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Data governance with AWS

Balance data access and control to accelerate data-driven decisions

Overview

Data governance with AWS helps organizations accelerate data-driven decisions by making it easy for the right people and applications to securely and safely find, access, and share the right data when they need it. You can curate data by automating data integration and data quality to limit the copies of data. You can discover and understand your data with centralized catalogs that boost data literacy. You can protect your data with precise permissions that let you share data with confidence. And you can reduce risk and improve regulatory compliance posture by monitoring and auditing data access.
Infographic depicting the AWS data governance circle, highlighting analytics and machine learning (ML) governance. The diagram features three main segments: Curate, Protect, and Understand, surrounding central concepts of data governance, analytics, and ML governance, with related activities such as data profiling, data lineage, data catalog, data security, data compliance, data lifecycle, data quality management, data integration, and master data management.

Benefits of data governance with AWS

Identify and manage your most valuable data sources, including databases, data lakes and data warehouses, so you can limit copies and redundant transformation of critical data assets. Curating data also means ensuring that the right data is accurate, fresh, and has sensitive information identified so users can have confidence in the data driving decisions and applications.
Discover and comprehend the meaning of data so data consumers can use it confidently to drive business value. With a centralized data catalog, data can be found easily, access can be requested, and data can be used to make business decisions.
Balance data privacy, security, and access. Govern data access across organizational boundaries, with tools that are intuitive for both business and engineering users.
Understand how data is being used and by whom. AWS services help you monitor and audit data access—including access through ML models-- to help ensure data security and regulatory compliance. Machine learning also requires auditing transparency to ensure responsible use and simplified reporting.

Balance data access and control by working backwards from your business initiatives

Read this O'Reilly Report to learn how to deploy data-driven solutions that require modern data governance. Executives will gain the necessary insights and knowledge to navigate the complexities of managing data governance at scale.
Read the report

Address data governance challenges with AWS

Due to siloed lines of business (LOBs), data stored in multiple formats (open or proprietary) and data stored in multiple storage devices, businesses have a limited view of the totality of data available to them. That blind-spot puts unaccounted-for data at governance risk.

Poor data governance can result in sprawl of a different kind—the creation of data copies to facilitate data access. As data is frequently copied, its reliability as a business’ source of truth degrades. This practices can sometimes result in copies of the data everywhere—perhaps slightly modified—which can can manifest as disconnected and ungoverned data lakes across the LOBs.

Even when a business’ totality of data is curated and accounted for, businesses still struggle to understand what that data means because there’s very little semantic information to explain the data. 

As the number of data users across an organization grow, it's difficult to find and share the best data assets that will drive decisions for targeted business initiatives.

As companies manage more data across more users, ensuring the right users inside and outside the organization have access to the right data becomes increasingly difficult to scale and maintain.

Access that is too restrictive can slow business decision-making. Access that is too lenient can introduce risk.

As the scope of regulatory and compliance obligations increase for businesses, they often struggle to understand who is accessing the data, and if that access aligns with policy and compliance regulations.

Data Governance with AWS Master Class

How can data governance accelerate your business initiatives? How can you use existing enterprise capabilities to build your data governance roadmap and secure funding? In this data governance master class, Kevin Lewis guides you through common missteps, and provides proven best practices.

Learn more about the Data Governance Master Class

Read more about What is Data Governance?

Govern data in your data lakes

Centrally manage and scale fine-grained data access permissions with AWS.
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