Veeva Consumer Products’ Post

Declaring that interest in #generativeAI will grow in 2024 is the easiest prediction in the history of predictions. The more interesting bits are how GenAI adoption will unfold this year, what impact it will have on businesses, and whether there will be unintended side effects on society. To answer these questions, @AIwire turns to a panel of #GenAI experts from industry. Read this article and discover the predictions, including the one by @Angel Viña, CEO & Founder of @Denodo! https://buff.ly/42jkMPY #データ仮想化 #データ統合 #データ連携 #データファブリック #データ利活用 #データマネージメント #DX #デジタルトランスフォーメーション

Enterprises are eager to use #GenAI, but the journey from exploration to full-scale adoption is challenging! Recent research shows that while 66% of organizations were exploring GenAI by late 2023 (IDC), truly operationalizing it across the business is not an easy task. Here are the top issues enterprises deal with when it comes to building a strong data foundation for GenAI. https://lnkd.in/gxDPJfTE

Forbes Tech Council explores how businesses can unlock competitive advantages through GenAI, emphasizing a data-centric approach in a recent article. The piece delves into the transformative potential of GenAI technologies in leveraging data to drive innovation and gain a competitive edge. By harnessing the power of artificial intelligence and data analytics, companies can optimize operations, enhance customer experiences, and uncover valuable insights. This strategic embrace of GenAI represents a pivotal shift in business strategies, paving the way for sustained growth and market leadership in the digital era. https://lnkd.in/et2VmPE5 #ForbesTechCouncil #GenAI #DataCentricApproach #CompetitiveAdvantage #ArtificialIntelligence #DataAnalytics #Innovation #DigitalTransformation #BusinessStrategy #MarketLeadership #UnderstandingEnterpriseTech #EnterpriseTechnologyNow #EnterpriseTechnologyToday

Enterprises are eager to use #GenAI, but the journey from exploration to full-scale adoption is challenging! Recent research shows that while 66% of organizations were exploring GenAI by late 2023 (IDC), truly operationalizing it across the business is not an easy task. Here are the top issues enterprises deal with when it comes to building a strong data foundation for GenAI. https://lnkd.in/g-DbFa9H

Enterprises are eager to use #GenAI, but the journey from exploration to full-scale adoption is challenging! Recent research shows that while 66% of organizations were exploring GenAI by late 2023 (IDC), truly operationalizing it across the business is not an easy task. Here are the top issues enterprises deal with when it comes to building a strong data foundation for GenAI. https://lnkd.in/dqNmVe5W

Enterprises are eager to use #GenAI, but the journey from exploration to full-scale adoption is challenging! Recent research shows that while 66% of organizations were exploring GenAI by late 2023 (IDC), truly operationalizing it across the business is not an easy task. Here are the top issues enterprises deal with when it comes to building a strong data foundation for GenAI. https://lnkd.in/gNZ4DN8E

Enterprises are eager to use #GenAI, but the journey from exploration to full-scale adoption is challenging! Recent research shows that while 66% of organizations were exploring GenAI by late 2023 (IDC), truly operationalizing it across the business is not an easy task. Here are the top issues enterprises deal with when it comes to building a strong data foundation for GenAI. https://lnkd.in/gS7_DDfG

While #GenAI is here to stay, for most companies it is also a future tool. Right now access to #GenAI will be through existing technology and how it is deployed by those companies. Curious about the impact of #GenAI in the business world? Check out what industry leaders, like #Qlik's Brendan Grady, have to say about its staying power.

At Data Ideology, we understand that harnessing the power of AI requires a robust data foundation focusing on data strategy, governance, and infrastructure. -Data Strategy: A data strategy is the cornerstone of successful AI adoption, aligning business objectives with data-driven decision-making processes. -Data Foundation: Want AI success? You need a strong data foundation to establish reliable data pipelines, implement efficient data solutions, and ensure data quality. -Data Governance: Your data needs to be accurate, secure, and in compliance before it can power any AI solution. A clear Data Governance policy will keep your data assets protected and used responsibly. -Solving Data Challenges: From data silos to integration complexities, you’ll need to navigate more than one challenge on your journey to AI adoption. At Data Ideology, we leverage our expertise and experience to help you overcome these obstacles. Are you ready to transform your data into a strategic asset and unleash the power of AI? Connect with us at Data Ideology to learn more about our comprehensive data solutions and how we can help you achieve your business objectives. #DataStrategy #DataFoundation #DataGovernance #AI #DataChallenges #Innovation #DataIdeology #TransformingData #UnlockingPotential

Privileged to have joined today's roundtable with esteemed data leaders from Operative, Telesign, Layer5, Braze, Aquifer, and Sightly (yours truly). We delved into several critical aspects of data management: Data Infrastructure Management: We shared approaches combining cloud platforms like AWS with custom in-house systems. Discussions revolved around tackling challenges in scaling, navigating privacy regulations, and cost management. The group also emphasized the need for robust data governance, access controls, and efficient cataloging. Talent Retention & Skills Shortage: There was a strong focus on the necessity of continuous professional development and crafting compelling employee value propositions to attract and retain talent. I pointed out that it's important to consider the varying values of employees across different generations when making hiring and retention decisions. Data Centralization: We explored the pros and cons of data lakes versus decentralized data mesh models. A shared understanding emerged that flexibility in data management is crucial, as no single model suits all purposes. Data Storage and Processing Costs: The discussion acknowledged the universal cost rise due to increasing data volume, more complex analytics, and stringent privacy requirements. Innovative approaches like data minimization and the creation of monetizable data products were suggested as potential cost mitigation strategies. Leveraging Generative AI: We exchanged experiences on using generative AI, noting varying levels of adoption. The potential of AI in automating processes and creating competitive advantages was recognized, along with the current limitations in quality when applied to proprietary enterprise data. I added that Gen AI can create a skills moat, where if we have our teams using Gen AI to augment their skills and productivity, it can create competitive advantages. The meeting concluded with a consensus that data management strategies must be tailored to individual and organizational needs and that privacy and residency concerns are increasingly shaping these strategies. A big thank you to Sam Aberman's AI note-taker for helping with the recap! #DataManagement #Innovation #AI #BigData #DigitalTransformation"