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Data Governance: Framework, Tools, Principles, Benefits

Knowledge Hut

Data governance refers to the set of policies, procedures, mix of people and standards that organisations put in place to manage their data assets. It involves establishing a framework for data management that ensures data quality, privacy, security, and compliance with regulatory requirements.

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Why Data Governance Matters, Best Practices, and How to Build a Strategy

Monte Carlo

Yet as organizations invest in more data and more data accessibility, keeping all that data safe and well-maintained has never been more challenging. That’s why data governance has become a must-have for data-driven organizations. Table of Contents What is data governance?

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Complying with Quebec’s Data Privacy Laws Is Easier with the Data Cloud

Snowflake

Canada, in addition to being one of those 71% of countries with data protection and privacy legislation, stands out as an early adopter of privacy legislation. Quebec takes that a step further with its Bill 64, now referred to as Law 25, which modernizes data protection and privacy legislation for Canada’s second most populated province.

Cloud 91
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Cloudera Open Data Lakehouse Named a Finalist in the CRN Tech Innovator Awards

Cloudera

The Awards showcase IT vendor offerings that provide significant technology advances – and partner growth opportunities – across technology categories including AI and AI infrastructure, cloud management tools, IT infrastructure and monitoring, networking, data storage, and cybersecurity.

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A Closer Look at The Next Phase of Cloudera’s Hybrid Data Lakehouse

Cloudera

Struggling to access and collect, oftentimes disparate and siloed, data across environments that are required to power AI, many organizations are unable to achieve the business insight and value they had hoped for. Available for cloud and now also for the data center. ZDU gives organizations a more convenient means of upgrading.

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DataOps Architecture: 5 Key Components and How to Get Started

Databand.ai

DataOps Architecture Legacy data architectures, which have been widely used for decades, are often characterized by their rigidity and complexity. These systems typically consist of siloed data storage and processing environments, with manual processes and limited collaboration between teams.

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6 Pillars of Data Quality and How to Improve Your Data

Databand.ai

High-quality data is essential for making well-informed decisions, performing accurate analyses, and developing effective strategies. Data quality can be influenced by various factors, such as data collection methods, data entry processes, data storage, and data integration.