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In an era dominated by data-driven decisions, remaining on the cutting edge is not just an advantage—it's a necessity. With Fortune 100 companies already leveraging this transformative tool, and market research experts like Ray Poynter saying that “Synthetic Data will be a big part of market research and insights”*, the question isn't whether you should join the wave but how quickly you can dive in. Join our webinar, Want to ride the synthetic data wave? Dive in now with your own data, featuring industry expert Doug Guion to unlock the secrets of synthetic data and ensure your business isn't left behind. Doug will explore: 💡 The latest innovations in synthetic data for market research 💡 The doors these innovations open for brands and agencies alike 💡 How custom synthetic data can provide business-specific data to your projects, and 💡 Tips to building your business case for synthetic data solutions in your business WEBINAR DETAILS Want to ride the synthetic data wave? Dive in now with your own data 26 Mar // 2:00pm PST & 27 Mar // 9:30am PST Secure your seat today >> https://hubs.la/Q02nQHbC0 #SyntheticData #Insights #Innovation #AI * https://hubs.la/Q02nQVbJ0

🌐 **Data Observability: Evolving in the Digital Era** 📈 As organizations continue to embrace digital transformation, **data observability** has become more crucial than ever. The way we monitor and understand our data has evolved, reflecting the complexities of modern data ecosystems. 🔍 **Why Data Observability Matters**: In today’s digital age, data is the backbone of every decision. To stay competitive, businesses need real-time visibility into their data pipelines, ensuring accuracy, reliability, and timeliness. Data observability goes beyond traditional monitoring, providing insights into the **health** of your data across various platforms. 🚀 **Key Trends Driving Data Observability**: 1. **Real-Time Monitoring**: As data velocity increases, real-time insights are essential for quick decision-making. 2. **AI-Driven Analytics**: Leveraging AI and machine learning to detect anomalies and predict potential issues before they escalate. 3. **End-to-End Visibility**: Observability tools are now focusing on giving a complete view—from data ingestion to consumption—across hybrid and multi-cloud environments. 4. **Proactive Issue Resolution**: Moving from reactive monitoring to proactive strategies that prevent data downtime and ensure data quality. As data observability continues to evolve, it's empowering organizations to make better decisions, faster. It’s not just about seeing your data—it's about understanding it, ensuring its quality, and using it to drive innovation. #DataObservability #DigitalTransformation #DataQuality #Analytics #AI #BigData #DataOps

The 2024 #DataIQ100 Summit USA brought together the biggest names in #data and #analytics to discuss the most pressing matters facing the industry.   Key takeaways included:   💡 How to lead an AI revolution Diana Hoskins Schildhouse, Chief Analytics and Insights Officer, Colgate-Palmolive emphasized a business-first approach. "Our goal is to deliver impact, not outputs. Ask what actions were taken based on the recommendations and aim to quantify the expected benefits, ensuring alignment with the derived value.”  Shashank Kadetotad, Global Director and Head of Data Sciences, Mars, delved into how the data team at Mars Wrigley has taken a “business problem first mindset” to tackling value creation with AI. They explained that “data strategy should be core to any company in this digital age," and this digital strategy is what leads on to the connected data foundation.    💡 Leading through AI transformation Sathish M., Chief Information, Data, and Digital Officer, Ally, discussed the importance of building your business to accommodate emerging technologies and advised developing an AI Playbook to act as a translator for the new language you will be speaking.   💡 Being a data narrator  Avinash Tripathi, Vice President of Analytics, University of Phoenix highlighted the need for simplicity. “Start with a clear understanding of the problem itself, identify the success criteria for the use case, focus on two data metrics at most, and identify and analyze your stakeholders – this part is critical as it’s all about collaboration.”    💡 Scaling AI: Fireside with Blend and NBC Universal  John Lee, CDO, NBCUniversal, identified seven main challenges to navigate to achieve scale: AI talent, lack of strong data foundations, technical challenges, speed of innovation, business strategy integration failures, change management and trust.   💡 DataIQ 100 on how to lead business transformation Panellists from the #DataIQ100, including Meaghan Ferrigno, CFO and Chief Data and Analytics Officer, Destination Canada, Ronke Ekwensi Ekwenski, Vice President Data, T-Mobile, Satya Choudary, Vice President - Head of Cloud Platform, Data Analytics, Data Science and ML/AI, Credit Suisse and Ido Biger, Chief Information and Data Officer, Delek US Holdings, Inc., Grace Lee, SVP and Chief Data & Analytics Officer, Scotiabank and Dara Meath, PMP, SVP, Chief Technology Officer, Build-A-Bear Workshop pondered the potential of AI in transforming business and industry performance.   💡 Responsible AI  Ellen Nielsen, Former CDO, Chevron, presented a four-prong structure for addressing responsible AI and encouraged companies to consider their risk profile and what guidelines they should provide as key principles.   For a deeper dive into these insights, read the full article: https://lnkd.in/dPY5CktJ Keep up to date on registration for the 2025 #DataIQ100 Summit USA: https://lnkd.in/ePBjxb_N

🔔 Some great takeaways from a fantastic event which brought together some of the most influential people in data and analytics and recognized leading organization's developments using AI! 📢 DataIQ brings data professionals together to connect and network to overcome challenges, inform decision making and achieve data-driven excellence. ✉ If you would like to learn about our future events or what we do at DataIQ- please drop me a message!

