Data Masters Podcast

The future of data-driven organizations depends on context, not just models. We’re joined by Sastry Durvasula, Chief Operating, Information and  Digital Officer of TIAA, to explore how a century-old institution is transforming operations, client experiences and services with next-generation technology. Sastry shares how TIAA balances innovation with responsibility, leveraging vast datasets and AI to solve complex problems at scale while protecting vulnerable clients. He highlights strategies for embedding empathy in customer interactions, improving data quality and building a “workforce of the future” where humans and machines collaborate seamlessly.Key Takeaways:00:00 Introduction.03:09 TIAA manages vast data across retirement, wealth and asset management.08:00 AI strategy rests on four pillars: tech, client experience, operations, and services.16:10 Human service agents handle complex participant needs with AI support.21:42 Operating officers must blend operational expertise with AI and technology.25:13 AI solutions help protect older adults from fraud and cognitive decline risks.30:25 Complaints come through every channel and require timely resolution.34:56 Beyond semantics, the real focus is on building the workforce of the future with AI.38:55 AI agents shift economies by changing how consumers shop and services operate.Resources Mentioned:Sastry Durvasulahttps://www.linkedin.com/in/durvasula/TIAA | LinkedInhttps://www.linkedin.com/company/tiaa/TIAA | Websitehttps://www.tiaa.org/publicTIAA Institute Researchhttps://www.tiaa.org/public/instituteThanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

A traditional energy company is rewriting its future with data, AI and a customer-first mindset. We’re joined by Dak Liyanearachchi, Executive Vice President and Chief Technology Officer of NRG Energy, to explore how one of America’s largest energy companies is redefining its identity as a tech-forward, customer-centric organization. Dak shares how NRG is connecting the entire energy value chain — from generation to smart home consumption — through data and AI innovation. We also discuss the broader implications of grid efficiency, AI-driven forecasting and the cultural change required to power true digital transformation.Key Takeaways:(03:04) NRG spans energy generation to smart home energy use across deregulated markets.(07:05) Transforming the customer experience starts with managing home energy at the last mile.(09:48) Smart energy usage requires intelligent management of consumption and generation.(10:49) Data enables personalized insights to help customers choose the right energy plan.(14:24) A forecasting model simulates usage and market data to guide five-year energy planning.(20:00) GenAI boosts productivity and improves customer engagement through automated support.(25:02) The challenge isn’t adopting GenAI — it’s clearly defining what to do with it.(28:57) Ongoing transformation is fueled by a tech-first mindset and a focus on delivering value.Resources Mentioned:Dak Liyanearachchihttps://www.linkedin.com/in/dak-liyanearachchi-0664381/NRG Energy | LinkedInhttps://www.linkedin.com/company/nrgenergy/NRG Energy | Websitehttps://www.nrg.com/Renew Homehttps://www.renewhome.com/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

AI is everywhere, but what does meaningful adoption actually look like in marketing? We’re joined by Lillian Pierson, Fractional CMO and Growth Advisor of Data-Mania, to unpack how organizations can use AI strategically to drive results. Lillian outlines practical examples and a maturity model for AI in marketing, helping teams align tech with business outcomes. She breaks down where AI delivers the most value — from low-risk productivity tools to fully automated, cross-functional workflows — and offers guidance on the metrics that matter, how to tackle data fragmentation and why upskilling is critical for growth. Key Takeaways:00:00 Introduction02:53 AI shifts marketing from manual campaigns to real-time systems.05:29 Marketing success with AI depends more on strong data foundations than flashy tools.10:41 The bigger the AI investment, the more strategic de-risking it needs.15:59 Humanic uses AI to find hidden user segments from behavioral data.19:57 Marketing issues often stem from data silos and fragmentation.22:22 Without a data layer, ad algorithms can’t optimize or validate market fit.26:27 AI bridges marketing and tech through vibe coding and automation.30:29 Try vibe coding tools — you’ll be surprised what you can build.Resources Mentioned:Lillian Piersonhttps://www.linkedin.com/in/lillianpierson/Data-Mania | LinkedInhttps://www.linkedin.com/company/data-mania/Data-Mania | Websitehttps://www.data-mania.com/Cursorhttps://cursor.com/Windsurfhttps://windsurf.com/editorHumanichttps://www.humanic.com/Growth Solutionshttps://growthsolutions.in/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

