Data Citizens Dialogues

Join us LIVE at Collibra’s DC’22, where we talk about the relevance of data intelligence. We are joined by the 2022 Collibra Excellence Award-Winners: Acceleration All-Star winner Heather Wentworth, chief data officer of Accelerant Holdings; Program of Year winner David Mitchell, senior director of engineering of Cox Automotive; and Collibra Ranger of the Year Peter Vennel, enterprise data strategy and execution executive of Equifax.How do businesses strike the ideal balance between powerful analytics and ease of use? Tune in to learn how data intelligence can help you solve problems and grow your business.Here are three reasons why you should listen to this episode:Learn why these individuals and companies stand above the rest in data intelligence.Discover the secret to maximizing Collibra.Unravel the future of data intelligence.Resources Learn more about CollibraAccelerant Cox AutomotiveEquifaxConnect with our guestsHeather: LinkedInDavid: LinkedInPeter: LinkedIn | TwitterEpisode Highlights[01:54] Collibra Award’s SignificanceAccording to Heather, the Acceleration All-Star of the Year award represents the company’s efficient planning and implementation from start to production.David sees the Data Program of the Year award as a culmination of their data strategy and execution efforts. It also highlights their culture of innovation and collaboration. Winning the Collibra Ranger of the Year award, Peter considers their company’s decision to use Collibra a wise investment. [06:47] How They Started in the Field of Data David was a software engineer before moving into the financial data industry, where he discovered his love for problem-solving and helping customers.Heather shifted careers because of the culture of valuing sizzle over data.Given his professional background, Peter’s transition into the data industry was not by chance. As he continues to work in the field, he hopes to improve its quality.[13:12] Reduce the Swivel Chair Instead of focusing on various aspects, it is best to concentrate on system engagement.David: “As you look at bringing people processing technology together, you’ve got to win the hearts and minds of people to actually get involved in [system engagement].”Learn how to use Collibra’s automation to pull information rather than having people do it.[14:25] The Secret Sauce Your team is the key to success.Start-ups have a significant advantage in moving around the data ecosystem quickly.Understand your company culture.Heather: “​​All of my team have some experience and have seen the [worst of implementations]. I think a lot of that comes to guidance from maybe consulting firms that are not close enough to it or don’t understand the company culture.”[16:10] Peter’s Ranger Journey Peter wanted an in-depth understanding of the Collibra process and got his certification after 8 months.Peter: “There’s no one size that fits all. Every industry can implement Collibra in a different way.”You need to be a domain expert to see the advantage of Collibra quickly.[18:24] Five Years from Now In the future, we’ll be able to predict businesses' performance and prevent negative outcomes. We’ll be able to mine data and perform more automated processing.Automation will be critical in the quick transmission of data from provider to consumer.AIML will be further infused with technical lineage and data quality.About Heather, David, and PeterHeather Wentworth is the chief data officer at Accelerant Holdings, where she is in charge of the company’s data strategy and the design and implementation of data intelligence. Her team’s dedication to providing customer-facing solutions that reinvent the insurance experience earned them the Collibra Acceleration All-Star award.Follow Heather on LinkedIn.David Mitchell is the senior director of engineering at Cox Automotive. His company's program was named Collibra's Program of the Year. With excellent engineering teams, David builds and operates the cloud-native Enterprise Data Platform, Enterprise Data Marketplace, and ModelOps platform. Follow David on LinkedIn.Peter Vennel is the enterprise data strategy and execution executive of Equifax. He assists organizations in monetizing data as an asset. Peter has worked with multiple C-suite executives and external partners on Strategic and Tactical Data Management and Governance initiatives. He was named Collibra Ranger of the Year. Follow Peter on LinkedIn and Twitter. Enjoyed this Episode?If you did, be sure to follow, post a review and share it with others.This episode will inform you on how organizations can effectively implement data ethics and the importance of upholding your customer’s privacy when using their data.Have any questions? You can connect with our host, Jay Militscher on LinkedIn. Thanks for tuning in! For more updates, please visit our website. You may also listen on Apple Podcasts or Spotify.