Register for our upcoming webinar: "How AI is Changing Data Quality" presented by Gorkem Sevinc and Piyush Mehta 📆 Register here: https://lnkd.in/esJpU4VB What we'll cover: 🔘 Learn how AI can help tackle the toughest challenges in data quality. 🔘 Discover essential tools and processes for improving data quality. 🔘 Understand how to measure ROI and gain insights from real-world success stories. Hosted by DataCamp #datacamp #qualytics #dataquality #genai #machinelearning #webinar #data #bigdata

Good McKinsey article that outlines ways organization should incorporate GenAI into their data strategy to accelerate innovation and digital transformation by: 1/ Automating complex tasks enhances data engineering, leading to more accurate and efficient processing of vast data volumes. 2/ Advancing data governance through predictive analytics and pattern recognition to identify potential breaches and inconsistencies, facilitating proactive measures to safeguard sensitive information. 3/ Unlocking deeper insights by sifting through extensive datasets to anticipate market changes and customer needs, driving strategic decision-making and fostering a data-driven culture. 4/ Optimizing data operations to make them more cost-effective and efficient. 5/ Catalyzing innovation in product and service development by creating personalized offerings, improving customer engagement, and taping into new markets industries.

Do you wish to unlock hidden value in your business? In a world that generates huge amount of data every day, understanding the concept of #DataNormalization is crucial. Data Normalization is a technique that organizes #Data in such a way that you can serve your business well. It helps you realize the potential of your data, reduce redundancy, and make sure the data dependencies are logically designed leading to more efficient use of your data. Unnormalized data could be preventing you from gleaning critical business insights. To maximize the power of your data, investing in industries best practices for data normalization can steer your organization toward a data-driven future. Tap in to deep-dive into the potential of properly normalized data and how it can transform the way you run your business operations. Worth the time, I promise! 🙌 Ready to start your journey towards data normalization? Let's talk about it! 🚀 Schedule a quick call with me at your convenient time here👉 https://buff.ly/3TOGCad #BigData #DataScience #BusinessIntelligence #NoCode #AI #DataManagement #InformationManagement #DataQuality #DataGovernance #DataInsights #DataAnalytics #DataOptimization #DataStrategy

📣 Our 2024 DataIQ 100 Summit USA was action-packed with thought leadership from top leaders across the #data and #analytics community. That said, there are far too many people to thank on this post, but you know who you are, and we couldn't have done this without you! 📅 I highly recommend you make plans to attend in 2025 because this event is only going to get better. For those who couldn't make it, take a look at the article below for some insight into the conversations that took place! 💡 A key insight that resonated with me was a comment shared by several attendees: 'No matter the size of our organizations, the industry we're in, or our level of maturity, we're all tackling the same initiatives with slightly different "flavors." This begs the question: Why reinvent the wheel when you can tap into the wealth of knowledge and experience your peers bring to the table?! Don't hesitate to get in touch with me if you have any questions about the event or DataIQ in general. #dataiq #dataiq100 #dataiq100summit #ai

💡 AI Revolution – Essential insights from the DataIQ 100 Summit At the 2024 #DataIQ100 Summit, data leaders shared their experiences driving an #AI revolution and how they devised strategies and approaches to integrate AI tools into their organisations. Diana Hoskins Schildhouse, Chief Analytics and Insights Officer, Colgate-Palmolive, at the DataIQ 100 Summit, discussed her four-part strategy for leading the AI revolution: 🔹 A business-first approach Taking a business-first approach offers numerous advantages for data leaders and organisations. These include prioritising customers, gaining first-mover advantages by executing strategies ahead of competitors, and focusing investments and commercial decisions for financial benefits. 🔹 Communicating a vision through a concise strategy Clear communication of a vision is essential. A #data vision needs to be set in motion and this can be done in different ways depending on the size, legacy and ambitions of the organisation, so careful consideration is needed from the data team. 🔹 The promotion of data literacy Schildhouse emphasised at the DataIQ 100 Summit that promoting data literacy is vital. It's an ongoing effort for businesses, requiring inclusive approaches such as avoiding jargon and simplifying information. This enhances engagement, adoption, and fosters the growth of data literacy and culture across the organisation. 🔹 Creating value Creating value involves articulating the impact of your work internally and focusing on priority areas to achieve goals. It's crucial for data leaders to emphasise that value creation doesn't happen automatically with data; they must start with questions as to how value needs to be created in the business and then leverage data effectively. 🔎 Learn more about Diana's four part strategy here: https://lnkd.in/ewvKGGc6

For those interested - An Executive Summary of our Data & AI Summit is below. I found Monte Carlo's & Alation's summaries helpful as well and will link those in the comments. --- With nearly 16K attendees and an amazing line-up of keynote speakers, this year’s #DataAISummit featured a variety of product announcements, innovations, and insights. Check out this recap of the Executive Forum talks and the newest Databricks innovations!