AI can mimic human language, but does that make it intelligent? We’re joined by Ozair Ali, Co-Founder of ekai, to unpack what it truly takes to turn cutting-edge AI into real-world solutions. Drawing on his global experience in startups, government and academia, Ozair brings unique insight into the limitations and possibilities of LLMs in the enterprise. He walks us through the practical UX challenges of working with LLMs, the statistical roots of modern AI and what makes an interface more than just a chat window. Key Takeaways:(02:56) AI terms often come from engineering, causing common confusion.(05:57) Like the brain, LLMs show emergent behavior that’s hard to explain.(09:00) LLMs mimic human speech but lack calibration.(16:11) RAGs aren’t the first step — cheaper, simpler methods often get the same results.(20:07) It’s mind-blowing that chat is still the default AI interface, as something better must exist.(25:18) Non-technical users can build fast, blurring the line between data and software engineers.(31:00) LLMs favor data-rich giants, but there’s hope for new disruptors to emerge.(32:49) AI can unlock opportunities globally despite local infrastructure challenges.Resources Mentioned:Ozair Alihttps://www.linkedin.com/in/ozairali/ekai | LinkedInhttps://www.linkedin.com/company/ekaiai/ekai | Websitehttps://www.ekai.ai/Conway’s Game of Lifehttps://playgameoflife.com/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Most data teams focus on building assets — only a few focus on making them useful. Manav Misra, Chief Data and Analytics Officer of  Regions Bank, explores what it takes to make data genuinely useful in a complex enterprise. Manav shares lessons from academia, startups and enterprise leadership, walking us through how he applies a product mindset to drive real impact with data in the banking sector. Key Takeaways:(02:25) Falling in love with AI led Manav from engineering to academia and beyond.(06:16) Startups offer a faster learning curve for early career professionals.(10:02) Start with the customer problem and keep solutions as simple as possible.(15:04) A data product must be usable, measurable and deliver real impact.(19:49) Manav added “analytics” to his title to highlight a focus on business impact.(23:03) Data product partners bridge tech teams and business users to deliver real value.(26:19) Starting from consumption ensures governance efforts stay focused and impactful.(28:28) Federated governance builds ownership and relevance across teams.Resources Mentioned:Manav Misrahttps://www.linkedin.com/in/manavmisra/Regions Bank | Websitehttps://www.linkedin.com/company/regions-financial-corporation/Regions Bank | Websitehttps://www.regions.com/Colorado School of Mineshttps://www.mines.edu/The opinions expressed in the presentation are statements of the speaker’s opinion, are intended only for informational purposes, and are not formal opinions of, nor binding on Regions Bank, its parent company, Regions Financial Corporation and their subsidiaries, and any representation to the contrary is expressly disclaimed.Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Security isn’t just a checkbox — it’s the foundation of trustworthy data analytics. Oren Falkowitz, Advisor at Gigasheet, joins us to explore what it really takes to secure data in the digital era. With a background spanning NSA, US Cyber Command, Amazon and Cloudflare, Oren brings a deep understanding of how to strike a balance between access and protection, especially as analytics demands grow. He explains why most companies fail to define what they need to protect, why phishing remains a top vulnerability and how treating security as a technology — not just a human — problem changes the game. Key Takeaways:(03:24) Government and private sector data security face similar foundational challenges.(06:08) User training alone won’t stop phishing — it’s like expecting drivers not to text.(10:29) Apache Accumulo shows cell-level controls matter more than having all the data.(18:50) Intelligence turns technical data into real decisions.(24:42) LLMs need rich, licensed data — scraping alone isn’t enough.(27:59) Cyberattacks work because they look real, visually or organizationally authentic.