Join us LIVE at Collibra’s DC’22, where we talk about the importance of data governance with Joe Wallace, senior manager for Digital Asset Governance, Adobe, and Ryan Galloway, senior vice president for Moody's Corporation. How can companies improve their data quality and decision-making processes? Listen as they explore some of the challenges associated with data governance and share tips for overcoming them. Tune in if you want to learn to integrate effective and ethical data governance in your company.Here are three reasons why you should listen to this episode:Find out how Adobe and Moody’s Corporation integrate data governance.Learn how Adobe and Moody’s Corporation utilize data governance to achieve their company goals.Discover how data governance can help companies succeed in today’s market.Episode Highlights[03:09] Moody’s Corporation and Data Governance Ryan: “I always say push versus pull. It's a journey. You have to start there.”Moody’s Corporation welcomed data governance to their company because they believe it would be helpful for business. As a result, they found an advocate for data governance and thought of using it to solve business problems.Any company interested in integrating data governance should consider building the following: standards and policies, business partners, advocacy, and real governance.Once these are in place, form a data governance team to help solve real data-related business problems.Focus on the mantra, “success breeds success.”[04:13] Digital Asset Governance and Data GovernanceJoe: “Fish with a smaller fish to get a bigger fish.”Adobe started small and ended big by building data governance around the company’s goals.It grew exponentially as more and more people heard and saw the data-related efforts the company was doing.The people could enrich the company because it dedicated its time to guiding them, providing them with playbooks, and facilitating their work.[07:16] Data, Water, and CakeJoe believes that data is like water. You trust the source that the water is clean.He adds that data is a component of a cake. The top layer where the frosting sits pertains to the business layer (e.g. process flows, business rules), the one people see.Below the frosting are the data products. The final layer is the data lineage.The three layers compose every company's data governance. They are assets that draw customers in and protect them.Data governance should always be customer-centric.[10:34] The Future Of Data GovernanceSociety has moved from wanting more data to trying to solve the problem of excess data. Hence, Joe believes that over the next ten years, people will start labeling and organizing data.Joe: “The groundwork is there. But I think there's just gonna be more and more and more and more data.”Ryan agrees that there is a ton of data in society today. So, the challenge for people now is defining meaningful and not meaningful is critical.He adds that automation will improve. Scanning databases and grading data lineage could become automated in the future.Ryan: "You're never done with data governance. We must realize this isn't going away. This is something we're going to have to continue doing."About Joe and RyanJoe Wallace is the senior manager of Digital Asset Governance at Adobe. He has over 15 years of experience in digital asset management and has been instrumental in developing and implementing several successful governance models for major organizations. Joe is a recognized expert in the area of digital asset governance.Ryan Galloway is the senior vice president of Enterprise Data Management Tools at Moody's Corporation. He is a thought leader in data management and instrumental in helping Moody's Corporation implement some of the most cutting-edge data management technologies worldwide. Follow Ryan on LinkedIn.Enjoyed this Episode?If you did, be sure to follow, post a review and share it with others.This episode will inform you on how organizations can effectively implement data ethics and the importance of upholding your customer’s privacy when using their data.Have any questions? You can connect with our host, Jay Militscher on LinkedIn. Thanks for tuning in! For more updates, please visit our website. You may also tune in on Apple Podcasts or Spotify.

Data can drive game-changing business decisions, but inconsistent data can do the opposite. The world of data has come a long way, but we still see businesses with problematic data reporting, which leads to their eventual downfall. The more we use data, the more we need to see it as both an asset and a responsibility.In this episode, our host, Jay Militscher, invites Stijn Christiaens, Collibra's very own Chief Data Citizen, to explore the topic of data citizenship and what it means for companies and data professionals. They will dive into what it means to be a data citizen and how to be intentional about data usage. Stijn also shares Collibra's growth over the years and showcases the importance of continuous improvement as data citizens. They also discuss the upcoming Data Citizen Conference and what it means to thrive with data.By listening to the episode, you will:Learn about why correct data handling is critical for businesses to thrive in today's world.Discover the meaning and context of data citizenship.Understand the value of different kinds of data literacy skills in an organization.Find out what questions to ask when using data to create and develop products.Pick up insights on how data drives continuous improvement.Want to know more about how to be a better data citizen? Tune in to discover the what, how, and why of being a data citizen.

In this conversation, Sarah Hoffman, Vice President for AI and Machine Learning Research at Fidelity, sheds light on the practical applications of AI in modern business. She breaks down common myths about AI, explaining its mathematical foundation and ethical implications related to data bias. Sarah emphasizes the need for diversity in AI development and how it reflects our societal values. Additionally, she discusses AI's transformative role in enhancing workplace innovation and accessibility through democratized technology.

