Data Citizens Dialogues

What's the point of creating value with your data if you never cash it in? This week, Barb Wixom, Principal Research Scientist at MIT Sloan's Center for IS Research, takes us through the critical but oft neglected journey of turning data into definitive financial gains.In peeling back the layers inherent to the value creation process, Barb insists that the leap from data to dollars must involve more than simply generating insights; it requires a strategic pivot towards value realization. With the IWS (Improve, Wrap, Sell) framework, we’ll help demystify the process, and show you exactly how operational enhancements and product advancements can be carefully leveraged to achieve financial outcomes. It’s a comprehensive look at the practicalities of converting data into tangible value; a must-listen for anyone looking to navigate the complexities of data monetization effectively.Three reasons you should listen to this episode:1. Value Creation to Realization. Barb breaks down the critical steps from value creation to value realization in data monetization, highlighting a commonly overlooked phase that is crucial for translating data benefits into financial returns.2. The IWS Framework. A simple yet powerful tool for organizations to strategize their data monetization efforts, providing a clear pathway from operational improvements to selling information-based solutions.3. Sustainability and Data Monetization. For any effort to be viable long-term, it must not only generate social or operational benefits but also secure financial returns, thereby ensuring the initiative's economic feasibility over time.ResourcesConnect with JayConnect with BarbTake her survey for her data monetization study Enjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Is data the Coast Guard’s compass to new horizons? This week, Toan Do, Area Vice President of Federal Sales at Collibra, invites Capt. Brian Erickson, Chief Data and Artificial Intelligence Officer at the United States Coast Guard, to shed some light on the Coast Guard's transformative journey from traditional navigation to data-driven decision-making, illustrating how data is becoming the compass guiding the organization's mission and operations.Amid the challenges of implementing data analytics and AI within the Coast Guard, Capt. Erickson has come to recognize the value of starting small, focusing on high-priority use cases, and fostering a data-literate workforce. His personal transition from a career aviator to leading the Coast Guard's first data office is a perfect parallel to the evolving role of data as a strategic asset in enhancing mission effectiveness. And as if that’s not already a shining example of leadership in data, Capt. Erickson is now preparing to pass on this newfound passion to his successor, setting the stage for a bright future of enthusiastically data-literate military personnel.Three reasons you should listen to this episode:Unique perspective on data's role. Capt. Erickson’s journey from a career aviator to leading the Coast Guard's first data office highlights how data can be leveraged as a strategic asset in a multifaceted organization.Practical insights on data implementation.  When approaching the integration of data analytics and AI, starting with small initiatives and developing a workforce that is proficient in data literacy yields big results.Strategic approach to data management. Order and efficiency are clearly a necessity in data management, as is incremental growth and easy wins to build confidence.ResourcesConnect with ToanConnect with Capt. EricksonEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

We all know that every bit of an organization’s data ought to be treated equal, right?  Well, in a world where clean data is often the status quo, Julie Fawdington, Senior Director PMO at Hewlett Packard Enterprises, invites us to ask the question, how clean is clean enough?Drawing on her extensive experience in data transformation, Julie’s take on data quality suggests the need for data quality differentiation. As she puts it, the stuff in her pet’s water bowl isn’t the same as what’s in her water bottle. But does this idea that not all data requires the same level of cleanliness really upend conventional wisdom? Or does it simply provide a more nuanced understanding of how to efficiently manage data in today's fast-paced business environment?Three reasons you should listen to this episode:1. Redefining data standards. Discover Julie's unique approach to data quality and how it can revolutionize your data management practices.2. Empowering data stewards. Examine the role of data custodians and stewards in driving business processes and effectively managing data quality and governance.3. Leadership's role in data management. Learn practical steps for how leaders can promote data quality and management within their organizations.ResourcesConnect with Julie on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

It's no secret that AI has seen massive success in FinTech, but what hidden forces are driving this success, and how do they transform raw data into global opportunities? This week, guest host Stijn Christiaens invites Peep Küngas, Data Architect at Monese to decode the intricacies of data quality management and its profound impact on the tech landscape, offering fresh insights into this crucial yet often overlooked backbone of AI innovation.How do the smallest details in data curation fuel major breakthroughs in AI-driven solutions? And what unseen challenges do data architects grapple with in their mission for impeccable data? Listen as Peep and Stijn peel back the layers of data quality management to reveal the critical role of precision and insight in shaping the future of FinTech and our next technological leap forward.Three reasons you should listen to this episode:1. The foundation of AI success. Understand the integral role of data quality management in enhancing AI's performance in the FinTech industry.2. Navigating data complexities. Examine the challenges, strategies, and rigorous process behind ensuring impeccable data quality.3. Data quality as a discipline. Find out what fitness routines teach us about the continuous effort and collaboration required to maintain and improve the backbone of digital innovation.ResourcesConnect with Peep on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

