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Data Management in the Cloud

Data management encompasses acquiring, storing, protecting, and processing data across an organization or business unit. It helps ensure that data is validated and fully accessible to stakeholders when needed. Data provenance (origin) and data governance (rules and procedures around data security and access) can ll roll up into the data management function.

Data Cloud for Dummies Cloud Data Lake for Dummies

As cloud computing becomes ubiquitous among most core enterprise business functions, data management in the cloud is naturally growing in adoption. Decades of Murphy's Law growth in storage and compute capacity followed by the capacity explosion of the cloud has reduced the price of storage to a tiny fraction of what is was a few decades ago. Tradtional on-premise data lakes and data warehouse products can run in an all-cloud or multi-cloud environment and it is therefore entirely logical that data management and governance are following suit. 

Big data management in the cloud can also be defined as the collection of data from a broad range of cloud applications, with all of that data then stored and processed in a data cloud environment.

Data management in the cloud is part of a broader trend of data modernization. In the past, cloud and data strategies were often managed separately. Today, they should be part of a broader unified strategy that takes advantage of the cloud's inherent elasticity, scalability, and economies of scale to enable faster, more powerful business insights and new capabilities.

Snowflake and Data Management in the Cloud

The Snowflake Data Cloud is purpose-built to help companies pursue an aggressive data modernization strategy. Encompassing cloud-built data warehousing, cloud data lake, collaboration, data science, data engineering, applications and a data marketplace across one or multiple clouds, the Snowflake platform allow businesses to build the most modern data infrastructure possible to drive better business outcomes and stay ahead of the competition. Full elasticity and scalability allow Snowflake users to meet almost any volume or concurrency challenges. A robust partner ecosystem connects Snowflake to preferred BI, data science, machine learning, and ETL tools.