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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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D&B ConnectMaximizing the value of your first-party data is essential for success. D&B Connect offers a customizable master data management solution that is self-service and capable of scaling to meet your needs. With D&B Connect's suite of products, you can break down data silos and unify your information into one cohesive platform. Our extensive database, featuring hundreds of millions of records, allows for the enhancement, cleansing, and benchmarking of your data assets. This results in a unified source of truth that enables teams to make informed business decisions with confidence. When you utilize reliable data, you pave the way for growth while minimizing risks. A robust data foundation empowers your sales and marketing teams to effectively align territories by providing a comprehensive overview of account relationships. This not only reduces internal conflicts and misunderstandings stemming from inadequate or flawed data but also enhances segmentation and targeting efforts. Furthermore, it leads to improved personalization and the quality of leads generated from marketing efforts, ultimately boosting the accuracy of reporting and return on investment analysis as well. By integrating trusted data, your organization can position itself for sustainable success and strategic growth.
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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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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.
What is Rational Governance?
Rational Governance is a specialized enterprise software solution designed to support various industry applications aimed at identifying, understanding, categorizing, and managing data effectively. The system utilizes several essential technologies, including a lightweight software framework that connects with vital unstructured data sources such as personal computers, email platforms, file storage systems, and document management tools, all of which work together to create a comprehensive content index. Its architecture includes a central server that allows for the unified searching and administration of all indexed materials, complemented by advanced analytical tools that leverage sophisticated machine-learning algorithms to facilitate automated content classification and extensive data analysis. Data management is executed through these analytical capabilities on a project or policy basis, empowering organizations to manage their content effectively by enabling the preservation, deletion, duplication, relocation, or tracking of data from a single centralized interface. This efficient, streamlined methodology not only enhances operational efficiency but also significantly strengthens data governance and compliance throughout the organization, ensuring that all data handling practices adhere to regulatory standards. Furthermore, by integrating these capabilities, Rational Governance positions itself as a crucial ally in navigating the complexities of modern data management challenges.
What is Data Identification Manager™?
The Data Identification Manager™ streamlines the process of data classification by employing consistent technology, rules, and continuous oversight throughout the organization. By doing so, it effectively safeguards your entire IT infrastructure against the risks associated with untrustworthy and unnecessary data. Moreover, this comprehensive approach enhances overall data governance and operational efficiency.
Integrations Supported
ShareFile
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
Rational Enterprise
Date Founded
2006
Company Location
United States
Company Website
Rationalenterprise.com
Company Facts
Organization Name
Data443 Risk Mitigation, Inc.
Date Founded
2016
Company Location
United States
Company Website
data443.com/products/data-identification-manager/
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
Categories and Features
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 Privacy Management
Access Control
CCPA Compliance
Consent Management
Data Mapping
GDPR Compliance
Incident Management
PIA / DPIA
Policy Management
Risk Management
Sensitive Data Identification
eDiscovery
Case Analytics
Compliance Management
Discussion Threads
Document Indexing
Document Tracking
Full Text Extraction
Keyword Search
Metadata Extraction
Topic Clustering
GDPR Compliance
Access Control
Consent Management
Data Mapping
Incident Management
PIA / DPIA
Policy Management
Risk Management
Sensitive Data Identification
Policy Management
Approval Process Control
Attestation
Audit Trails
Policy Creation
Policy Library
Policy Metadata Management
Policy Training
Reporting / Analytics
Version Control
Workflow Management