The digital realm's new currency is data, yet its value is often as enigmatic as it is critical. Sanjeev Mohan, Principal of SanjMo and former Gartner analyst, decodes the complexities of data valuation, advocating for a product-oriented view that frames data's utility and impact within an organization. The prerequisites for defining a 'data product'—from maintaining stringent quality and availability standards via Service Level Agreements to managing its lifecycle for enduring relevance— bring into focus the role of the data product manager. This role is vital to ensuring continuous enhancement and overseeing the retirement of data products; a job that guarantees these products remain a driving force for organizational value.In the pursuit of measurable benefits, treating data with the rigor of product management emerges as a beacon for Chief Data Officers, offering concrete metrics through the creation and utilization rates of data products, and providing a clear gauge for the pace and quality of innovation in data work.Three reasons you should listen to this episode:1. Data Product Insights. Grasp the value of data work as Sanjeev Mohan breaks down the essence of data products and their role in shaping business strategies.2. Data Observability. Learn about the critical nature of data observability and quality, and why these factors are non-negotiable in the pursuit of high-caliber data standards.3. Industry Foresight. Gain perspective on the current and future trends of data analytics as seen through the lens of an industry veteran.ResourcesConnect with Sanjeev on LinkedInAnd for a deeper understanding of data products, check out Sanjeev’s book, "Data Products for Dummies".Enjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Becoming "data driven" transcends mere technical implementations—it’s an organizational culture rooted in deliberate mindsets and collaborative strategies. Nico Huybrechts, CEO at Datashift, elucidates this concept, sharing from a wellspring of expertise on fostering a data-centric culture that's embedded in an organization's DNA.While expounding on the notion of 'data-preneur tiger teams,' which hints at a daring approach to tackling challenges in the data realm, Nico's mantra, "achieve impact together," resounds as a call for deep organizational collaboration on strategy, emphasizing that there's no separate data strategy from the business strategy. This approach, enriched with deep listening skills and meaningful cross-organizational connections, not only aligns teams but embeds a data-driven ethos within the organizational fabric, paving the way for sustained success.Three reasons you should listen to this episode:1. Unlock the roadmap to becoming a data-driven entity. Nico Huybrechts shares actionable insights on blending technical and human elements to foster a data-centric culture, a crucial step for leaders aiming to leverage data for enhanced business outcomes.2. Learn practical strategies to enhance business agility. Delve into strategic alignment, the concept of data-preneur tiger teams, and the transition from creative to running mode for data projects to tackle common challenges in data strategy execution.3. Gain a holistic understanding of embedding a data-driven ethos. Explore the importance of deep listening. organizational collaboration, and meaningful cross-organizational connections to get a well-rounded perspective on truly becoming data-driven.ResourcesConnect with Nico on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

A seismic shift is underway at Booking.com as the travel giant embarks on an ambitious cloud migration and data transformation journey. In this episode, Milo Milovanovic, Senior Director of Big Data Technologies, offers an insider's look at how they are reshaping their data analytics and machine learning platforms to accelerate innovation. By transitioning to the cloud and establishing robust data governance, Booking.com aims to unlock the full potential of their data. Milo explains how improved data quality, access controls, and lineage tracking enable analysts to spend less time prepping data and more time unlocking actionable insights. The end goal is simple: leverage technology to deliver unparalleled customer experiences… and trust in data to drive vital insights for the organization.Three reasons you should listen to this episode:1. Learn how data governance and quality unlocks innovation in the cloud. Milo provides an invaluable perspective into how Booking.com is streamlining their data analytics and machine learning platforms. By focusing on governance, access controls, and data transparency, they empower analysts to spend less time prepping data and more time generating impactful insights.2. Discover how to accelerate your analysts’ productivity. Booking.com aims to reduce the time analysts spend cleansing data and increase the time they spend on value-add analysis. Milo explains how robust data governance and cloud migration helps them achieve this goal.3. Gain insider tips on executing major cloud transformations. Milo offers an insider’s view of the real-world complexities involved in migrating analytics and ML platforms to the cloud. Tune in for wisdom on change management, delivering quick wins, and getting organizational buy-in.ResourcesConnect with Milo on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

