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Listen to data and analytics leaders share the secrets of their success. Wayne Eckerson, long-time global thought leader interviews guests who run data and analytics programs at Fortune 2000 organizations around the world. Tune in to stay abreast of the latest technologies, techniques, and trends in our fast-paced industry.
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Discover best practices to scale Power BI effectively—improving performance, governance, and self-service across enterprise environments.Published at:https://datalere.com/articles/power-bi-best-practices-from-the-field-lessons-from-enterprise-deploymentsVon Eckerson Group
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Chief Data Officers are expanding data sharing to drive productivity, innovation, and better decisions. Data marketplaces simplify access by connecting users to ready-to-use, high-value data through a centralized, self-service platform.Published at:https://www.eckerson.com/articles/how-data-product-marketplaces-enable-seamless-data-consumption-and-…
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This blog defines the governance requirements that streaming data pipelines must meet to make artificial intelligence/machine learning (AI/ML) initiatives successful.Published at:https://www.eckerson.com/articles/streaming-data-governance-three-must-have-requirements-to-support-ai-ml-innovationVon Eckerson Group
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Despite $180 billion spent on big data tools and technologies, poor data quality remains a significant barrier for businesses, especially in achieving Generative AI goals.Published at:https://www.eckerson.com/articles/poor-data-quality-is-a-full-blown-crisis-a-2024-customer-insight-reportVon Eckerson Group
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This article explores how Product Information Management (PIM) helps manufacturers and retailers manage rich product data through phased attribution and collaborative workflows.Published at:https://www.eckerson.com/articles/keys-to-succeeding-in-your-product-information-management-pim-journeyVon Eckerson Group
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As cloud adoption accelerates, not all analytics workloads are heading in the same direction. This blog explores three strategic options for data and IT leaders.Published at:https://www.eckerson.com/articles/are-you-cloud-bound-the-case-for-migration-repatriation-or-keeping-your-analytics-projects-on-premises…
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This article breaks down the evolving landscape of AI/ML platforms, from AutoML to full-stack AI workbenches, and provides a structured tool evaluation framework to cut through vendor ambiguity.Published at:https://www.eckerson.com/articles/the-ai-ml-tool-evaluation-template-a-guide-to-smarter-selection…
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This guide provides a step-by-step framework to assess vendors, align priorities, and make informed decisions about enterprise data and analytics tools.Published at:https://www.eckerson.com/articles/the-buyer-s-guide-to-selecting-the-right-enterprise-data-analytics-toolVon Eckerson Group
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This blog, the second in a series, recommends six criteria to help data leaders evaluate tools for managing streaming data pipelines.Published at:https://www.eckerson.com/articles/ultimate-guide-to-streaming-data-pipelines-six-criteria-to-evaluate-and-select-the-right-toolVon Eckerson Group
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Change is inevitable, but adoption is key. From AI/ML tools to leadership shifts, success depends on aligning people, not just technology.Published at:https://www.eckerson.com/articles/managing-change-in-the-age-of-ai-the-head-heart-and-herd-frameworkVon Eckerson Group
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This blog covers integrating SAP and third-party systems to build a unified data foundation for analytics and AI in conversational use cases.Published at:https://www.eckerson.com/articles/analytics-and-ai-for-sap-environments-build-a-unified-data-foundation-to-drive-advanced-use-casesVon Eckerson Group
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This blog recommends four questions to help data and AI leaders compare homegrown and commercial options for retrieval augmented generation.Published at:https://www.eckerson.com/articles/build-or-buy-rag-four-questions-to-guide-your-approach-to-retrieval-augmented-generation-for-genaiVon Eckerson Group
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Exploring data observability’s limits in data migration, integrity audits, and the need for specialized tools for reliability.Published at:https://www.eckerson.com/articles/the-shiny-allure-of-data-observability-its-limits-in-data-migration-integrity-audits-and-certificationVon Eckerson Group
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Many practitioners view data mesh and data fabric as mutually exclusive approaches to data strategy. However, these paradigms complement each other. Data mesh focuses on decentralization and autonomy; Data fabric ensures centralized integration and governance. Let’s dive into how blending elements of both can offer flexibility and control to create…