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 good as the data that you train it on.”Big tech companies open source their models, architectures, and patent packages. However, their data isn’t.Obtaining data that’s vast and also diverse is a challenge.Security has to be built-in from the start to ensure the obtained data isn’t biased.[26:23] Auto-MLAuto-ML only works well when the hyper parameters are already known. Computer vision enables the detection of objects in images equal to or sometimes better than human accuracy.Another breakthrough was also seen in NLP but language is more complicated than pictures since it’s constantly evolving.[31:03] Data Science in the Next Five YearsPeople will see value in combining ML with privacy protection.Gretel: “Machine learning is a little greedy beast. It needs a lot of food. It needs lots of data. It's very data hungry. A little hungry,  little thing. And how do you marry that? How do you combine that with also the increasing emphasis on privacy?”There’s a new emerging field called privacy preserving machine learning.Differential privacy ensures that data can’t be used to reverse engineer other datasets.Jay: “What's often really interesting about data is finding common things, patterns, clusters of information. Those patterns help to answer questions, make decisions, make predictions, and even recommendations.”About GretelGretel De Paepe has been working as a Senior Data Scientist at Collibra for three years. She has amassed an experience of over 20 years in data. She started as a data analyst, turned into a data scientist then delved into machine learning for the past six years. Gretel considers herself a data addict who loves anything to do with data. If you want to reach out, you can contact Gretel via LinkedIn.Enjoyed this Episode?If you did, be sure to subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. You can also share this episode with your friends and colleagues. This episode will help them understand the ESG perspective.Have any questions? You can connect with us on LinkedIn. Thank you for tuning in! For more updates, please visit our website. You may also tune in on Apple Podcasts or Spotify.

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.Mislabeling, such as green-washing, is a significant risk from a reputational and management perspective.The regulations have defined standards and metrics to make ESG initiatives comparable across different industries.Many companies have shifted from being very marketing-driven to producing substance first and then being vocal.[10:10] Diversity in Companies’ Board of DirectorsA diversified board is a great step towards achieving the governance aspect of ESG.Many corporations have intrinsic motivation to have diverse views on the boards.The US is leading on the topic of diversity. The European side doesn't have a detailed discussion of what a diversified board should look like.There's a push to have internal discussions and debates within firms about living up to this diversity standard.It’s not realistic to change everything at once. It’s more about defining a transition plan towards aligning on the targets and making it public.Martin: “The diversity element is just one element that’s really helping to spark discussions and to get corporations and leaders thinking what you can really do differently to contribute to the overarching goals.”[13:27] The Current Social AspectThe social aspect is now following the focus on the environmental element.The focus of the debate on the European side is on taxonomy regulation. It's about determining whether an economic activity is sustainable or not.There are emerging discussions on what defines social activities that deserve support, investment, and improvement.People are exploring the topics of human health, safety, and human rights in more detail from a banking and insurance perspective.More companies have realized that focusing on the social rather than the environmental aspect of ESG can help them make an impact.[16:52] Shifting the Perspective on RegulationsESG regulations are now more purpose-led. As such, there's momentum within the workforce to do something different because they see a meaning behind it.Companies used to see regulations as a burden and an additional cost factor.[18:13] Sectors Where ESG is Most ImpactfulAlmost all sectors are moving toward becoming more sustainable or producing more sustainable products.More regulations have triggered financial services at an earlier stage. But there’s also a growing sustainability movement in other high energy-consuming sectors.A growing focus on stakeholders instead of financial KPIs is a common theme across sectors.There’s also a focus on optimizing supply chains to become more sustainable and transparent.The two sides of climate risks are how the climate influences the business model and how to improve how the company is impacting the climate.[21:17] The Challenges Companies FaceThe current greatest challenge is data and implementation.Another is the changing political environment outside pure sustainable topics, i.e., other current problems.The challenge to data access varies on the sector type. It may involve information on supply chain, loan sustainability, sustainability of investee companies, etc. Martin: “The market is still maturing, but we are not there yet where we need to be.”