If the rise of Chief Data Officers (CDOs) within the public sector is any indication, we’re currently witnessing a paradigm shift towards making data a fundamental cornerstone of government operations. What’s more, as these agencies increasingly prioritize data, legislative acts like the Foundations of Evidence-Based Policymaking Act and the Open Data Act further underline the shift. In the quest for actionable insights from data, Adita Karkera, CDO at Deloitte Goverment, dives deep into the "so what" of data to spotlight the significance of ethically grounded AI, transparency in its applications, and the imperative for diversity in data teams. Tracing her journey from a database analyst to a pivotal, business-centric role, Adita underscores the essence of aligning data strategies with broader mission objectives. It's not just about collecting and analyzing data; it's about understanding its broader implications, the story it tells, and the impact it has on the people it serves.Three reasons you should listen to this episode:1. CDOs in the Public Sector: Understand the burgeoning role and significance of Chief Data Officers in governmental operations.2. The Universality of Data Literacy: Explore the significance of data literacy across organizations, how it's more than just for technical roles, and why CDOs are emphasizing its importance in developing a solid data culture and strategy for better outcomes.3. Ethics and Diversity in AI: Delve into the responsibilities of using AI in the public sector and the vital role of diversity, especially women, in the decision-making processes of data-driven solutions.ResourcesConnect with Adita on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Data is more than just a buzzword at Colt Technology Services; it's the linchpin of their operational evolution. In this episode, we talk with Ram Narasimhan and Rohan Pawar about how Colt is reshaping its organizational culture around a five-pillar program designed to democratize data and foster trust at every level of the enterprise.Navigating through the complexities of data quality and cloud-based governance, our guests offer invaluable insights into the convergence of business strategy and technology. They also discuss the real-world benefits of a data-driven approach, from enhancing customer experience to unlocking new revenue streams. Tune in to learn how their journey can serve as a roadmap for your own organization's data-driven transformation.Three reasons you should listen to this episode:1. Democratization in Action: Get an insider's view of Colt's five-pillar program that is setting new standards in democratizing data and fostering organizational trust.2. The Business-Technology Synergy: Understand the nuances of aligning business strategies with data and technology, as explained by experts in the field.3. Tangible Benefits: Hear firsthand about the measurable improvements in customer experience and revenue generation that a data-driven culture can achieve.ResourcesConnect with Ram on LinkedInConnect with Rohan on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

In healthcare, data governance stands as a pivotal factor in improving both patient outcomes and operational efficiency. In this episode, Roy Schmidt, Data Governance Program Manager at Envision Healthcare, joins us to share an insider's perspective on how his organization has successfully implemented a robust data governance program, impacting both clinicians and patients alike. Roy delves into Envision Healthcare's transition toward value-based care, a model which rewards healthcare providers based on patient outcomes rather than services provided. Join us as we explore how combining effective data governance with a human-centric approach can make a transformative difference in healthcare delivery, patient satisfaction, and overall organizational goals.Three reasons you should listen to this episode:1. Real-World Success Insights: Gain a deeper understanding of Envision Healthcare's successful data governance model that optimizes healthcare delivery and patient outcomes.2. Value-Based Care Unveiled: Discover the critical role data governance plays in enabling a value-based care system, enhancing both patient satisfaction and cost-effectiveness.3. Human-Centric Data Governance: Learn how a people-first approach in data governance not only increases operational efficiency but also contributes to compassionate healthcare delivery systems.ResourcesConnect with Roy on LinkedInEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Navigating the intricacies of building a data governance program within  a banking context is no small feat, requiring strategic vision, stakeholder buy-in, and detailed execution. In this episode, Börge Hansen, Strategic Data Manager at Union Investment, invites us into his world of establishing a data governance program across the organization. , where hHe reveals the nuances of his comprehensive approach and shares lessons learned along the way.Hansen emphasizes the importance of having a structured and comprehensive overview of data within a bank, a foundation that has proven critical in his role. He candidly discusses the indispensable need for designated data owners for each system and outlines the strategies he employed to secure essential stakeholder buy-in. Join us for a deep dive into Börge's journey, offering a masterclass in the tangible steps and strategic thinking required to produce exemplary results in data governance.Three reasons you should listen to this episode:Gain firsthand insights from Börge Hansen, as he navigates the complexities and challenges of building a robust data governance program in a banking environment.Understand the pivotal role of having a comprehensive and structured overview of data, and appreciate the value of designated data owners within a banking system.Learn actionable strategies for securing essential stakeholder buy-in for data governance initiatives, drawn from Börge’s wealth of experience and proven track record.ResourcesConnect with Börge on PolyworkEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Amid a sea of change, the retail landscape has dramatically shifted over the past five years. In this episode, Henry Rice from Frasers Group joins Chief Data Citizen, Stijn Christiaens, at Data Citizens On the Road where they explore the far-reaching impacts of Brexit, the global pandemic, and the cost of living crisis on the retail industry. In the latter part of the conversation, Henry and Stijn tackle the challenge of morphing a 'data village’ into a formidable 'data metropolis.’ They also explore how we can shatter the age-old boundaries between technical and business facets to become indispensable data partners to our business.Three reasons you should listen to this episode:Learn about the profound impact of Brexit, the global pandemic, and the cost of living crisis on the retail landscape, and how Frasers Group managed to adapt and thrive.Understand the pivotal role of data governance in adopting emerging technologies like generative AI and machine learning.Discover insights on transitioning from a 'data village to a 'data metropolis', the importance of aligning with the business, and how to become an indispensable data partner to your business.ResourcesConnect with Henry on LinkedinConnect with Stijn on LinkedinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

