and privacy considerations into your projects and processes from the beginning to comply with regulations like GDPR and CCPA. Moreover, developing a unified data dictionary will help sustain a consistent source of business context across multiple tools and platforms, thereby strengthening data governance. This approach not only aids in meeting compliance requirements but also promotes a culture of data-driven success throughout your organization. Ultimately, fostering collaboration and ensuring access to quality data can significantly elevate your strategic initiatives.
Integrations Supported
ACS
ALIP
Agile CRM
AspDotNetStorefront
Ataccama ONE
Collibra
Dataedo
Decimal
Epos
Eviden MDR Service
Integrations Supported
ACS
ALIP
Agile CRM
AspDotNetStorefront
Ataccama ONE
Collibra
Dataedo
Decimal
Epos
Eviden MDR Service
API Availability
Has API
API Availability
Has API
Pricing Information
Every customer gets a package tailored to their needs. The final prices are based on the selected features and the number of scripts in the package.
Sample Packages:
Data Governance
DataOps
Cloud Migrations
Sample Packages:
Data Governance
DataOps
Cloud Migrations
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
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
Manta
Date Founded
2016
Company Location
New York
Company Website
manta.io
Company Facts
Organization Name
Informatica
Date Founded
1993
Company Location
United States
Company Website
www.informatica.com/products/data-quality/axon-data-governance.html
Categories and Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Lineage
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
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 Privacy Management
Access Control
CCPA Compliance
Consent Management
Data Mapping
GDPR Compliance
Incident Management
PIA / DPIA
Policy Management
Risk Management
Sensitive Data Identification
Categories and Features
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Lineage
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View