(31:03) Security improves by mastering the basics, not chasing the newest trend.(32:43) Strong analytics matter more than the breach itself when it comes to security impact.Resources Mentioned:Oren Falkowitzhttps://www.linkedin.com/in/orenjfalkowitz/Gigasheet | LinkedInhttps://www.linkedin.com/company/gigasheet/Gigasheet | Websitehttps://gigasheet.com/Apache Accumulohttps://accumulo.apache.org/Cloudflarehttps://www.cloudflare.com/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Data doesn’t just reflect communities — it can help shape more inclusive, constructive conversations. We’re joined by Russell Stevens, Head of Strategy and Development at the MIT Center for Constructive Communication, to explore how qualitative data, storytelling and ethical AI design can bridge gaps in society and decision-making. Russell shares how his team moved beyond traditional media analytics to build a platform that amplifies unheard voices through small-group conversations. He explains why trust, local context and human-in-the-loop sense-making are critical for turning narratives into actionable insight.Key Takeaways:(03:50) MIT used early language models to analyze media data and gauge public opinion.(09:27) Ingesting more data only amplified the loudest voices, not diverse perspectives.(18:31) Peer-led talks in Newark schools revealed stories that would never be revealed to adults.(24:55) Like Tamr, the process uses humans to guide AI through iterative coding.(30:40) Radical transparency and consent are core to ethical data use.(37:07) Hearing humanity in others is essential to overcoming division.(41:32) Replacing people with AI personas is a rejected dystopian shortcut.(43:12) Without humanity, all you’re left with is empty thematic summaries.Resources Mentioned:Russell Stevenshttps://www.linkedin.com/in/russell5mit/MIT Center for Constructive Communication | LinkedInhttps://www.linkedin.com/company/cccatmit/MIT Center for Constructive Communication | Websitehttps://www.ccc.mit.edu/Corticohttps://cortico.ai/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Data is the backbone of every great brand, but for Margaritaville, it’s also the bridge to a lifestyle of laid-back escapes and unforgettable memories. Claudia Infante, Chief Data Officer of Margaritaville, joins us to explore how this iconic brand blends data-driven decisions with the spirit of escapism. Claudia shares insights into the company’s unique licensing model, their approach to data governance, and how they prioritize customer experience while managing diverse data sources.Key Takeaways:(02:12) Margaritaville grew from a song to a lifestyle brand, starting with a t-shirt shop in Key West.(06:26) Hotels handle more complex customer and operational data than restaurants.(11:56) Margaritaville is an emotion, creating deep connections and lasting memories.(17:27) Strong brands build community and connections beyond just products.(20:43) Intentional data collection focuses on purpose and meaningful use over hoarding.(27:03) Clear data purpose reduces risk and aligns with business goals.(31:23) Marketing focuses on storytelling and letting customers engage on their terms.(37:36) Margaritaville offers diverse experiences, letting customers choose their own path.Resources Mentioned:Claudia Infantehttps://www.linkedin.com/in/claudiainfante/Margaritaville | LinkedInhttps://www.linkedin.com/company/margaritaville/Margaritaville | Websitehttps://www.margaritaville.com/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

AI isn’t magic — it’s science powered by quality data. Dr. Stephanie Lahr, Chief Experience Officer of Artisight, sits down with us to explain how data, computer vision and ambient sensors are transforming patient care. She reveals how Artisight helps clinicians reclaim time by automating documentation, improving the quality of data and restoring focus to human connection. Stephanie also shares her journey from internal medicine physician to healthcare technology leader, emphasizing that reducing burnout and elevating care begins with smarter data collection. Key Takeaways:(03:04) Stephanie’s journey from clinician to digital health leader started with a hurricane and an EMR revelation.(08:38) Even in the time of Hippocrates, medicine has always relied on data through observation and testing.(12:08) In healthcare, patient care comes first — data entry comes second.(17:40) Computer vision captures real-time patient data without burdening clinicians.(21:30) Virtual care uses real-time support without recording or storing sensitive data.