[24:40] Data Access TrajectoryCompanies will have to disclose some information publicly in a format that makes it easier to digest.Presently, we rely on data providers with their own cost and fee structures. In the future, data will be available in regulator-defined public databases and data clouds.It will not be enough to rely on public information in some cases. Thus, a hybrid data architecture from vendors and external experts will still be beneficial.[26:11] Martin’s 5-Year PredictionsESG will still be very high on the priority list of all leaders. There are a lot of new market developments where small niche players will help pivot change.Five years from now, we still won’t have achieved what we aimed for from today’s perspective. The journey is more of a marathon than a five-year sprint.There will be no sector or corporation that will not focus on sustainability. There will be a lot of public pressure behind it.Some smaller players will struggle with the significant overhead of regulations that drive ESG progress.[27:54] Jay’s Key TakeawaysAttention on the subject of ESG has recently gained substantial momentum and traction worldwide.There's a lot of regulatory focus that is a groundswell of public and societal desire. Implementation of regulations follows a gradual buildup approach.ESG is aspirational for the greater good, aligned with doing good in the world using methods and frameworks and accomplishing that in measurable ways.New industries, products, and ideas are being created as a part of ESG.About the SpeakersMartin Weirich is a Partner in Financial Services Management Consulting at PwC. His role is to help asset managers and banks transform toward sustainable finance. He is also responsible for helping his team implement the EU Action Plan and adapting business and operating models based on new ESG products and regulatory requirements.If you want to reach out, can contact Martin Weirich via LinkedIn.Enjoyed this Episode?If you did, be sure to subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. You can also share this episode with your friends and family. This episode will help them understand the ESG perspective.Have any questions? You can connect with us on LinkedIn. Thank you for tuning in! For more updates, please visit our website. You may also tune in on Apple Podcasts or Spotify.

The issues our society face today are increasingly complex and urgent. The rise of technology and the impact of the pandemic has put the spotlight on our growing social and environmental crises. But these crises are an opportunity for companies to rise up and show their worth. Now more than ever, companies are called to shift their solutions and initiatives in a way that will positively impact society at large by engaging in collaborative and holistic solutions. This way, they foster a more responsible corporate environment and create a sustainable future for all.In this episode, Melissa Mavlanova-August, the Global Head of Equity and Impact at Collibra, discusses the link between ESG and DEI. Melissa shares the initiatives and programs Collibra organizes to promote social and environmental awareness across the company. She also discusses the work involved in ESG and DEI career paths and the importance of storytelling in sustainable change management.Tune in to the episode to understand the impact incorporating ESG and DEI can have for creating sustainable and ethical companies.Here are three reasons why you should listen to this episode:Learn the meanings of ESG and DEI and the direct link between them.Discover how companies can shift to a sustainable social and environmental focus.Find out how to get into the ESG and DEI career paths.ResourcesCollibraBlueDotBlueDot Public Benefit ReportsTeach FirstAccentureSetting the Table by Danny MeyerConnect with Melissa on LinkedInConnect with Jay on LinkedInEpisode Highlights[01:56] Environmental Social Governance (ESG) and Diversity Equity Inclusion (DEI) at CollibraESG is about ensuring a sustainable business that’s well-protected for the future in terms of its practices and human resources.Before formally starting their ESG efforts, Collibra's DEI-related work had shifted its focus on corporate social responsibility. They realized that there is a direct link between ESG and DEI.Melissa’s team looks after everything — the planet, people, and economy.[03:48] Employee Resource Group (ERG)Many of Colliibra's appetite for environmental, sustainability, and DEI work has come from their employees.Collibra had the environmental community, Planet Collibra Community, before formally establishing an ESG team.They rebranded ESG to "communities" to focus more on the human touch. Collibra has nine DEI-related communities that foster a sense of inclusion and accountability.[05:08] Shifting to an Environmental FocusThe pandemic has brought the environmental crisis to the forefront of media and industries.There is a direct link between system inequality, systemic change, and environmental inequality. Environmental crises impact marginalized communities most.Collibra's growing sense of environmental responsibility led them to formally establish ESG and DEI into their framework.[06:41] Planet Collibra Community’s Earth Month ProgramsFor Earth Month, Collibra organized an employee-led program aiming to promote environmental consciousness and awareness across the company.At the Reunited Company Employee Conference, employees built a water filtration system to be shipped to a country in need. Planet Collibra focuses on practical, measurable value.[09:10] Collibra Swag StoreCollibra integrates ESG principles across the business into company plans and processes, such as the Swag StoreThe Swag Store is a product of Collibra's partnership with BlueDot. BlueDot only partners with providers who drive environmental change or are part of a marginalized community.The swag includes everything from t-shirts and socks to gadgets.BlueDot provides regular impact reporting to see how much change results from the swag partnership.[12:05] Getting into ESG and DEI Career PathsA business needs to be aligned to the correct stakeholders to utilize ESG and DEI career paths.Intentionally maneuver throughout your current organization and speak to the right people. Then, contribute to key initiatives and ask strategic questions.[13:09] How Melissa Ended Up in CollibraMelissa has always advocated for change, people's rights, and the environment. She studied French and English in college but wanted to get into a field where money is and which she loves.Her first job was as a teacher at Teach First, a nonprofit teaching and leadership academy. It sparked her desire for equality and inclusion.Then, she worked as a management consultant for Accenture, where she got to work out her passions. From there, she moved on to other opportunities that honed her DEI muscle until she found herself at Collibra.[15:46] Melissa’s WorkThe skills you need for DEI, CSR, and ESG are very similar. Passion is only a small part of it.These are all technical disciplines that also require influencing skills.Above relentlessness, it’s the methodology that makes you successful in the  DEI, CSR, and ESG initiatives.Melissa: “A lot of people see these disciplines as the ‘soft side of business’ or they're nice to have, and it's really not like that. It's a very rigorous discipline. It requires a lot of perseverance and a smile to make sure that things move forward.”[17:14] The Technical Components of ESGPart of it is the regulatory components of ESG. There is an increase in regulations from a DEI and environmental perspective.Increased regulation is driving competition. Businesses are getting urged to focus on ESG because of stakeholders’ demands.Melissa: “I think the whole world has kind of got to a stage where it realizes that in order to do sustainable business, you have to make sure you are doing business sustainably. And how can you make sure you're doing business sustainably? Well, you need to make sure that you are thinking about your environmental footprint, your impact on people and the communities you serve, and that you are also making sure you've got a critical business model in place, a resilient business model, which can ensure that you can stand the test of time.”The daily requirements of the job are also technical, i.e., staying on top of regulatory and reporting requirements and customer demands.[19:22] Storytelling in Change ManagementChange is incremental and needs to get driven at a sustainable pace.The storytelling and messaging are crucial. Being specific with what you're achieving can make people realize the change you effect.Melissa: “If people expect us to change the world tomorrow or to get rid of the environmental crisis tomorrow, then that's gonna be very disappointing when we don't do that. But if they see that we are going to take these 10 steps in the next six months, and it's gonna get us to X, Y, Z, then they're motivated. And so that's why storytelling and messaging is so important for me.”Change management is about telling the right story and doing the right things at the right time with the right people.It’s best to be collaborative and facilitative instead of making decisions for people.Being strategic, telling the story, and managing change keep people's passion alive and spearhead success. [22:22] Problems Melissa Dreams of SolvingESG professionals spend a lot of time manually reporting on what they’re doing.Melissa wants somebody to create a reporting mechanism or tool for ESG teams to report in a consistent and standardized way.Her ideal state 50 to 100 years ahead is for ESG and DEI not to exist anymore because it’s just the way to do business.[23:50] Jay’s Key TakeawaysOrganizations with corporate social responsibility, ESG, and DDEI initiatives are increasingly becoming attractive places to work.ESG programs help organizations do good by addressing environmental concerns. Social and governance initiatives help organizations through transparent practices.Weaving ESG and DEI programs together amplify the impact both of them make. Companies implementing these programs can perform better, attract the best talent, and contribute meaningfully to society.About the SpeakersMelissa Mavlanova-August is the Global Head of Equity and Impact at Collibra. She oversees the company's environmental social governance (ESG) and diversity equity inclusion (DEI). In line with this, she leads Collibra's global team in developing the company's internal ESG roadmap. Melissa's vision is to create sustainable and equitable products and help customers use data to change the world.If you want to reach out, you can contact Melissa Mavlanova-August via LinkedIn.Enjoyed 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. You can also share this episode with your friends and family. This episode will help them appreciate and take part in ESG and DEI initiatives that can help us all work for a sustainable future.Have any questions? You can connect with us on LinkedIn. Thank you for tuning in! For more updates, please visit our website. You may also tune in on Apple Podcasts or Spotify.

Over the years, we’ve seen technology grow and how companies use the power of data to drive decision-making. However, we may be gathering more data than we can handle. Some companies may observe inconsistencies among data reports, leading to arguments and a lot of time wasted. This is where data governance comes in.  In this episode, Joseph Wallace, Senior Manager of Data Governance at Adobe, joins us to talk about the importance of data governance, like how it can deter arguments around inconsistent data and improves business processes. He shares how data governance works, and how Adobe has a vision to make trusted data discoverable. He also shares what he believes is the future of data governance and how we must look at data like how we consume water. Tune in to the episode to dive deeper into data governance. Here are three reasons why you should listen to this episode:Understand how data governance is defined, and how it can be used to improve business processes. Learn why Adobe’s data governance is rooted in making trusted data discoverable, and how the company defines trust, data, and discoverable. Discover the water analogy of data governance and how data governance will continue to grow. Episode Highlights[00:57] How Data Governance Started at AdobeAdobe implemented data governance around five years ago. This program started because the company started noticing inconsistencies among data reports. The data governance program began by defining how metrics were created and calculated, and what they mean. The initial point of their data governance program was to avoid arguments over conflicting data by creating an official source of truth.The more the program has grown, it has decreased storage costs and computing costs. It can also drive new insights and new revenue opportunities.  Joe began looking at how many people are looking for data and how long they are looking.  Joe: We've spent 20, 25 years saying ‘data, data, data, gimme the data. I want to analyze the data. We're gonna drive with data. We're gonna do things with data.’ And now we're here with mountains of data and we have no clue what to do with it. We have no real knowledge of where it is and how to use it. What's the most efficient and effective way of using it? That's the real value proposition of data governance. It's protecting it. It's making it searchable. It's helping people use it in the right ways at the right times for the right purpose. [07:06] How To Define Data Governance For Joe, data governance is about making trusted data discoverable. For Adobe, trust means customers are using their products securely and know that if there’s an issue, it could be recovered. Trust also involves operational data used for operational decisions that drive the company. Joe explains that their data governance program is the hub of the wheel. Its spokes include privacy, corporate governance, and legal components.[10:35] How Adobe Defines Discoverable Data Data covers actual tables and columns, assets like IP, and both customer and Adobe content.  Joe prefers the term “digital asset governance,” since data can mean different things to different people. In order to make data discoverable, Adobe uses a trust score and a prioritization model. The trust score looks at how people are using products, and how often. Right now, the prioritization model is undergoing changes to prioritize customer data. [14:30] How Adobe’s Data Governance Team FunctionsInitially, Joe needed to convince people why data governance is important. Now, people are coming into the team on their own. Over time, Joe has created different templates and playbooks built from previous cases. He helps empower teams and people throughout the business to do their own data governance. Joe: “You can't govern it if you don't know it's there. As we build out that catalog and as people add more things, then we can actually truly begin to put the govern in governance.”[17:41] The Water Analogy of Data Governance In the full episode, Joe shares how data is like water. You don’t think about how or where it comes from, you just drink it. Similarly, people need to be able to access data the same way.Data governance – the identification and classification of the – is first. Protection is second. Updating and auditing is third. Data governance never stops since data, and its use, will always change.  Joe shares that governance is about validating that the data is compliant. Joe: “Data should be the same. It should be clean. You shouldn't have to worry about it. You shouldn't have to think about 25 different angles of questions or concerns that you have with it. You just consume it. And that is a really important component of what data governance can provide. It's clean water, clean data.” [21:57] What Joe is Working On Next, Joe will work on tying all the dots together, including the service registry and the business process.  Not only can this ensure you can troubleshoot through components when there’s a technology problem, but this can also improve change management. [27:09] Joe’s Challenges Around Data GovernanceJoe shares that people typically don’t disagree with governance until you ask them to do something for it. His main challenge with the data governance program was convincing people that it was important to do, especially to solve business problems.  [29:30] The Future of Data GovernanceJoe shares that Adobe is a pioneer in data governance. He sees that its capability will expand further. We also need a world data organization similar to how we have one for global health. The problem now is that every country and state has different ways of defining things. About Joe Joseph, or Joe, Wallace is the senior manager of data governance at Adobe and has worked in the company for over 12 years. His specialties include financial analysis, corporate finance, auditing, leadership, and much more!  Joe graduated from Indiana University Robert H. Mckinney School of Law, then worked for an NGO and became an intern at the Federal Bureau of Investigation. He believes all these experiences shape how he sees data governance.  Enjoyed this Episode?If you did, be sure to subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. You can also share this with your friends and family. This episode will inform them of the importance of data ethics and becoming aware of unconscious bias when dealing with data.Have any questions? You can connect with us on LinkedIn. Thank you for tuning in! For more updates, please visit our website. You may also tune in on Apple Podcasts or Spotify.

As companies grow and their market expands, their systems and processes become more complex. Managing data assets can be overwhelming without proper knowledge, organization, and mastery. This is where the concept of a data office comes in handy. In a time when data is more valuable than ever, it is imperative that a company understands how to make it work for them.It might be time for you to consider forming a data office within your company, particularly if your company: is in a position of rapid growth, onboards employees daily, is expanding their market, and/or deals with systems and processes that may be out of date.In this episode, Stijn Christiaens, Founder and Chief Data Citizen at Collibra, joins us to discuss the importance of handling data and starting a data office. He explains what inspired him to begin creating the data office within Collibra, and how this concept may pave the way for future companies. Tune in to the episode to further understand how to build a data office for your business. Here are three reasons why you should listen to this episode: Understand the importance of data in a growing company. Identify if your company needs to build its own data office.Learn from Collibra’s journey of building a data office.Jay Militscher: “It meant to me that data and facts inform whatever point you’re making at the moment. Are you making a recommendation to buy something? Where’s the chart? Meaning data, to back up that decision. Are you delivering a critique on something? Again, where’s the data to back up an otherwise subjective opinion.”Episode Highlights[07:47] More People Means More DataCollibra experienced rapid growth in its company, onboarding more people than the system could handle.As more people filter into the company, more data is added to the system.This increase in staff also implies an increase in customer interactions. [08:19] An Expanding MarketFor Collibra, rapid internal growth meant growth in the market. They needed to streamline their transition from data governance to data intelligence.Stijn believes that the growth in people and in the market means growth in data, which needs to be mastered.Stijn Christiaens: “And, in that sense, we also said, okay, if we set up a data office now because we need it, right? Because systems and processes will also have the added benefits if we do this right to continue to lead our customers. And then you start to experience, really, also what some of your customers experience, right?” [09:58] Leading the WayStijn took on the challenge of accepting the new role of becoming the “data boss” to lead the way not only for Collibra but for future organizations. “Data Office 2025” is realized by Stijn and his team for future organizations that will face similar challenges as Collibra is experiencing. This includes dealing with new data technology and new tools for data stakeholders across the business.Stijn Christiaens: “All organizations, over time, we need to get better at mastering data assets. So all organizations, just like they have a chief financial officer. They will have a data boss or somebody responsible for data and maybe a data office just like their finance and HR, let’s say. So, we saw a trend, and then we said, okay, we can actually do this.”About StijnStijn Christiaens is the co-founder and current chief data officer at Collibra. He’s been involved with the company for 15 years and spearheaded the creation of the data office for Collibra.Enjoyed this Episode?If you did, be sure to subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. You can also share this with your friends and family. This episode will inform them of the importance of data and building a data office for your company’s future.Have any questions? You can connect with us on LinkedIn. Thank you for tuning in! For more updates, please visit our website. You may also tune in on Apple Podcasts or Spotify.