In this episode, Katie Reynolds, Director of Data Management, Analytics, and Visualization at Case Western Reserve University draws on her experience with building a data community across various universities to underscore the importance of data governance amidst extensive regulatory requirements.As we explore the rapid evolution of technology and AI, and the pivotal role of data governance communities in expediting the journey towards effective data governance in higher education, Katie’s journey highlights the power of shared experiences, from success stories to challenges, and the insights gleaned from interacting with other universities. Three reasons you should listen to this episode:Grasp the complex dynamics and importance of establishing a data community in higher education, and the integral role of data governance in this context.Learn about the transformative power of data governance communities in propelling the journey towards effective data governance in higher education.Gain insights into the rapid advancements in technology and AI and their implications for the future of data governance.ResourcesConnect with Katie on LinkedinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

The significance of data literacy in our efforts to promote collaboration and decision-making cannot be overstated. In this episode, John Yelle, Executive Director for Enterprise Data Management at DTCC, takes us inside the fascinating world of the financial industry to explore the three V's of data - volume, velocity, and variety - and learn how they play a vital role in driving this digital evolution. Join us as we delve into DTCC's data management program, a seven-year journey of dedication and innovation. John shares invaluable insights about the importance of data quality, governance, and the necessary cultural changes for achieving a successful transformation. We also discuss the tangible measures of success, such as risk reduction, faster results, and effective capacity planning, which serve as proof of the merit of a data-first digital transformation approach.Three reasons you should listen to this episode:Gain insights into the role of data - volume, velocity, and variety - in driving digital transformation in the financial industry.Learn about the importance of data quality, governance, and cultural changes in achieving a successful digital transformation.Understand the measures of success for a data-first digital transformation approach, including risk reduction, faster results, and capacity planning.ResourcesConnect with John on LinkedinEnjoyed this Episode?Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.Have questions? You can connect with us on LinkedIn. For more updates and additional resources, please visit our website.