(27:39) High-quality insights depend on high-quality data — it’s a continuous cycle.(31:20) AI success in healthcare requires collaboration between clinicians, data scientists and system leaders.(34:41) Precision medicine improves treatment, but restoring humanity to care is what truly drives innovation.Resources Mentioned:Dr. Stephanie Lahrhttps://www.linkedin.com/in/stephanie-lahr-md-chcio-767b916/Artisight | LinkedInhttps://www.linkedin.com/company/artisight/Artisight | Websitehttps://artisight.com/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Real-time data from the factory floor is becoming a powerful driver of operational efficiency and competitive advantage. We’re joined by Tom Ferrucci, Chief Information Officer of Natco Home Group, to unpack how data is transforming the manufacturing floor. With over 30 years of experience in IT and digital transformation, Tom shares how manufacturing processes are not just supported by data but are actively producing it, offering new insights into efficiency, automation and supply chain resilience.Key Takeaways:(02:26) The manufacturing floor holds valuable data that drives cost savings and efficiency gains.(06:37) Real-time telemetry from machines replaces outdated manual tracking and offers deeper insights.(07:46) RFID tags, originally for compliance, are now enhancing internal visibility in warehousing operations.(10:17) Automated systems use sensor data to reduce scrap, speed up repairs and trigger maintenance workflows.(11:37) Linking data to key metrics such as mean time to repair helps drive operational improvements.(15:47) Applying data-driven strategies to the supply chain helps improve predictability in a volatile environment.(21:00) Strong data governance and classification ensure fast-moving insights stay accurate and reliable.(22:18) Manufacturing is data-rich and full of untapped potential when fully leveraged.Resources Mentioned:Tom Ferruccihttps://www.linkedin.com/in/tomferrucci/Natco Home Group | LinkedInhttps://www.linkedin.com/company/natco-home-products/Natco Home Group | Websitehttps://www.natcohome.com/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

What if the truth was buried in a sea of misinformation and it was your job to find it? Paul Smith, Chief Information Officer of Amnesty International, joins us to explore how unstructured data drives advocacy in the fight for global human rights. Paul highlights the ethical and operational complexities of data in the nonprofit world, making this a must-listen for anyone navigating data integrity in high-stakes environments.Key Takeaways:(03:16) Unstructured data is key to documenting human rights abuses.(06:43) Amnesty International verifies data using reverse image search, metadata and cross-referencing.(12:34) SharePoint and Preservica help manage, archive and access multilingual data.(16:35) AI adds speed and scale across Amnesty International’s research and evidence processes.(20:21) Generative adversarial networks help mitigate AI risks like bias and censorship.(24:18) Nonprofits need to guide people, from learning about the cause to becoming advocates.(28:33) The future of advocacy depends on AI, crowdsourcing and protecting privacy.(30:13) The flood of false information is an important area to watch out for in advocacy efforts.Resources Mentioned:Paul Smithhttps://www.linkedin.com/in/pdsmithmba/Amnesty Internationalhttps://www.linkedin.com/company/amnesty-international/Preservicahttps://preservica.com/Microsoft Sentinelhttps://azure.microsoft.com/en-us/products/microsoft-sentinel/Microsoft Defenderhttps://www.microsoft.com/en-us/microsoft-365/microsoft-defender-for-individualsSharePointhttps://www.microsoft.com/en/microsoft-365/sharepoint/collaborationThanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Gut instinct alone isn’t enough in construction — data is now a game-changer. Annette Cooper, Director of Data and Analytics at Graham, sits down with us to explore how data is transforming the construction industry. She explains how Graham leverages analytics to manage risk, optimize efficiency and improve project execution. Annette emphasizes that success comes from solving real business problems rather than simply generating reports.Key Takeaways:(03:17) Graham is expanding rapidly through acquisitions, creating new data challenges.(04:05) Risk management is a priority in an industry with long project timelines and tight margins.(07:26) Many project managers are eager for data insights but lack access to the right tools.