DataBuck
Ensuring 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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Plauti
Plauti is a data quality platform built natively for CRM, designed for organizations that want tight governance, strong security, and practical control over the accuracy of their customer data. Unlike solutions that move data to external servers or require separate platforms, Plauti runs entirely inside your existing CRM infrastructure, so no data leaves your system and no additional security perimeter is introduced.
For Salesforce customers, Plauti covers the end-to-end data quality lifecycle:
Prevent duplicates at the source: Real-time alerts notify users of potential duplicates as they enter records, helping sales, marketing, and service teams keep data clean from the start.
Protect against hidden duplicates: Detect duplicates created by imports, integrations, and APIs to keep inbound data streams aligned with your standards.
Remediate at scale with batch jobs: Run configurable batch processes to find, review, and merge existing duplicates across large data volumes, with full audit trails that support compliance, internal controls, and reporting.
Verify contact information: Check email addresses and phone numbers before they’re saved to reduce bounce rates, improve campaign performance, and support more reliable outreach.
All of this operates on Salesforce’s own infrastructure, using your existing permissions, roles, and security model. There is no separate user login, no data sync lag to manage, and no additional compliance gap to justify to auditors or security teams.
For Microsoft Dynamics 365, Plauti focuses on robust duplicate prevention and control. Admins can configure real-time alerts, leverage API-based detection, run batch processes, and apply cross-entity matching rules to keep accounts, contacts, and leads aligned and consolidated.
Plauti is built for CRM admins, data stewards, and operations teams who need immediate, self-service control over data quality—without waiting for developers, complex projects, or long IT ticket queues.
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ArchiverFS
Introducing a file archiving solution tailored for servers and network storage systems, enabling the utilization of any device as a second-tier storage option.
ArchiverFS is compact yet powerful, offering features like cloud support, DFS replication, de-duplication, and compression. This versatile tool can be deployed on any NAS, SAN, or cloud environment to manage and archive older unstructured files. It allows for network sharing through a UNC path and can be formatted using NTFS. Unlike other solutions, ArchiverFS operates without a database for file storage, pointers, or metadata, relying solely on the straightforward capabilities of NTFS.
With ArchiverFS, you can efficiently transfer large volumes of outdated files from your primary first-tier storage to secondary storage, all while maintaining file attributes, permissions, and directory structures intact. Additionally, it provides the ability to create links that substitute for deleted files, including seamless symbolic links that replicate the appearance and functionality of the original files effortlessly. This makes the process of archiving not only efficient but also user-friendly.
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Data Ladder
Data Ladder specializes in improving data quality and cleansing, dedicated to helping clients optimize their data with services such as data matching, profiling, deduplication, and enrichment. We strive to keep our product offerings straightforward and transparent, delivering outstanding solutions and customer support at competitive rates. Our clientele includes a diverse array of users, notably those from Fortune 500 companies, and we take pride in our ability to attentively listen to their needs, allowing us to rapidly enhance our products. Our user-friendly and powerful software enables business professionals from various industries to handle their data more effectively, resulting in a positive influence on their financial outcomes. Our premier data quality software, DataMatch Enterprise, has proven its efficiency by uncovering approximately 12% to 300% more matches than top competitors like IBM and SAS across 15 independent studies. With over ten years dedicated to research and development, we are perpetually refining our data quality solutions to better serve our clients. This steadfast commitment to innovation has led to more than 4000 successful installations worldwide, highlighting the confidence our customers have in our offerings. As we look to the future, our mission remains focused on delivering exceptional data management tools that foster success and growth for our clients, ultimately shaping a more data-driven world.
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