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In this article, we present a brief overview of compliance and regulations, discuss the cost of non-compliance and some related statistics, and the role data quality and datagovernance play in achieving compliance. The average cost of a data breach among organizations surveyed reached $4.24
One of the key processes in healthcaredata management is integrating data from many patient information sources into a centralized repository. This data comes from various sources, ranging from electronic health records (EHRs) and diagnostic reports to patient feedback and insurance details.
However, according to a survey, up to 68% of data within an enterprise remains unused, representing an untapped resource for driving business growth. One way of unlocking this potential lies in two critical concepts: datagovernance and information governance.
What is a DataGovernance Framework? A datagovernance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.
So, organizations create a datagovernance strategy for managing their data, and an important part of this strategy is building a data catalog. They enable organizations to efficiently manage data by facilitating discovery, lineage tracking, and governance enforcement.
Data fabric aims to simplify the management of enterprise data sources and the ability to extract insights from them. Data fabric platforms should also focus on data sharing, not within the enterprise but also across enterprise. Data Lakes.
All three have a unique purpose in organizing, defining, and accessing data assets within an organization. For instance, in a healthcare institution, “Patient Admission” might be “the process of formally registering a patient for treatment or care within the facility.”
This means that your business’s data is available and secure regardless of a data breach or system failure. Some examples are healthcare analytics software, retail analytics , or modern logistics analytics. In Cloud SaaS, pre-existing disaster recovery protocols are in place to manage potential system failures.
This is because the integration of AI transforms the static repository into a dynamic, self-improving system that not only stores metadata but also enhances data context and accessibility to drive smarter decision-making across the organization. And when everyone has easy access to data, they can collaborate and meet demands more effectively.
Modern data architecture is characterized by flexibility and adaptability, allowing organizations to seamlessly integrate structured and unstructured data, facilitate real-time analytics, and ensure robust datagovernance and security, fostering data-driven insights.
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