(09:05) A standardized data strategy is essential for integrating multiple systems post-acquisition.(12:45) Project estimations require a balance of historical data and real-world unpredictability.(17:22) Effective data teams focus on solving problems, not just collecting data.(20:01) Data should drive decisions, not just generate reports that frustrate users.(25:42) Predictive models can highlight risks early, but human expertise remains crucial.(31:55) The future of AI in construction lies in automating insights, not replacing workers.(35:10) AI can streamline building code compliance by identifying design issues before construction begins.Resources Mentioned:Annette Cooperhttps://www.linkedin.com/in/annette-cooper-2aa442bb/Graham | LinkedInhttps://www.linkedin.com/company/grahambuilds/Graham | Websitehttps://www.grahambuilds.com/New Zealand Ministry of Business, Innovation & Employmenthttps://www.mbie.govt.nz/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Joetta Gobell, Senior VP of Data Strategy and Insights at Dotdash Meredith, joins us to discuss strategies for reaching consumers in their moment of need. She explains how Dotdash Meredith leverages its vast network of brands to provide timely, relevant content. She highlights how D/Cipher helps advertisers connect with audiences based on their content interactions rather than invasive data collection. She emphasizes prioritizing user experience over ad revenue to ensure advertising enhances rather than disrupts content engagement.Key Takeaways:(02:31) Leveraging the power of brands to help people in their moment of need.(04:14) Joetta’s background in math, psychology, and cognitive science shapes her approach to data.(06:09) Publishing has constantly evolved, requiring adaptability.(08:58) Human needs haven’t changed — only the way we deliver information.(10:28) Prioritizing user experience leads to better long-term success.(14:07) Targeting needs and behavior is more effective than using user data.(19:25) Data is not the only source of insight — context is more powerful than identity-based targeting.(24:50) Balancing AI and human teams by understanding each other’s strengths and weaknesses.(31:05) Understanding content meaning is key to effective advertising.(40:26) Interpreting data is more valuable than simply collecting it.Resources Mentioned:Joetta Gobell -https://www.linkedin.com/in/joetta-gobell-9378832/Dotdash Meredith | LinkedIn -https://www.linkedin.com/company/dotdashmeredith/Dotdash Meredith | Website -https://www.dotdashmeredith.com/D/Cipher by Dotdash Meredith -https://www.dotdashmeredith.com/advertisingThanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Scott Taylor, “The Data Whisperer” and Principal Consultant of MetaMeta Consulting, shares techniques for communicating the value of data in a business context. He emphasizes simplifying complex data concepts to align with business goals, advocating for clear communication, the avoidance of technical jargon and the use of relatable analogies. From practical strategies for engaging C-suite leaders to insights on navigating AI-driven challenges, Scott offers actionable advice for data practitioners looking to bridge the gap between technical expertise and business outcomes.Key Takeaways:(03:24) Two types of data storytelling: one for analytics and one for data management.(05:30) Truth in data must come before deriving meaning from it.(08:10) Avoid buzzwords and focus on vocabulary the business understands.(12:21) Listen to earnings calls or strategy meetings to learn your company’s objectives.(17:23) Master data is foundational to delivering business value at scale.(22:17) Use industry-specific analogies to clarify data’s impact.(26:42) Poor data management can amplify errors in AI-driven systems.(28:04) Master data challenges exist in every industry and era.(33:19) Developing storytelling skills is essential for career growth.Resources Mentioned:Scott Taylor -https://www.linkedin.com/in/scottmztaylor/MetaMeta Consulting -https://www.linkedin.com/company/metametaconsulting/"Telling Your Data Story" by Scott Taylor -https://www.metametaconsulting.com/the-bookThanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Natarajan Subbiah, Chief Product Officer of Uber Freight, joins us to discuss how data science is reshaping the logistics industry. He explains Uber Freight’s innovative approach to optimizing supply chains by combining human expertise, digitalized workflows and large language models to automate pricing, load tracking and delivery management. Natarajan also shares insights on balancing centralized and decentralized teams, the role of data in ensuring marketplace liquidity and strategies for building high-performing, collaborative teams.Key Takeaways:(02:30) Marketplaces thrive on data to balance supply and demand efficiently.