Discover the fascinating world of data marketplaces and unlock the potential of monetizing your organization's data in our conversation with Jay Bhankharia, a Senior Director at Databricks. Jay shares his expertise on how data marketplaces connect buyers and sellers of data assets and discusses the role of Language Learning Models (LLMs) in enhancing the user experience and aiding data providers in sharing and selling data more effectively.In this episode, we’ll explore the increasing importance of data marketplaces for businesses in the digital age, highlighting a Gartner study that states that companies who collaborate and share data have three times better economic outcomes than those that don't. Learn how data marketplaces offer an open platform for customers to access data from multiple vendors, transferring it into their own tools and platforms with ease. We also touch on the impact of controls in data marketplaces to ensure data products are user-friendly and easy to purchase, and the exciting advancements in technology that have enabled companies to access and use data more efficiently, such as cloud computing, data science, and governance and access controls. Don't miss our conversation on the future of data marketplaces and how they're becoming a key component of business success.ResourcesConnect with Jay on LinkedinEnjoyed this Episode?If you did, subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. Have any questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Can data governance programs evolve to provide even greater value from our data? That's the question we tackle with our insightful guest, Raluca Alexandru, an analyst at Forrester. We talk about the key components of a data governance program, such as people, process, and technology, as well as the critical role that data catalogs and business glossaries play in mapping out data assets, structuring them in an easily digestible way, and connecting them to business goals and objectives. The episode also delves into the need to create connected intelligence by combining data governance with AI governance programs. We discuss the potential risks of generative AI and how existing data governance frameworks can help manage those risks while creating value. We also take a closer look at the ethical and legal implications of AI programs and why AI governance is essential in reducing bias and adhering to policies and regulations. Moreover, we explore the importance of setting measurable metrics to assess the success of data governance programs, and how an intelligent federated approach can maximize their value. Don't miss this thought-provoking conversation with Raluca Alexandru that covers the future of data governance and intelligence solutions!ResourcesConnect with Raluca on LinkedinEnjoyed this Episode?If you did, subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. Have any questions? You can connect with us on LinkedIn. For more updates, please visit our website.

Data strategy in 2023 is no longer a mystery. As businesses embrace data monetization, it’s vital to understand how to convert data products into revenue sources. In this episode, we chat with Stijn Christiaens, co-founder and Chief Data Citizen of Collibra, who unveils the secrets of data strategy and bridges the gap between data and business language.Join us as we explore the evolving role of data engineers and their need for a deeper understanding of the products and applications they work on. We also discuss the significance of data democratization and the emerging data marketplace, which allows organizations to access and measure data value in a democratic way.Tune in to this insightful episode to stay ahead of the curve in data strategy.Here are three reasons why you should listen to this episode:1. Learn the importance of data monetization in your overall data strategy.2. Discover how the role of data engineers is evolving as they adapt to operationalizing machine learning models.3. Understand the impact of data democratization and the rise of data marketplaces on the business landscape.ResourcesConnect with Stijn on LinkedinEnjoyed this Episode?If you did, subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. Have any questions? You can connect with us on LinkedIn. For more updates, please visit our website.

AI is no longer for data scientists only. Most businesses have made AI tools part of their workflow. For example, we’ve seen chatbots, automated emails, and the like. As we embrace artificial intelligence, we have to discuss it. What is AI? What is it not? Should we use it for everything?In this episode, Sarah Hoffman, VP of AI and Machine Learning Research in Fidelity Investments, defines AI and its impact on our lives. She also describes the ethical challenges of data bias and what people are doing to overcome it. Finally, Sarah explains why diversity and prejudice are significant concerns in AI development.Tune in to this episode to learn how AI pushes for innovation. Here are three reasons why you should listen to this episode:Discover artificial intelligence as a new approach to learning and training. Learn how AI is a reflection of our own beliefs and understanding. Understand the relevance of diversity in the field of artificial intelligence.ResourcesConnect with Sarah on LinkedIn and Twitter Know more about FCATBe part of Random Hacks of KindnessEpisode Highlights[00:47] AI and ML Research at FCATThe Fidelity Center for Applied Technology (FCAT) has a long history of innovation and commitment to technology.Sarah: "We invest deeply in technology. But we've also always recognized that technology is just a tool. It's really how we apply it that matters." FCAT develops platforms and products to empower the next generation.Sarah is a part of FCAT's research team. They explore the future of artificial intelligence (AI).[02:29] Defining AISarah uses AI and machine learning (ML) interchangeably.ML refers to code learning from data.  It produces answers based on stored information to make predictions.AI is math, not magic. [03:43] AI in the Finance World FCAT provides services that harness AI’s true potential.Financial services use AI tools often. Many people use chatbots, robo-advisers, and automated email responders.Several companies have adopted personalization and sentiment analysis.Models need to adjust when something changes in the world.[06:46] Data Ethics Concerns AI learns biases through data. Ethics boards address ethical issues regarding AI projects and decide whether a problem needs AI.Fairness and explainability tools are available to protect against inadvertent biases. Using AI can enhance how we train people and use fairness and explainability tools. li...

