As enterprise data continues to explode in volume, velocity, and variety, executive leaders must implement mechanisms to ensure that this data is always governed and secure. Therefore, the question that begs is how do organizations make sure their enterprise data is governed and protected?
The title’s questions: What is metadata, and can you have too much of it, are fundamental to answering the overarching question: What role does metadata play in the modern data stack?
As described in the article titled “Everything You Need to Know About DataOps and Data Platforms,” the amount of data generated per day continues to grow unabated. And trying to quantify these daily data volumes (as well as types) continues to prove challenging. At best, it is only possible to derive approximations.
Our DataOps, data orchestration platform, was specifically designed and built as a solution for (or to address) common data problems that prevent most organizations from deriving maximum value from their data, including the following aspects:
DataOps.live and data.world build integrated governance solutions with Snowflake’s Governance Accelerated program and announce 1-Click Data Cataloging for Snowflake
DataOps.live builds integrated governance solutions with Snowflake’s Data Governance Accelerated Program & new capabilities around Object Tagging, Access History, Row Access Policies and Dynamic Masking policies.
Our latest masterclass (held on 9 November 2021) comprised a technical session between our very own Guy Adams and Bryon Jacobs of data.world. The subject was data cataloging – gathering (or collecting) all the metadata from different systems and publishing it in a data catalog.
The rapid and continued expansion of data systems and the exponential explosion of data drive the use cases for advanced data analytics and data science applications. However, without adopting the principles and philosophy of #TrueDataOps, it will always be challenging to develop, test, and deploy data pipelines that deliver trusted, reliable data to analytics applications and machine learning models in a short space of time and according to business stakeholder requirements.
With the exponentially increasing importance of and value attributed to data, it’s never been more critical to test, observe, and monitor the quality of data being used to develop many different data products, driving strategic decision-making at an organizational level. To enhance and facilitate the development of the highest-quality data products, we have recently announced our support for Soda SQL and Soda Cloud. Succinctly stated, Soda SQL has been fully integrated into our DataOps platform, with full support for Soda Cloud.
The cloud data warehouse or data cloud is increasing in importance exponentially as more organizations understand the value of using data-driven insights as a foundation for and critical part of any decision-making process. As a result, it is essential to move unstructured, structured, and semi-structured raw data from its source to a centralized location (the cloud data warehouse) to be processed, transformed, modeled, and analyzed to derive meaningful insights or information.