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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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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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Data management encompasses the processes, policies, and technologies that govern the entire lifecycle of data, from its creation and acquisition to its storage, processing, analysis, and eventual archiving or deletion.
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Imagine a workplace where everyone can easily find, access, and analyze data to make informed decisions. In such an environment, data becomes a true strategic asset, driving critical business operations and unlocking its potential as a game changer. Achieving this vision requires creating a self-service analytics framework that boosts productivity, reduces data quality issues, and ensures broader data access. Here's how to get started.
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Artificial Intelligence (AI) is transforming financial services by automating tasks that require human intelligence, such as decision-making and problem-solving. AI technologies like machine learning, natural language processing, and predictive analytics enable financial institutions to improve operations, enhance customer interactions, and make smarter decisions.
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Data governance defines how data is gathered and used within an organization. It establishes policies, processes, and standards to ensure that data is consistent, trustworthy, and aligned with business objectives. As organizations collect and generate vast amounts of data from various sources, effective data governance becomes crucial for maintaining data quality, ensuring regulatory compliance, and enabling data-driven decision-making.
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Artificial intelligence (AI) is reshaping industries, driving innovation, and opening up new economic opportunities. According to a 2023 report by McKinsey, generative AI has the potential to add between $2.6 trillion and $4.4 trillion in value to the global economy annually.
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Data leaders face a unique double challenge of balancing defensive and offensive data strategies. While data leaders in regulated industries like finance must safeguard data defense (instilling practices focused on compliance, risk management, and data security/privacy), the rise of AI poses a key question: How can they innovate? Offensive data strategies, by contrast, are aimed at driving innovation and competitive advantage with data.
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Artificial Intelligence (AI) is rapidly reshaping the financial services industry, from streamlining operations to creating new products. GXS Bank, a digital bank in Singapore, has been at the forefront of adopting both traditional AI and generative AI (GenAI) to address pressing challenges like fraud detection and customer service. In a recent interview, Dr. Geraldine Wong, Chief Data Officer (CDO) at GXS Bank, shared insights into the bank’s AI experimentation and how these technologies are improving operations and transforming customer experiences.
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Data Security Management (DSM) ensures data is secure, protected, and only accessible to authorised individuals. In this way, it is the bedrock of any organisation's plans to protect their customers and data from cyber threats. As a discipline, it helps organisations comply with internal policies and public regulations.
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Alation is thrilled to announce its inclusion in Amazon Web Services’ (AWS) Data and AI Governance Program. This initiative brings together expert Service Integrators (SIs) and Independent Software Vendors (ISVs) to address the pressing challenges of managing data and AI assets in today’s fast-evolving landscape.
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