Data analysis, data science, and machine learning. The boundaries between these three may not be apparent, but these fields are related and interconnected. So it’s possible to start a career in one and dabble with another. Data has made it easy to connect and acquire information. However, we must be vigilant in upholding privacy.In this episode, Gretel De Paepe, senior data scientist at Collibra, shares what she’s learned in her data career. She tackles the importance of data in our lives and its incredible value — in the present and the future. Lastly, she tackles myths on artificial intelligence and machine learning.Tune in to the episode to learn how to handle data correctly.Here are three reasons why you should listen to this episode:Find out what inspired Gretel into pursuing data science.Learn how to appreciate data in making our lives better from both the average user’s and company’s perspective.Go beyond data bias and our misconceptions around artificial intelligence and machine learning.ResourcesConnect with Gretel on LinkedIn.Episode Highlights[01:02] Machine Learning Projects at CollibraCollibra offers many services to their customers.Data classification helps companies classify fields that contain personally identifiable information (PII) data.Asset recommenders give a list of recommendations based on one’s datasets.Similarity detection looks for similar assets to prevent potential duplication and keeps the database clean.[02:42] Defining Data Science, ML and AIData analysts looks at the data to provide a data-driven answer for a business question. Data science deals with statistical modelling.The leap from data science to machine learning (ML) is small because machine learning is one way to model data.ML is simply a tool in the data science toolkit. [04:51] Gretel’s Data JourneyGretel’s progression from data analysis to data science was a natural process.When solving different challenges, you must explore other techniques and build up your portfolio.She invested time and money into learning about machine learning.[10:19] Gretel’s Natural Interest in Data ScienceGretel treats data analysis like a hobby.She easily loses herself in a project because she’s interested in data science.Gretel: “Usually when I start with a project, there's not much information yet. It's sort of, “Oh, we may wanna do something in this area. But we don't really know yet what it is.” And so, the whole exploration phase of trying to identify what it is that we could do, what techniques we could use. And compare them, just try them out and compare them. It's a creative process.”[14:05] How Data Gives Value to ConsumersWe use data in statistics.Data is used often in our daily lives and provides many benefits.[19:24] The Myths and Unnecessary Hype around Data ScienceMarketing for artificial intelligence should focus on the fact that it’s only artificial. A machine’s algorithm is limited by what it’s trained to do.[23:26] Data BiasGretel: “If you have a bias in your data, you will have a bias in your model. So your model is indeed only as...

The topic of sustainability has undoubtedly gained massive traction and momentum across industries over the past years. According to Martin Weirich, ESG is more than a buzzword and a PR trick — businesses have realized the beneficial impacts of sustainable models. From this, the term ESG or Environmental, Social, and Governance has emerged — and it's here to stay in the hopes of a better future for the world.In this episode, Martin Weirich, Partner Financial Services Management Consulting at PwC, discusses the basics of ESG. Martin delves into the regulatory aspect of ESG and how it can help make the world a better place. He talks about shifting the perspective and the future trajectory of ESG regulations. He also shares the most significant challenges companies face and how to navigate them.Tune in to the episode to understand how ESG is changing the ways of companies and the world's future.Here are three reasons why you should listen to this episode:Learn the three aspects of ESG.Discover the impact ESG makes on companies and the world at large.Find out Martin's prediction on what the ESG landscape would look like five years from now.ResourcesPwCConnect with Martin on LinkedInConnect with Jay on LinkedInEpisode Highlights[01:19] What is ESG?ESG stands for Environmental, Social, and Governance.The environmental aspect includes concepts around climate, biodiversity, energy consumption.The social aspect concerns equal opportunities, human rights, health and safety, etc.Governance is about determining good governance and dealing with topics from an organizational standpoint.[02:18] The Regulatory AspectThe European side has already committed politically to specific ties they want to achieve as a region by 2030.There’s a new required regulation influencing different sectors to support the political world to reduce greenhouse gas emissions and move toward renewable energy.The regulators began with the financial services sector because it deals with the orientation of capital flows. Achieving the requirements also requires acquiring information (financial and environmental advocacy) from investee companies.These are not only regulations for bureaucracy’s sake but to make the world a better place.Martin: "I think the dimension has a prompt. It's not only doing a tick box exercise from a regulatory perspective but also thinking out 'How can my products and my services help contribute to the overarching goals that we have all set?'"[06:26] More than Just a PR StatementA lot of companies used ESG as a marketing instrument in the beginning. However, these companies soon realized that there's also public transparency enforced by regulators, clients, investors, and associations.li...