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As organizations grapple with data spread across various storage locations, solutions like Coginiti Hybrid Query offer a much-needed alternative to fragmented tools.Published at:https://www.eckerson.com/articles/a-novel-approach-for-reducing-cloud-data-warehouse-expenses-from-coginitiVon Eckerson Group
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Data teams must filter, blend, and refine raw data inputs to create the high-octane fuel that drives innovation with artificial intelligence and machine learning (AI/ML).Published at:https://www.eckerson.com/articles/refining-the-right-fuel-how-data-integration-drives-the-ai-ml-model-lifecycleVon Eckerson Group
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Many data leaders want to implement self-service, but don’t realize that they first have to implement the right architecture, governance, operating model, project delivery approach, data, and change management plan.Published at:https://www.eckerson.com/articles/self-service-is-the-outcome-not-the-driver-of-a-data-driven-organization…
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Explore the essential characteristics to choose the right conversational query tool for your needs and environment.Published at:https://www.eckerson.com/articles/modernizing-analytics-with-conversational-query-tools-five-must-have-characteristicsVon Eckerson Group
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Data analytics is a balance of flexibility for innovation and governance to control risks. This blog discusses its implications for artificial intelligence (AI), including machine learning (ML) and generative AI (GenAI).Published at:https://www.eckerson.com/articles/ai-ml-innovation-requires-a-flexible-yet-governed-data-architecture…
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Non-profit organizations are more mission-driven, consensus-driven, and resource-constrained than commercial organizations. As a result, it’s imperative that non-profits develop a data strategy before plunging into building data solutions. It will save them time, money, and burnout in the long run.Published at: https://www.eckerson.com/articles/why…
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Explore the reasons for data engineers to collaborate with data scientists, machine learning (ML) engineers, and developers on DataOps initiatives that support GenAI.Published at:https://www.eckerson.com/articles/dataops-for-generative-ai-data-pipelines-part-iii-team-collaborationVon Eckerson Group
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This article compares data catalogs and data marketplaces and argues that you need both and will soon have both as vendors add data marketplace extensions.Published at:https://www.eckerson.com/articles/why-do-i-need-a-data-marketplace-when-i-have-a-data-catalogVon Eckerson Group
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This blog defines conversational BI, why companies should consider it, and how their power and casual users can best get the desired results.Published at:https://www.eckerson.com/articles/driving-results-with-conversational-bi-best-practices-for-power-and-casual-usersVon Eckerson Group
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Data engineering is now considered a crucial job in IT as Generative AI, the hottest technology of this decade, relies on data engineers to provide accurate inputs.Published at:https://www.eckerson.com/articles/data-engineering-for-genai-how-to-optimize-data-pipelines-and-governanceVon Eckerson Group
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Companies that adopt DataOps increase the odds of success by making GenAI data pipelines what they should be: modular, scalable, robust, flexible, and governed.Published: https://www.eckerson.com/articles/dataops-for-generative-ai-data-pipelines-part-ii-must-have-characteristicsVon Eckerson Group
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Most data leaders want to deliver data products, but few are doing it. Let's face it: most data teams today function as internal service bureaus that fulfill customer requests that arrive via ticketing systems, email, handwritten notes, or calls from colleagues looking for a favor. Most work double time to keep their request backlogs from balloonin…
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"Meet the business where it is." If you're on the data team, that's what you're expected to do to empower stakeholders with data. But how far should you go to meet the business? And shouldn’t the business be expected to move a little toward meeting the data where it is?Published at:https://www.eckerson.com/articles/meeting-the-data-where-it-is-time…
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The European Union recently passed the first of its kind legal framework on the development, use, and governance of artificial intelligence. It lays out rules and standards with the aim of ensuring technologies are safe and transparent, and do not violate the fundamental rights of an individual.Published at:https://www.eckerson.com/articles/the-eu-…
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Most organizations are committed to responsible and ethical use of AI. Yet anticipating unintended consequences before designing and implementing AI can be challenging. This framework and process helps evaluate short-term and long-term impacts across multiple dimensions so you can mitigate AI’s unintended consequences.Published at:https://www.ecker…
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