(03:30) Uber Freight”s introduction of upfront pricing to simplify logistics.(07:20) Liquidity is the key metric for marketplace success.(07:35) The easiest way to grow a marketplace is to constrain it on multiple dimensions. (12:10) 80 to 90% of complete goods or supply parts for goods get moved on trucks.(17:22) What scaling automatization means for the freight industry.(22:14) Over time, about 80% of freight will be moved in a highly automated way. (26:59) Centralized vs de-centralized teams, pros and cons.Resources Mentioned:Natarajan Subbiah -https://www.linkedin.com/in/natarajan-subbiah-b82ba3a/Uber Freight | LinkedIn -https://www.linkedin.com/company/uber-com/Uber Freight | Website -https://www.uberfreight.com/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

On this episode, we are joined by Will LaForest, Global Field CTO of Confluent, to discuss the transformative impact of data streaming on businesses and platforms. He explains the shift from traditional monolithic big data models to data streaming systems, moving from data analysis to continuously bringing new data to the same questions, enabling hyper-personalized customer experiences and operational efficiency.Key Takeaways:(02:59) Will’s early career sparked a passion for large-scale data systems.(05:25) Data streaming shifts the paradigm by delivering a constant stream of data to the questions.(08:23) Data streaming helps decouple data producers and deliver data to the consumers in real time.(17:05) Real-time data streams are used across multiple industries, including financial services and cybersecurity.(19:36) Ride-sharing exemplifies the indispensable role of data streaming.(22:49) Reliability, decoupling and speed are some of the reasons data streaming has taken off.(27:00) Streaming supports hyper-personalized experiences.(39:36) Confluent simplifies streaming adoption for businesses of all sizes.Resources Mentioned:Will LaForest -https://www.linkedin.com/in/willlaforest/Confluent | LinkedIn- https://www.linkedin.com/company/confluent/Confluent Platform - https://www.confluent.io/“Data Mesh” by Zhamak Dehghani -https://www.thoughtworks.com/insights/books/data-meshApache Kafka -https://kafka.apache.org/Apache Flink -https://kafka.apache.org/MongoDB -https://www.mongodb.com/Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

Rouzbeh Gerami, Senior Vice President of Data Science at Nielsen, joins us on this episode to discuss the complexities of measuring audiences and defining their characteristics across diverse media and platforms. He explains how the shift toward digital privacy impacts audience measurement and highlights the crucial role of high-quality ground truth data in teaching machine learning models to correct massive raw data.Key Takeaways:(03:08) How physics equips data scientists with unique skills.(08:43) Nielsen’s history and mission.(09:23) The evolution of audience measurement.(11:46) The challenge of measuring fragmented digital media consumption.(16:12) Nielsen’s efforts to stay relevant in the privacy-protected world.(20:20) Ground truths help AI learn and correct massive data. (23:40) Privacy’s impact on smaller publishers and media outlets.(32:40) The need for continuous learning in a rapidly evolving industry.Resources Mentioned:Rouzbeh Gerami -https://www.linkedin.com/in/rouzbeh-gerami-69b0b77/Nielsen One Ads -https://www.nielsen.com/news-center/2023/nielsen-one-launches-globally/“The Innovator’s Dilemma” by Clayton Christensen -https://www.hbs.edu/faculty/Pages/item.aspx?num=46Thanks for listening to the Data Masters Podcast. If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

In this episode, Lori Bieda, Chief Data and Analytics Officer of BMO North American Personal and Business Bank, explains how BMO leverages data and AI to drive business efficiency, personalize and enhance customer experiences, and mitigate risk. Lori highlights the importance of balancing centralized data governance with data democratization to make fast, smart and effective decisions across business units. She also shares how BMO is using AI-powered tools to make its home-buying process more transparent and personalized.Key Takeaways:(02:07) BMO centralizes data governance and distributes analytics across business units.(04:50) Centralized data governance ensures regulatory compliance and reduces costly data issues.