Best Data Governance Software for Apache Hive

Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

Ataccama is a revolutionary way to manage data and create enterprise value. Ataccama unifies Data Governance, Data Quality and Master Data Management into one AI-powered fabric that can be used in hybrid and cloud environments. This gives your business and data teams unprecedented speed and security while ensuring trust, security and governance of your data.

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

DataHub is a free and open-source metadata platform that streamlines data discovery, observability and governance across diverse data ecologies. It allows organizations to discover trustworthy data with experiences tailored to each user and eliminates breaking updates with detailed cross-platform, column-level lineage. DataHub gives you a complete view of your data, including its business, operational and technical context. The platform provides automated data quality checks, AI-driven anomaly identification and alerts teams when problems arise. It also centralizes incident tracking. DataHub's detailed ownership, documentation, and lineage information allows for quick issue resolution. It automates governance by classifying assets in real-time, reducing manual work with GenAI documentation, AI classification, and smart propagation. DataHub’s extensible architecture supports more than 70 native integrations.

Astronomer is the driving force behind Apache Airflow, the de facto standard for expressing data flows as code. Airflow is downloaded more than 4 million times each month and is used by hundreds of thousands of teams around the world. For data teams looking to increase the availability of trusted data, Astronomer provides Astro, the modern data orchestration platform, powered by Airflow. Astro enables data engineers, data scientists, and data analysts to build, run, and observe pipelines-as-code. Founded in 2018, Astronomer is a global remote-first company with hubs in Cincinnati, New York, San Francisco, and San Jose. Customers in more than 35 countries trust Astronomer as their partner for data orchestration.

Alteryx AI Platform will help you enter a new age of analytics. Empower your organization through automated data preparation, AI powered analytics, and accessible machine learning - all with embedded governance. Welcome to a future of data-driven decision making for every user, team and step. Empower your team with an intuitive, easy-to-use user experience that allows everyone to create analytical solutions that improve productivity and efficiency. Create an analytics culture using an end-toend cloud analytics platform. Data can be transformed into insights through self-service data preparation, machine learning and AI generated insights. Security standards and certifications are the best way to reduce risk and ensure that your data is protected. Open API standards allow you to connect with your data and applications.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

Apache Ranger™, a framework that enables, monitors and manages comprehensive data security across Hadoop's platform, is called Apache Ranger. Ranger's goal is to provide complete security across the Apache Hadoop ecosystem. Apache YARN has made it possible to create a data lake architecture on Hadoop. Multi-tenant environments allow enterprises to run multiple workloads. Hadoop data security must evolve to support multiple use-cases for data access. It also provides a framework for central administration and monitoring of user access. All security-related tasks can be managed centrally through a UI or REST APIs using central security administration. Fine-grained authorization to perform a specific action or operation with a Hadoop component/tool. This is managed through a central admin tool. Standardize authorization methods across all Hadoop components. Enhanced support for different authorization methods, such as Role-based access control, etc.

Complexity is the enemy of security. Simplify and scale fine-grained data access control. Dynamically authorize and audit every query to comply with data security and privacy regulations. Okera integrates seamlessly into your infrastructure – in the cloud, on premise, and with cloud-native and legacy tools. With Okera, data users can use data responsibly, while protecting them from inappropriately accessing data that is confidential, personally identifiable, or regulated. Okera’s robust audit capabilities and data usage intelligence deliver the real-time and historical information that data security, compliance, and data delivery teams need to respond quickly to incidents, optimize processes, and analyze the performance of enterprise data initiatives.

Find out in minutes if you have sensitive data hidden in places that you didn't expect (Screenshots and logs, messages, tickets, tables, messages). LightBeam's executive or delta reports can be generated with just one click to gain valuable insight into your sensitive data. Automate DSRs by leveraging LightBeam’s unique PII/PHI charts, which are comprehensively created based on your data infrastructure. By giving your users control over the data they collect, you can build trust with them. Monitor how sensitive data are collected, shared and maintained within your organization.

Identify code issues and optimize code in real-time. Prevent data incidents before deployment. Manage code changes that impact data from the operational database all the way to the dashboard. Data lineage is automated, allowing for analysis of every dependency, from the operational database to the reporting layer. Foundational automates the enforcement of data contracts by analyzing each repository, from upstream to downstream, directly from the source code. Use Foundational to identify and prevent code and data issues. Create controls and guardrails. Foundational can be configured in minutes without requiring any code changes.

Bluetab Solutions developed Truedat, an open-source data governance business solution tool. It was created to help our clients become data-driven businesses. We assist in defining business processes, roles and responsibilities. We can also help you put these processes into action. Integration and customization of truedat’s open-source components to support data governance processes. We guarantee the maintenance and support of the solution modules we have installed. Based on our extensive experience, we have created a solution that addresses the need for Data Governance. This allows you to manage complex and changing data architectures. Truedat is becoming more important due to the increasing migration of enterprise IT platforms into cloud, multi-cloud, hybrid architectures. This increases the complexity, sources, and types of data. Our Data Governance consulting and development experience spans more than 8 years.

QueryPie allows you to centrally manage multiple data sources and security policies from one place. Your company can be on the fast track for success without having to change the data environment. Data governance is essential in today's data-driven world. You must ensure that you adhere to data governance standards and allow many users accessing growing amounts of important information. You can establish data access policies by adding key attributes like IP address and access time. To secure data analysis and editing, privilege types can be created using SQL commands such as DML, DCL and DDL. You can view logs based upon permissions to see details of SQL events and uncover user behavior and security concerns. All history can be exported to a file for reporting purposes.

No more data catalog ghost cities. Acryl Cloud accelerates time-to-value for data producers through Shift Left practices and an intuitive user interface for data consumers. Continuously detect data-quality incidents in real time, automate anomaly detecting to prevent breakdowns, and drive quick resolution when they occur. Acryl Cloud supports both pull-based and push-based metadata ingestion to ensure information is reliable, current, and definitive. Data should be operational. Automated Metadata Tests can be used to uncover new insights and areas for improvement. They go beyond simple visibility. Reduce confusion and speed up resolution with clear asset ownership and automatic detection. Streamlined alerts and time-based traceability are also available.

Salesforce Data Cloud is an online data platform that allows businesses to collect, harmonize, and analyze data in real time. This creates a 360-degree customer profile which can be used across Salesforce's various applications, such as Marketing Cloud, Sales Cloud, and Service Cloud. It allows businesses collect, harmonize and analyze data in real-time, creating a 360° customer profile that can then be used across Salesforce's different applications, including Marketing Cloud, Sales Cloud and Service Cloud. This platform allows for faster, more personal customer interactions through the integration of data from online and off-line channels, such as CRM data, transactional information, and third-party sources. Salesforce Data Cloud offers advanced AI and analytics capabilities that help organizations gain deeper insight into customer behavior, and predict future needs. Salesforce Data Cloud helps improve customer experiences, target marketing, and data-driven decision making across departments by centralizing and refining the data.