Data Digest
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Introducing the Alation Data Products Marketplace: Trusted, High-Impact Data at Speed
Modern organizations face a persistent challenge: balancing rapid insights with the need for trust, security, and compliance. Business leaders need fast access to data, but centralized data teams often become bottlenecks, delaying decision-making. Conversely, decentralized teams promote agility but can introduce inconsistencies in quality and governance. This tension, known as the "Speed vs. Trust Conflict," prevents organizations from fully harnessing their data.
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Blog
Announcing Alation Data Quality: Restoring Trust in Your Data
Today, quality data can often spell the difference between business success and failure. In fact, Gartner projects that poor data quality costs the average business about $12.9 million each year. Small wonder, as poor data quality leads to flawed AI models, operational errors, and costly decisions – creating distrust between data producers and consumers. This lack of trust can severely hinder an organization's ability to make informed decisions and achieve desired outcomes.
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Reimagining Data Management: Tom Davenport on AI, Innovation, and Business Transformation
Tom Davenport is a distinguished thought leader in data, analytics, and artificial intelligence, shaping modern business thinking through more than 20 influential books and numerous articles.
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How to Conduct a Data Protection Impact Assessment: 2025 Guide
Data protection and privacy have become increasingly critical as digital transformation accelerates and regulatory landscapes evolve. A Data Protection Impact Assessment (DPIA) is an essential tool for organizations to manage privacy risks associated with processing personal data.
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Introducing the Alation AI Agent SDK: Easily Build Smarter Agents
The pressure to deliver AI-driven innovation has never been higher, whether you are using off-the-shelf solutions or creating custom tools to meet specific business needs. While many AI teams are in the experimentation stage, piloting new AI projects, leading companies are already capturing substantial returns on investment. According to a recent Deloitte survey, 74% of respondents reported advanced Generative AI initiatives are meeting or exceeding ROI expectations, and 78% of respondents expect to increase their AI spending next year.
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What is AI-powered Data Quality?
AI is reshaping industries and dominating conversations across organizations. Yet, with innovations emerging rapidly, many struggle to understand the nuances between popular AI technologies—and even fewer fully grasp how crucial data quality is for achieving AI success. This blog post defines key AI terms and explains why high-quality data, supported by robust data governance, is foundational for realizing AI’s true potential.
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Reshaping Business Processes with AI: Insights from Raza Habib, CEO of Humanloop
Large Language Models (LLMs) are revolutionizing business operations, transforming how organizations approach automation, decision-making, and efficiency. In a conversation on Data Radicals, Raza Habib, co-founder and CEO of Humanloop, shared his insights on the evolving landscape of AI, including prompt engineering, fine-tuning, AI agents, and the role of data product managers.
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Reinventing the Role of Data Catalogs and Governance in the Era of Agents
When we started Alation in 2012, our mission was clear: to help organizations navigate the complexity of data. At the time, data was exploding in volume, yet there was no easy way for businesses to find, trust, and use it effectively. So, we pioneered the modern data catalog, introducing a solution that empowered data teams and made self-service analytics possible. Since then, a lot has changed.
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Blog
Announcing Alation Data Quality: Restoring Trust in Your Data
Today, quality data can often spell the difference between business success and failure. In fact, Gartner projects that poor data quality costs the average business about $12.9 million each year. Small wonder, as poor data quality leads to flawed AI models, operational errors, and costly decisions – creating distrust between data producers and consumers. This lack of trust can severely hinder an organization's ability to make informed decisions and achieve desired outcomes.
Read now
Blog
Introducing the Alation Data Products Marketplace: Trusted, High-Impact Data at Speed
Modern organizations face a persistent challenge: balancing rapid insights with the need for trust, security, and compliance. Business leaders need fast access to data, but centralized data teams often become bottlenecks, delaying decision-making. Conversely, decentralized teams promote agility but can introduce inconsistencies in quality and governance. This tension, known as the "Speed vs. Trust Conflict," prevents organizations from fully harnessing their data.
Read now
Blog
Data Products vs Data as a Product: What’s the Difference?
Data’s value is unarguably immense. But many organizations struggle to effectively utilize their vast data resources because traditional approaches to data access and usage can’t keep up with exploding data volumes and variety of sources. This post explores two key concepts—data products and data as a product—to uncover how organizations can unlock data’s true potential.
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