Remove Data Warehouse Remove Government Remove Metadata
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The High Cost of Poor Data Warehouse Governance

Monte Carlo

This truth was hammered home recently when ride-hailing giant Uber found itself on the receiving end of a staggering €290 million ($324 million) fine from the Dutch Data Protection Authority. Poor data warehouse governance practices that led to the improper handling of sensitive European driver data. The reason?

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Announcing New Innovations for Data Warehouse, Data Lake, and Data Lakehouse in the Data Cloud 

Snowflake

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

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Eliminate Friction In Your Data Platform Through Unified Metadata Using OpenMetadata

Data Engineering Podcast

Summary A significant source of friction and wasted effort in building and integrating data management systems is the fragmentation of metadata across various tools. Start trusting your data with Monte Carlo today! Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads?

Metadata 100
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Building A Data Governance Bridge Between Cloud And Datacenters For The Enterprise At Privacera

Data Engineering Podcast

Summary Data governance is a practice that requires a high degree of flexibility and collaboration at the organizational and technical levels. The growing prominence of cloud and hybrid environments in data management adds additional stress to an already complex endeavor.

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Bringing The Power Of The DataHub Real-Time Metadata Graph To Everyone At Acryl Data

Data Engineering Podcast

Summary The binding element of all data work is the metadata graph that is generated by all of the workflows that produce the assets used by teams across the organization. The DataHub project was created as a way to bring order to the scale of LinkedIn’s data needs. How is the governance of DataHub being managed?

Metadata 100
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Key considerations when making a decision on a Cloud Data Warehouse

Cloudera

Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

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Databricks, Snowflake and the future

Christophe Blefari

Snowflake was founded in 2012 around its data warehouse product, which is still its core offering, and Databricks was founded in 2013 from academia with Spark co-creator researchers, becoming Apache Spark in 2014. It adds metadata, read, write and transactions that allow you to treat a Parquet file as a table.

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