The UK Ministry of Defence (MOD) oversees the lifecycle management of over 120,000 assets.
Previous reliance on Excel-based models and manual processing limited team collaboration and the development of predictive capabilities. Utilising SAS Viya, Defence Infrastructure Organisation (DIO) transitioned to AI-driven simulation models, enabling predictive and prescriptive analytics to optimise asset management. Now recognised as an advanced asset management model in government, hear how DIO have demonstrated data-driven decision-making, and advanced analytical capabilities across government.
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Data and analytics leaders and their data engineering teams are tasked with evaluating and selecting data integration tools. However, there are many options, which can be confusing. This session will explain the various types of data integration tools and technologies available in the market, and help you select the right data integration tool for your needs.
Urgent Investments in data, analytics and AI use cases has put the spotlight once more on strong data management foundations. Is our Data even Ready for upcoming AI, analytics and data sharing initiatives is now top of mindshare for heads of data, CDAOs and their counterparts. Data Fabrics have emerged as a long term, foundational data management architecture that you should now pursue for sustained D&A success. This session will:
1. Help understand what data Fabrics are and what they mean for your data strategy and architecture
2. Help decide how to build and where to buy
3. Navigate the vendor landscape to assist in tech procurement decisions to aid your fabric journey
Successful data and analytics strategies today are business-centric, focused on achieving tangible and measurable business outcomes. This session will discuss the anatomy of an effective data and analytics strategy that enables organizations to thrive in today’s highly challenging and dynamic business environments.
Analytics and Business Intelligence (ABI) Platforms are being transformed by AI. Data insights are more likely to be discovered by machine learning. Natural language generation will turn dashboards into data stories. Natural language query will make data more accessible. This session will show how ABI Platform vendors are incorporating AI and how analytic leaders can manage the additional cost and risk these trends will bring.
Heads of analytics & AI face many challenges such as keeping afloat, staying the course or racing ahead in the race for AI superiority. This session will focus on the top fears, risks, objections and hurdles leaders of Analytics & AI face and most importantly, how to handle them.
This very popular workshop shares the latest toolkit which can be used to diagnostically connect data, analytics, governance and their impact on business processes, decisions and outcomes.
D&A leaders and teams are at an AI-driven inflection point. They are crucial to enable business value through AI-readiness but must evolve their strategy and operating model to meet their organization’s AI ambitions. Reporting from the Gartner 2025 CDAO Agenda Survey, this session reveals actions successful D&A leaders have taken to deliver business outcomes from AI, data, and analytics, and what they need to do next year.
With high D&A ambitions and AI pilots becoming increasingly ubiquitous, focus is shifting toward consistent execution. We will share how to continue innovating and experimenting while scaling success. In this keynote, Gartner’s perspective will guide you on preparing for the expected and adapting to the unexpected. Learn to enhance your D&A and AI capabilities on the path to success.
In this episode, Tristan Handy and Lukas Schulte, co-founder of SDF Labs and now part of dbt Labs, dive deep into the world of compilers—what they are, how they work, and what they mean for the data ecosystem. SDF, recently acquired by dbt Labs, builds a world-class SQL compiler aimed at abstracting away the complexity of warehouse-specific SQL. Join Tristan and members of the SDF team at the dbt Launch showcase to learn more about the brand new dbt engine. Register at https://www.getdbt.com/resources/webinars/2025-dbt-cloud-launch-showcase For full show notes and to read 8+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.
Will generative artificial intelligence lead to nirvana or dystopia? Great question, which we don’t exactly answer in this week’s podcast, but we do weigh the most critical downstream effects of the technology based on recent research done by urban economists Frank Levy and Scott Abrahams. We assess how GenAI impacts the benefits of a college degree, the nation’s political dynamics, and which metro area economies will win (think Savannah) and lose (think San Francisco). Guests: Frank Levy, Visitor in the Strategy Group of the Fuqua School of Business, Duke University, and Scott Abrahams, Professor of Economics at Louisiana State University Read Frank and Scott's recent research on Gen AI here: From San Francisco to Savannah? The Downstream Effects of Generative AI (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4874104) Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Follow Mark Zandi on 'X', BlueSky or LinkedIn @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn
Questions or Comments, please email us at [email protected]. We would love to hear from you. To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.
