Best Metadata Management Software for Freelancers

data.world is a fully managed service, born in the cloud, and optimized for modern data architectures. That means we handle all updates, migrations, and maintenance. Set up is fast and simple with a large and growing ecosystem of pre-built integrations including all of the major cloud data warehouses. When time-to-value is critical, your team needs to solve real business problems, not fight with hard-to-manage data software. data.world makes it easy for everyone, not just the "data people", to get clear, accurate, fast answers to any business question. Our cloud-native data catalog maps your siloed, distributed data to familiar and consistent business concepts, creating a unified body of knowledge anyone can find, understand, and use. In addition to our enterprise product, data.world is home to the world’s largest collaborative open data community. It’s where people team up on everything from social bot detection to award-winning data journalism.

The modern data workspace. Make all your data assets from data tables to BI reports, instantly discoverable. Our powerful search algorithms combined with easy browsing experience, make finding the right asset, a breeze. Atlan auto-generates data quality profiles which make detecting bad data, dead easy. From automatic variable type detection & frequency distribution to missing values and outlier detection, we’ve got you covered. Atlan takes the pain away from governing and managing your data ecosystem! Atlan’s bots parse through SQL query history to auto construct data lineage and auto-detect PII data, allowing you to create dynamic access policies & best in class governance. Even non-technical users can directly query across multiple data lakes, warehouses & DBs using our excel-like query builder. Native integrations with tools like Tableau and Jupyter makes data collaboration come alive.

Anzo is a modern data discovery and integration platform that lets anyone find, connect and blend any enterprise data into analytics-ready datasets. Anzo’s unique use of semantics and graph data models makes it practical for the first time for virtually anyone in your organization – from skilled data scientists to novice business users – to drive the data discovery and integration process and build their own analytics-ready datasets. Anzo’s graph data models provide business users with a visual map of enterprise data that is easy to understand and navigate, even when your data is vast, siloed and complex. Semantics add business content to data, allowing users to harmonize data based on shared definitions and build blended, business-ready data on demand.

Infor OS is your cloud operating platform for the future, designed to bring productivity, business processes and Artificial Intelligence together, and offer operational insights that were never accessible to a business before. The platform delivers technology that goes beyond enabling business, it drives it, putting the user at the centre of every experience, and serving as a unifying foundation for your entire business ecosystem. The result is a connected, intelligent network that automates, anticipates, predicts, and informs your stakeholders, unifying your business. By marrying business processes to employee communications, Infor OS's collaboration capabilities allow you to contextualise intelligence, make single sign-on a reality, and increase efficiency by enabling employees to work smarter and faster. Quickly develop enterprise capabilities tailored to your needs with the extensibility provided by Infor OS.

Aggua is a data fabric augmented AI platform that enables data and business teams Access to their data, creating Trust and giving practical Data Insights, for a more holistic, data-centric decision-making. Instead of wondering what is going on underneath the hood of your organization's data stack, become immediately informed with a few clicks. Get access to data cost insights, data lineage and documentation without needing to take time out of your data engineer's workday. Instead of spending a lot of time tracing what a data type change will break in your data pipelines, tables and infrastructure, with automated lineage, your data architects and engineers can spend less time manually going through logs and DAGs and more time actually making the changes to infrastructure.