(07:59) Decentralized analytics empower teams to make fast, data-driven business decisions.(09:06) The importance of democratizing data and making it easily consumable for business units.(12:23) Personalized customer experiences and fraud prevention.(17:52) The risk of data security breaches has grown significantly, necessitating a strong focus on AI-driven fraud prevention.(19:48) Convincing organizations to invest in data and AI requires showing both the risks of inaction and the benefits of investment.(24:00) BMO is using AI to streamline its home-buying process, creating a more transparent and personalized experience.Resources Mentioned:Lori Bieda -https://www.linkedin.com/in/loribieda/BMO North American Personal and Business Bank -https://www.linkedin.com/company/bank-of-montreal/BMO | Website -https://www.bmo.com/Thanks for listening to the Data Masters Podcast. If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

On today’s episode, we are joined by Tom Andriola, Vice Chancellor, Information, Technology and Data, and Chief Digital Officer of UC Irvine. Tom discusses the growing impact of AI and technology on education and healthcare. From AI assisting in patient diagnosis to unbundling traditional degree programs, Tom reveals how institutions like UCI are adapting to the changing digital and workforce landscape. He explores how AI, data analysis and creative innovation can revolutionize the future of both learning and healthcare, making them more efficient, accessible and personalized.Key Takeaways:(02:47) UCI operates across two distinct sectors: healthcare and education.(03:27) Healthcare and education are becoming more data-driven, from teaching to patient care.(05:09) Effective AI depends on having strong data foundations.(08:33) The traditional four-year degree model is evolving due to online and AI-assisted learning.(10:30) Unbundling education focuses on mastering specific skills, not completing full degrees.(12:19) UCI offers both online and in-person options for lower-level courses.(16:30) Wearable tech is reshaping healthcare by providing continuous health data.(20:57) UCI’s student and patient-centered strategy uses data to enhance outcomes and personalize care.(24:15) The future of data is moving toward conversational, query-based, AI-driven analytics.(28:04) Data analysts may evolve into expert prompters, helping businesses get what they need faster.(34:47) Institutions need to challenge whether data aligns with their values. Resources Mentioned:Tom Andriola - https://www.linkedin.com/in/tomandriola/UC Irvine - https://www.linkedin.com/school/university-of-california-irvine/Digital Squared - https://digitalsquared.buzzsprout.com/Thanks for listening to the Data Masters Podcast. If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast

On today’s episode, we’re joined by Austin Tidmore, Vice President of Data Innovation at ASGN Incorporated. Austin shares his vision of innovation as an intentional data-powered process developed to achieve business goals. He emphasizes the importance of augmenting human capabilities with AI rather than replacing them and highlights the critical intersection of innovation and data in shaping enterprise-level strategies.Key Takeaways:(02:05) Unify businesses with data and AI to operate more efficiently and add value for clients.(03:10) Innovation is linked to maximizing operational efficiency.(06:35) Consulting accelerates career growth through diverse exposure.(12:33) The difference between innovation and disruption.(13:47) The talent and staffing industry is ripe for innovation.(15:00) AI augments human decisions, it doesn’t replace them.(18:30) The role of AI in both crafting résumés and mining through the noise.(23:47) The challenges for LLM and enterprises posed by unstructured data.(26:40) Graph databases can help structure and navigate data.(29:46) Innovation is intentional and needs to align with business value.Resources Mentioned:Austin Tidmore - https://www.linkedin.com/in/austintidmore/ASGN Incorporated | LinkedIn - https://www.linkedin.com/company/asgn-incorporated/ASGN Incorporated | Website - https://www.asgn.com/University of North Texas - https://www.unt.edu/Clayton Christensen's Disruptive Innovation - https://hbr.org/1995/01/disruptive-technologies-catching-the-waveHadoop and Big Data - https://hadoop.apache.org/Spark Clusters - https://spark.apache.org/Thanks for listening to the Data Masters Podcast. If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.#DataStrategy #DataManagement #DataMastersPodcast