Windocks
Windocks provides on-demand Oracle, SQL Server, as well as other databases that can be customized for Dev, Test, Reporting, ML, DevOps, and DevOps. Windocks database orchestration allows for code-free end to end automated delivery. This includes masking, synthetic data, Git operations and access controls, as well as secrets management. Databases can be delivered to conventional instances, Kubernetes or Docker containers.
Windocks can be installed on standard Linux or Windows servers in minutes. It can also run on any public cloud infrastructure or on-premise infrastructure. One VM can host up 50 concurrent database environments. When combined with Docker containers, enterprises often see a 5:1 reduction of lower-level database VMs.
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DataBuck
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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DATPROF
Mask, generate, subset, virtualize, and automate your test data with the DATPROF Test Data Management Suite. Our solution helps managing Personally Identifiable Information and/or too large databases. Long waiting times for test data refreshes are a thing of the past.
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MDClone
The MDClone ADAMS Platform serves as a robust, self-service environment for data analytics that facilitates collaboration, research, and innovation within the healthcare sector. With this groundbreaking platform, users gain real-time, dynamic, secure, and independent access to valuable insights, effectively dismantling obstacles to healthcare data exploration. This empowers organizations to embark on a journey of continuous learning that enhances patient care, optimizes operations, encourages research initiatives, and fosters innovation, thereby driving actionable outcomes throughout the entire healthcare ecosystem. Additionally, the use of synthetic data allows for seamless collaboration among teams, organizations, and external partners, enabling them to delve into the essential information they require precisely when it is needed. By tapping into real-world data sourced directly from within health systems, life science organizations can pinpoint promising patient cohorts for detailed post-marketing analysis. Ultimately, this innovative approach transforms the way healthcare data is accessed and utilized for life sciences, paving the way for unprecedented advancements in the field. As a result, stakeholders can make informed decisions that significantly impact patient outcomes and overall healthcare quality.
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