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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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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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OORT DataHubOur innovative decentralized platform enhances the process of AI data collection and labeling by utilizing a vast network of global contributors. By merging the capabilities of crowdsourcing with the security of blockchain technology, we provide high-quality datasets that are easily traceable. Key Features of the Platform: Global Contributor Access: Leverage a diverse pool of contributors for extensive data collection. Blockchain Integrity: Each input is meticulously monitored and confirmed on the blockchain. Commitment to Excellence: Professional validation guarantees top-notch data quality. Advantages of Using Our Platform: Accelerated data collection processes. Thorough provenance tracking for all datasets. Datasets that are validated and ready for immediate AI applications. Economically efficient operations on a global scale. Adaptable network of contributors to meet varied needs. Operational Process: Identify Your Requirements: Outline the specifics of your data collection project. Engagement of Contributors: Global contributors are alerted and begin the data gathering process. Quality Assurance: A human verification layer is implemented to authenticate all contributions. Sample Assessment: Review a sample of the dataset for your approval. Final Submission: Once approved, the complete dataset is delivered to you, ensuring it meets your expectations. This thorough approach guarantees that you receive the highest quality data tailored to your needs.
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Semarchy xDMExplore Semarchy’s adaptable unified data platform to enhance decision-making across your entire organization. Using xDM, you can uncover, regulate, enrich, clarify, and oversee your data effectively. Quickly produce data-driven applications through automated master data management and convert raw data into valuable insights with xDM. The user-friendly interfaces facilitate the swift development and implementation of applications that are rich in data. Automation enables the rapid creation of applications tailored to your unique needs, while the agile platform allows for the quick expansion or adaptation of data applications as requirements change. This flexibility ensures that your organization can stay ahead in a rapidly evolving business landscape.
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Google Cloud BigQueryBigQuery serves as a serverless, multicloud data warehouse that simplifies the handling of diverse data types, allowing businesses to quickly extract significant insights. As an integral part of Google’s data cloud, it facilitates seamless data integration, cost-effective and secure scaling of analytics capabilities, and features built-in business intelligence for disseminating comprehensive data insights. With an easy-to-use SQL interface, it also supports the training and deployment of machine learning models, promoting data-driven decision-making throughout organizations. Its strong performance capabilities ensure that enterprises can manage escalating data volumes with ease, adapting to the demands of expanding businesses. Furthermore, Gemini within BigQuery introduces AI-driven tools that bolster collaboration and enhance productivity, offering features like code recommendations, visual data preparation, and smart suggestions designed to boost efficiency and reduce expenses. The platform provides a unified environment that includes SQL, a notebook, and a natural language-based canvas interface, making it accessible to data professionals across various skill sets. This integrated workspace not only streamlines the entire analytics process but also empowers teams to accelerate their workflows and improve overall effectiveness. Consequently, organizations can leverage these advanced tools to stay competitive in an ever-evolving data landscape.
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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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PropelPropel helps product companies accelerate innovation by unifying lifecycle management, quality processes, and product information in a single platform. With centralized data and built-in governance, every team—engineering, quality, operations, and commercial—can work from the same source of truth. The result is stronger collaboration, faster decisions, and a more reliable path from concept to customer.
What is BiG EVAL?
The BiG EVAL solution platform provides powerful software tools that are crucial for maintaining and improving data quality throughout every stage of the information lifecycle. Constructed on a solid code framework, BiG EVAL's software for data quality management and testing ensures high efficiency and adaptability for thorough data validation. The functionalities of this platform are the result of real-world insights gathered through partnerships with clients. Upholding superior data quality across the entirety of your information's lifecycle is essential for effective data governance, which significantly influences the business value extracted from that data. To support this objective, the automation tool BiG EVAL DQM plays a vital role in managing all facets of data quality. Ongoing quality evaluations verify the integrity of your organization's data, providing useful quality metrics while helping to tackle any emerging quality issues. Furthermore, BiG EVAL DTA enhances the automation of testing activities within your data-driven initiatives, further simplifying the entire process. By implementing these solutions, organizations can effectively enhance the integrity and dependability of their data assets, leading to improved decision-making and operational efficiency. Ultimately, strong data quality management not only safeguards the data but also enriches the overall business strategy.
What is Ataccama ONE?
Ataccama offers a transformative approach to data management, significantly enhancing enterprise value. By integrating Data Governance, Data Quality, and Master Data Management into a single AI-driven framework, it operates seamlessly across both hybrid and cloud settings. This innovative solution empowers businesses and their data teams with unmatched speed and security, all while maintaining trust, security, and governance over their data assets. As a result, organizations can make informed decisions with confidence, ultimately driving better outcomes and fostering growth.
Integrations Supported
Teradata VantageCloud
Amazon Redshift
Apache Hive
Cloudera
Collibra
Databricks Data Intelligence Platform
Google Cloud BigQuery
Google Cloud Platform
HPE Ezmeral Data Fabric
Hadoop
Integrations Supported
Teradata VantageCloud
Amazon Redshift
Apache Hive
Cloudera
Collibra
Databricks Data Intelligence Platform
Google Cloud BigQuery
Google Cloud Platform
HPE Ezmeral Data Fabric
Hadoop
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
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
BiG EVAL
Date Founded
2010
Company Location
Switzerland
Company Website
bigeval.com/platform/
Company Facts
Organization Name
Ataccama
Date Founded
2007
Company Location
Toronto, Canada
Company Website
www.ataccama.com
Categories and Features
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
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 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 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 Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization