Data Digest
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Alation Launches Salesforce Connector to Enhance Data Trust
We are excited to announce a new strategic partnership with Salesforce. This partnership will bring data governance and deep insights around data lineage into Salesforce Data Cloud. With this bidirectional integration, Alation joins the Salesforce Data Governance alliance.
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How to Choose the Best Enterprise Data Catalog: Key Criteria Uncovered
It's analyst report season! In the next few months, analyst firms will provide guidance on how to approach the data catalog market and key criteria for choosing a data catalog. These reports can be helpful starting points. But they should be just that: a starting point. With over 12 years of experience and a customer base of nearly 600 enterprises, including 40 of the Fortune 100, we've developed a comprehensive understanding of what truly matters in a data catalog solution to deliver business success. Here are our key criteria uncovered:
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How to Prepare for and Pass a Data Audit
Are you prepared for the growing wave of data regulations? As businesses across all sectors manage ever-increasing volumes of sensitive information, the need to be audit-ready has never been more urgent. This is especially true for industries like finance, healthcare, and the public sector, which face some of the most stringent regulatory demands. With new regulations on the horizon—particularly as AI transforms these fields—routine data audits are essential. They’re not just about compliance but about building a solid foundation to meet future challenges and protect customer trust.
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Understand These Data Governance Models: Centralized, Decentralized, and Federated
Data governance describes how data is gathered and used within an organization. Effective data governance is crucial for ensuring data quality, security, and compliance, as well as enabling informed decision-making and driving business value. Data governance encompasses the processes, policies, and standards that govern how data is managed, secured, and utilized within an organization.
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Top Data Quality Checks Every Business Should Perform
Data quality refers to the accuracy, completeness, consistency, and reliability of data. Organizations today rely heavily on data to make informed decisions, drive business strategies, and gain a competitive edge. However, poor data quality can have severe consequences, leading to flawed analyses, incorrect decisions, and ultimately, financial losses.
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IDC MarketScape for Data Intelligence 2024: Key Takeaways
In the latest IDC MarketScape: Worldwide Data Intelligence Platform Software 2024 Vendor Assessment, Alation has been named a Leader. This year’s report evaluates the 13 vendors in the space.
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Alation’s New Power BI Integration in Microsoft Fabric: Empowering Modern Data Teams
We're excited to announce that Alation now supports Power BI within Microsoft Fabric, Microsoft’s unified platform to streamline and centralize data workflows. This integration reflects Alation’s commitment to becoming the go-to metadata hub for the Fabric ecosystem, helping organizations navigate the rapidly changing landscape of data management and maximize the value of their data.
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Why Metadata Maturity Matters for AI-Ready Data: Key Points from Gartner
In the age of Artificial Intelligence (AI), effective governance is critical to success. According to Gartner’s Market Guide for Metadata Management Solutions, active metadata management is central to ensuring governance – which makes it also essential for AI readiness. This blog highlights key strategies from the guide, offering practical recommendations for business leaders to establish a framework that ensures data reliability and regulatory compliance, while also delivering business value.
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What is Data Architecture? A Detailed Overview
Data architecture serves as the foundational blueprint for managing the entire data lifecycle, encompassing frameworks to ensure data is safe, secure, compliant, and high-quality. Effective data architecture can transform data into a valuable asset that not only supports internal decision-making and compliance but also drives product development and fosters innovation.
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What Is Reference Data Management?
Introduction to Reference Data Management
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Mastering Data Quality Monitoring: Essential Checks & Metrics for Accuracy
Data quality is essential for any organization that relies on accurate and reliable information. Poor data quality has a massive financial impact on businesses. In 2021, Gartner estimated that bad data costs organizations an average of $12.9 million annually, and IBM pegged the U.S. cost at $3.1 trillion back in 2016 (TechTarget). While the importance of clean data is clear, how do we ensure it stays that way over time? Monitoring data quality can range from simple checks to increasingly sophisticated strategies that assess both the data itself and the processes generating it.
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