Data is a land mine for growth, and more businesses are realizing the great potential it holds. The value and insights from data have seen a rise in demand within organizations, and with this rise comes the expectation of a rapid turnaround time. However, this poses a significant challenge to central data teams, who handle data management and analytics. This led to the concept of data mesh, a decentralized approach that reduces friction and gives business domains the ability to quickly access and query the data they need.In this episode, Sonali Bhavsar, Managing Director for Global Data Governance at Accenture, joins us to talk about the four pillars of data mesh. She discusses how companies can start applying data mesh to their workflows. Sonali also shares how Accenture helps its clients achieve data-led transformations.Tune in to the episode to know more about data mesh, its significance and some tips to apply it to any business.Here are three reasons why you should listen to this episode:Learn about the four pillars of data mesh.Understand why a federated approach is favored over a centralized system.Discover how Accenture walks the talk in data mesh and data-led transformation.ResourcesBonus track episode on data meshConnect with Sonali on LinkedInEpisode Highlights[00:33] The Four Pillars of Data MeshData mesh is an approach to reduce friction in data workflows in order to maximize the value of data.Its four pillars are data as a product, domain ownership, self-service data infrastructure, and federated computational governance.[03:47] Federated vs. Centralized ApproachA federated approach allows your line of business to make decisions on their operation and what they value to meet regulatory obligations within their jurisdictions.A centralized approach has not been a sustainable model for the longest time. However, it’s most likely to work for an isolated, less hierarchy-driven organization.Traditionally, data governance decisions made outside of the business lineup and restructuring can lead to delays or unwanted results.For more complex organizations, each line of business might need to implement data governance in a certain way that may change or evolve within those lines.[07:14] Self-service Data InfrastructureA big wave of data literacy is happening and the end goal is self-service.Self-service means that the consumption of citizens’ data, whether internally or externally, is built on trust.[08:13] Data Mesh TrendsData mesh is not a new concept, but it’s becoming a hot topic. There is now a stronger awareness of data as a product, which was more theoretical before.The decentralized form of data ownership came about because businesses now see more value in data and want to maximize it.Sonali: “You really want to support that end data citizen to be flexible to use the data that they want to use it as, versus going through permissioning and asking for that data.”Some components will remain centralized. Federated simply means the catalog of data products leans toward business ownership rather than a centralized data ownership. There is a big pivot on determining data quality and its lineage, which affects whether different industries can use data and what data product can or cannot be made from it.[11:59] Businesses’ Data Mesh Readiness Industries such as financial services, insurance, and pharmacy already apply data mesh.High-tech companies are following suit.The line of businesses and the industries they’re in are altogether getting disrupted.[14:34] Readiness to Adopting a Self-service InfrastructureSelf-service is about firms investing in data catalog and data quality tools. Formerly, this was only done to observe regulatory protocols.Financial services have been always ahead of that curve because of regulations. Younger firms are often more flexible to pivot into something new.When you formalize the trust factor when dealing with data, the core pillars of data governance become ingrained as part of your ecosystem.There is now a clear delineation among different departments on how they want to handle data from different perspectives.The ideal situation is that businesses will have a clear responsibility, but also a fluid or gray area.Sonali: “You want data mesh to be sustainable and operational, and keep data mesh as data mesh and not as a data mess down the road.”[22:09] Product Thinking MindsetA product mindset means looking at different domains from an agile point of view and going through them iteratively.Data quality control is standardized to keep track of the data’s lineage.Consumers must be on the same page as businesses that the data product is validated and trustworthy for consumption.Ensure access and security are already validated to avoid bringing in random products that would endanger data consumption.[27:09] Data-led Transformation in AccentureAccenture is going through its own data mesh and transformation regularly.Accenture has built their own data marketplace as an asset that complements what Collibra brings from a catalog perspective.True data marketplace is an important aspect of data-led transformation. Accenture has an entire offering on data-led transformation for their clients across all industries.Sonali: “If the data was not good, AI is never going to be your driver, and writing good machine learning algorithms and AI is amalgamation of your machine learning algorithms.”Accenture believes going through a data-led transformation is their major asset.[29:36] Jay’s Key TakeawaysThe four pillars of data mesh are crucial for treating data as a product.Central data teams can and should still exist. The key is to act as an enabling force for the business.Change is hard; don’t try it all at once.Instead, make sure that the leadership is committed in the long haul. It will take restructuring and investment in skills and scalable technology.About SonaliSonali Bhavsar is the Managing Director for Global Data Governance for Data and AI at Accenture. She helps enterprises reinvent businesses to be data driven and fully utilize their data with the latest thinking and solutions available for advanced analytics, data management, and data governance.If you want to reach out, you can contact Sonali via LinkedIn.Enjoyed this Episode?If you did, be sure to subscribe and share it with your friends! Post a review and share it! If you enjoyed tuning in, then leave us a review. You can also share this with your friends and family. This episode will inform you about the four pillars of data mesh and their importance when bringing data into the marketplace.Have any questions? You can connect with me on LinkedIn. Thank you for tuning in! For more updates, please visit our website. You may also tune in on Apple Podcasts or Spotify.