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Data science isn't just about models and code—it's about people, connections, and shared knowledge. From online forums to in-person hackathons, communities play a crucial role in shaping careers and innovations. In this episode, we're joined by Yujian Tang — an expert in building and fostering data-driven communities — to discuss how these spaces can help you grow and why developer advocacy is a great role for people passionate about both building and fostering community. Whether you're looking to expand your network, break into data science, or grow your own community, this episode is packed with actionable insights from someone who has done it all. What You'll Learn: How getting involved in different communities can accelerate your career and open up unexpected opportunities The key differences between various data communities and how to find the right fit What it takes to build and nurture a thriving community of your own The evolving role of the Developer Advocate in growing data product visibility through community. Register for free to be part of the next live session: https://bit.ly/3XB3A8b Interested in learning more about GenAI? 👉 https://lu.ma/oss4ai Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter
If you're thinking about doing the Google Data Analytics Certificate, you need to hear this: DON'T. In this episode, I list five reasons why it is a waste of time. The ONLY Framework to Become a Data Analyst in 2025 (SPN Method): https://youtu.be/XUxWQgh3soo?si=v3SQV3zJ4h0jH1uQ 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator ⌚ TIMESTAMPS 00:00 - Introduction 00:11 - Reason 1: Certificates Don't Matter in the Data Industry 02:45 - Reason 2: The Course Teaches the Wrong Skills 06:32 - Reason 3: The Course is Slow and Theoretical 09:21 - Reason 4: Lack of Projects and Portfolios 14:15 - Reason 5: No Career or Networking Support 🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com/ Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
Summary In this episode of the Data Engineering Podcast Sida Shen, product manager at CelerData, talks about StarRocks, a high-performance analytical database. Sida discusses the inception of StarRocks, which was forked from Apache Doris in 2020 and evolved into a high-performance Lakehouse query engine. He explains the architectural design of StarRocks, highlighting its capabilities in handling high concurrency and low latency queries, and its integration with open table formats like Apache Iceberg, Delta Lake, and Apache Hudi. Sida also discusses how StarRocks differentiates itself from other query engines by supporting on-the-fly joins and eliminating the need for denormalization pipelines, and shares insights into its use cases, such as customer-facing analytics and real-time data processing, as well as future directions for the platform.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data managementData migrations are brutal. They drag on for months—sometimes years—burning through resources and crushing team morale. Datafold's AI-powered Migration Agent changes all that. Their unique combination of AI code translation and automated data validation has helped companies complete migrations up to 10 times faster than manual approaches. And they're so confident in their solution, they'll actually guarantee your timeline in writing. Ready to turn your year-long migration into weeks? Visit dataengineeringpodcast.com/datafold today for the details.Your host is Tobias Macey and today I'm interviewing Sida Shen about StarRocks, a high performance analytical database supporting shared nothing and shared data patternsInterview IntroductionHow did you get involved in the area of data management?Can you describe what StarRocks is and the story behind it?There are numerous analytical databases on the market. What are the attributes of StarRocks that differentiate it from other options?Can you describe the architecture of StarRocks?What are the "-ilities" that are foundational to the design of the system?How have the design and focus of the project evolved since it was first created?What are the tradeoffs involved in separating the communication layer from the data layers?The tiered architecture enables the shared nothing and shared data behaviors, which allows for the implementation of lakehouse patterns. What are some of the patterns that are possible due to the single interface/dual pattern nature of StarRocks?The shared data implementation has cacheing built in to accelerate interaction with datasets. What are some of the limitations/edge cases that operators and consumers should be aware of?StarRocks supports management of lakehouse tables (Iceberg, Delta, Hudi, etc.), which overlaps with use cases for Trino/Presto/Dremio/etc. What are the cases where StarRocks acts as a replacement for those systems vs. a supplement to them?The other major category of engines that StarRocks overlaps with is OLAP databases (e.g. Clickhouse, Firebolt, etc.). Why might someone use StarRocks in addition to or in place of those techologies?We would be remiss if we ignored the dominating trend of AI and the systems that support it. What is the role of StarRocks in the context of an AI application?What are the most interesting, innovative, or unexpected ways that you have seen StarRocks used?What are the most interesting, unexpected, or challenging lessons that you have learned while working on StarRocks?When is StarRocks the wrong choice?What do you have planned for the future of StarRocks?Contact Info LinkedInParting Question From your perspective, what is the biggest gap in the tooling or technology for data management today?Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The AI Engineering Podcast is your guide to the fast-moving world of building AI systems.Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.If you've learned something or tried out a project from the show then tell us about it! Email [email protected] with your story.Links StarRocksCelerDataApache DorisSIMD == Single Instruction Multiple DataApache IcebergClickHousePodcast EpisodeDruidFireboltPodcast EpisodeSnowflakeBigQueryTrinoDatabricksDremioData LakehouseDelta LakeApache HiveC++Cost-Based OptimizerIceberg Summit Tencent Games PresentationApache PaimonLancePodcast EpisodeDelta UniformApache ArrowStarRocks Python UDFDebeziumPodcast EpisodeThe intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
Apache Kafka, start to finish. Apache Kafka in Action: From basics to production guides you through the concepts and skills you’ll need to deploy and administer Kafka for data pipelines, event-driven applications, and other systems that process data streams from multiple sources. Authors Anatoly Zelenin and Alexander Kropp have spent years using Kafka in real-world production environments. In this guide, they reveal their hard-won expert insights to help you avoid common Kafka pitfalls and challenges. Inside Apache Kafka in Action you’ll discover: Apache Kafka from the ground up Achieving reliability and performance Troubleshooting Kafka systems Operations, governance, and monitoring Kafka use cases, patterns, and anti-patterns Clear, concise, and practical, Apache Kafka in Action is written for IT operators, software engineers, and IT architects working with Kafka every day. Chapter by chapter, it guides you through the skills you need to deliver and maintain reliable and fault-tolerant data-driven applications. About the Technology Apache Kafka is the gold standard streaming data platform for real-time analytics, event sourcing, and stream processing. Acting as a central hub for distributed data, it enables seamless flow between producers and consumers via a publish-subscribe model. Kafka easily handles millions of events per second, and its rock-solid design ensures high fault tolerance and smooth scalability. About the Book Apache Kafka in Action is a practical guide for IT professionals who are integrating Kafka into data-intensive applications and infrastructures. The book covers everything from Kafka fundamentals to advanced operations, with interesting visuals and real-world examples. Readers will learn to set up Kafka clusters, produce and consume messages, handle real-time streaming, and integrate Kafka into enterprise systems. This easy-to-follow book emphasizes building reliable Kafka applications and taking advantage of its distributed architecture for scalability and resilience. What's Inside Master Kafka’s distributed streaming capabilities Implement real-time data solutions Integrate Kafka into enterprise environments Build and manage Kafka applications Achieve fault tolerance and scalability About the Reader For IT operators, software architects and developers. No experience with Kafka required. About the Authors Anatoly Zelenin is a Kafka expert known for workshops across Europe, especially in banking and manufacturing. Alexander Kropp specializes in Kafka and Kubernetes, contributing to cloud platform design and monitoring. Quotes A great introduction. Even experienced users will go back to it again and again. - Jakub Scholz, Red Hat Approachable, practical, well-illustrated, and easy to follow. A must-read. - Olena Kutsenko, Confluent A zero to hero journey to understanding and using Kafka! - Anthony Nandaa, Microsoft Thoughtfully explores a wide range of topics. A wealth of valuable information seamlessly presented and easily accessible. - Olena Babenko, Aiven Oy
Moody’s Analytics colleague Dante DeAntonio joins the podcast to recap the April jobs report, along with the potpourri of other economic data released this week. Marisa dives into other labor market data, Cris tackles GDP, and Mark discusses consumer confidence. All along the way, Mark points out the thorns in recent data. The team also provides an update on their recession probabilities. Hosts: Mark Zandi – Chief Economist, Moody’s Analytics, Cris deRitis – Deputy Chief Economist, Moody’s Analytics, Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody’s Analytics Guest: Dante DeAntonio - Senior Director of Economic Research Follow Mark Zandi on 'X', BlueSky or LinkedIn @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn
Questions or Comments, please email us at [email protected]. We would love to hear from you. To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.
