DataHub
DataHub is a versatile open-source metadata platform crafted to enhance data discovery, observability, and governance within various data environments. It empowers organizations to easily find reliable data, providing customized experiences for users while avoiding disruptions through precise lineage tracking at both the cross-platform and column levels. By offering a holistic view of business, operational, and technical contexts, DataHub instills trust in your data repository. The platform features automated data quality assessments along with AI-driven anomaly detection, alerting teams to emerging issues and consolidating incident management. With comprehensive lineage information, documentation, and ownership details, DataHub streamlines the resolution of problems. Furthermore, it automates governance processes by classifying evolving assets, significantly reducing manual effort with GenAI documentation, AI-based classification, and intelligent propagation mechanisms. Additionally, DataHub's flexible architecture accommodates more than 70 native integrations, making it a robust choice for organizations seeking to optimize their data ecosystems. This makes it an invaluable tool for any organization looking to enhance their data management capabilities.
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Vertex AI
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case.
Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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ClearOPS
ClearOPS assists both buyers and sellers in effectively managing their vendors while fulfilling due diligence obligations. As a comprehensive third-party risk management platform, ClearOPS allows users to monitor and track all vendor activities, distribute assessments, upload necessary documentation, and navigate the vendor management processes required by their clients. The burden of vendor security questionnaires can feel overwhelming, but our AI streamlines the initial review, significantly reducing the time required for completion. By serving as a system of record, ClearOPS ensures that critical information about your business remains secure and does not inadvertently leave your organization. After securing a customer, the next challenge is retention, and maintaining a strong trust relationship is central to our mission. ClearOPS simplifies the management of privacy and security operations information, making it readily available and current. Our user-friendly third-party risk management software empowers you to inspire your team while allowing you to assess your vendors at your convenience. Moreover, with ClearOPS, you can foster a culture of accountability and transparency within your organization, further enhancing your vendor relationships.
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OneTrust Privacy Automation
Transparency, choice and control are key to trust. Organizations have the opportunity to leverage these moments to build trust, and provide more valuable experiences. People expect greater control over their data. We offer privacy and data governance automation to help organizations better understand and comply with regulatory requirements. We also operationalize risk mitigation to ensure transparency and choice for individuals. Your organization will be able to achieve data privacy compliance quicker and build trust. Our platform helps to break down silos between processes, workflows, teams, and people to operationalize regulatory compliance. It also allows for trusted data use. Building proactive privacy programs that are rooted in global best practice and not just reacting to individual regulations is possible. To drive mitigation and risk-based decision-making, gain visibility into unknown risks. Respect individual choice and integrate privacy and security by default in the data lifecycle.
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