Video : ER/Studio Enterprise Team Edition

Data Architecture, Data Governance, and Data Warehouse Automation

Data architecture, data governance, and data warehouse automation are essential elements for managing data effectively within an organization. Data architecture is the physical implementation of the business strategy and is a key part of the whole continuum needed to manage data effectively. Data governance promotes the availability, quality, and security of the data of an organization through different policies and standards, ensuring high-quality data that is both secure and easily accessible. Data warehouse automation focuses on the automation of data integration, data engineering, and governance in a data value chain between data providers and data consumers. These three components play a crucial role in maintaining data accuracy, security, and usability throughout the data life cycle, ensuring that the organization can make informed decisions and operate efficiently.

We know WhereScape reduces cost and risk of building and running the warehouse using automation. But users of WhereScape still need to gather metadata on source assets to drive that automation.

Watch this video to learn how metadata provided by your data governance team in the tool of their choice, along with useful business metadata, can pass through to WhereScape. We’ll explore how the structure of your warehouse can align with your accepted enterprise structures and definitions of data. See how the new integration between ER/Studio and WhereScape can deliver this as part of a data fabric ecosystem.

Topics : Data Governance,Data Modeling,Enterprise Architecture,Metadata,

Products : ER/Studio Business Architect,ER/Studio Data Architect,ER/Studio Data Architect Professional,ER/Studio Enterprise Team Edition,

See ER/Studio Enterprise Team Edition in action

ER/Studio Enterprise Team Edition

Document and enhance data from multiple database platforms with ER/Studio Enterprise Team Edition. We can help you build and maintain enterprise data models and metadata.

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