Agentic AI is here, but what is it? What are the differences between the traditional LLMs and this new agentic AI we're hearing about? With AI systems making autonomous decisions, driving analytics, and reshaping data strategies, what does this mean for analysts? We're joined by Vin Vashishta, CEO at V Squared and an expert in AI strategy and data science. Vin's book, From Data to Profit, lays out a roadmap for turning AI and analytics into real business value. AI isn't just a tool anymore; it's becoming a collaborator. How should we think about adapting? Don't miss his insights in this show! What You'll Learn: How Agentic AI will redefine the role of analysts in analytics. What makes an AI 'agent' different from a traditional LLM? Why knowledge graphs are the key to AI's next leap forward. How to future-proof your career in analytics. Register for free to be part of the next live session: https://bit.ly/3XB3A8b Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter
In this episode of Hub & Spoken, Jason Foster, CEO of Cynozure, goes solo and explores one of the most critical yet under-discussed business skills...decision making. Drawing on real-world examples, research, and personal experience, Jason unpacks why so many organisations struggle to make effective decisions, despite it being core to leadership, innovation, and progress. From decision paralysis to overconfidence, and data overload to gut instinct, he looks at the formal frameworks and informal dynamics that shape how choices are made across all levels of a business. The episode delves into the role of vision, bias, data literacy, and emotional intelligence, and outlines the essential skills leaders need to build confidence, clarity and adaptability into their decision-making culture. Whether you're leading a team, shaping strategy, or navigating change, this episode is packed with practical ideas to help you make better, faster, and more informed decisions. 🎧 Tune in now to rethink how decisions really get made, and how to make yours count. ***** Cynozure is a leading data, analytics and AI company that helps organisations to reach their data potential. It works with clients on data and AI strategy, data management, data architecture and engineering, analytics and AI, data culture and literacy, and data leadership. The company was named one of The Sunday Times' fastest-growing private companies in both 2022 and 2023 and recognised as The Best Place to Work in Data by DataIQ in 2023 and 2024. Cynozure is a certified B Corporation.
🎯 I analyzed 2,893 data analyst job postings so you don’t have to, and here’s what I found: You might be wasting your time learning the wrong skills. Find out how to pivot your career the data-driven way and stay ahead of the game. 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator ⌚ TIMESTAMPS 02:28 - FindADataJob.com. 04:04 - Most In-demand skills in 2025. 06:22 - Live Data at DataAnalystSkills.com 🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com/ Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
Become data-savvy with the widely used data and AI software Data and analytics are essential for any business, giving insight into what's working, what can be improved, and what else needs to be done. SAS software helps you make sure you're doing data right, with a host of data management, reporting, and analysis tools. SAS For Dummies teaches you the essentials, helping you navigate this statistical software and turn information into value. In this book, learn how to gather data, create reports, and analyze results. You'll also discover how SAS machine learning and AI can help deliver decisions based on data. Even if you're brand new to data and analytics, this easy-to-follow guide will turn you into an SAS power user. Become familiar with the most popular SAS applications, including SAS 9 and SAS Viya Connect to data, organize your information, and adopt sound data security practices Get a primer on working with data sets, variables, and statistical analysis Explore and analyze data through SAS programming and rich application interfaces Create and share graphs interactive visualizations to deliver insights This is the perfect Dummies guide for new SAS users looking to improve their skills—in any industry and for any organization size.