The Data Chief

Data governance. It’s a “dirty word” in business often associated with being told “no,” but from the perspective of the CDO it’s a crucial part of managing data quality and trust. How are employees being held accountable? Do people have the right access to insights? And is your own business’ data infrastructure and governance policies fostering innovation or stifling it? Ameet Shetty is Chief Data and Analytics Officer at Pilot Flying J, a company that serves more than 1.3 million consumers daily while operating more than 750 locations stateside. On this episode of The Data Chief, Ameet joins Cindi for a conversation on data governance and how to organize your analytics team. Ameet explains why governance gets a bad rap while also touching on the importance of balancing accountability with innovation, having the right technology foundation in place, and the most successful CDOs are natural connectors.Main TakeawaysLean on data as a driver for customer insights and intimacy: Data is key to creating unique personalized touchpoints for your customers. By allowing customers to willingly provide information across all the business touchpoints, this creates a chance to drive insights and move the organizations forward. Companies can use this information to create a stickier connection with the user by providing more personalized experiences in-store or across its apps, but this also gives the business a chance to enhance every touch point and provide a consistent user experience.Building a holistic team pushes you forward: A single individual cannot pull the boat forward, but a team rowing together can get the boat to where it needs to go. When building teams, make sure you are taking a holistic approach and bringing in members from different fields of expertise and backgrounds to close the gap in areas where you are not as strongOver-governing stifles innovation: The term governance is a dirty word for a lot of enterprises, but it’s more important to think about governance not as a burden or regulatory issue but more as data management. It’s important always to maintain data quality, but you must have a balance because you don’t want to govern your data to the point that it stifles innovation.About AmeetAmeet Sheet is the Chief Data Officer at Pilot Flying J. Prior to joining Pilot, Ameet served as McDonald’s first Chief Data Officer. Ameet is helping to define and infuse data across the global enterprise.  He is creating the roadmap to identify the technology, team, process and culture change required for enabling enterprise data transformation and establish best-in-class processes for data strategy and governance and evangelizing these changes throughout McDonald’s.Prior to McDonald’s, Ameet was the Chief Data & Analytics Officer for SunTrust Banks, Inc.  In this role, he led the Enterprise Data & Analytics office, with responsibility for driving the strategic vision and effective deployment of data and business intelligence capabilities to improve efficiency, reduce risk, and enable strategic business growth.Ameet earned an MBA in Marketing from Georgia State University and a Bachelor’s degree in Finance from the University of Georgia.  --The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

No journey to the cloud is the same. While some will encounter similar obstacles, each journey has its own unique challenges. But what happens when a company born in the midst of a crisis and changing technology, has to innovate just as fast as the changing landscape to keep up?Ryan Graciano is the co-founder and CTO of Credit Karma, a company that is aligning technology and data to help bring transparency to the credit lending process. On this episode of The Data Chief, Ryan explains how Credit Karma survived early struggles such as the financial crisis of 2008. Ryan also touches on how Credit Karma navigated it’s journey to the cloud, stepping away from the comfort of on-premises data centers to the elasticity of the cloud, and the importance of grooming outside data sources to keep insights consistent. That and more on today’s episode with Ryan Graciano.Main TakeawaysExplainable algorithms drive success: As third party datasets become more readily available, there is an evolving need for data professionals to understand where that data is coming from and how it will affect your models. While these datasets can make it easier for models to be spun up quickly, you must be able to account for how and why those algorithms are generating particular answers.Clean data leads to reliable answers: Data analysts must spend time making sure the data they are using is not only clean, but reliable. When an analyst uses dirty or untrustworthy data, algorithms will have a tendency to run in an undefined manner, which will lead to high variance in answer quality and consistency.Keep data fluency a priority: Even for organizations that believe they are data literate, the process of understanding data at an organizational level is an ongoing one. A best practice for maintaining data literacy is to create a standardized set of how data is recorded and reported internally. When practices like this are standardized, organizations can avoid issues like data bias.About RyanAs a co-founder of Credit Karma and Chief Technical Officer, Ryan Graciano has grown the company’s engineering department from a one-man band into a team of hundreds, developing a technical framework to support the company’s rapid growth. His expertise and innovation has helped bring new levels of usability and sophistication to financial services technologies.Today, Ryan runs an ever-expanding group of engineers tasked with building out new products at pace while stressing a culture of agility and experimentation, even as Credit Karma reaches new levels of scale. As a leader, he serves as a constructive agitator, looking to break down traditional workplace hierarchies and empowering each member of his department with real influence over the future of the product.Ryan has a Bachelor's degree in Computer Science from the Georgia Institute of Technology and spent five years at IBM before joining Credit Karma.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

The role of the Chief Data Officer is an evolving one. Today, data professionals are expected to be champions for their business  – aligning data goals with business values – while also leading their company’s digital transformation. It’s a position best suited for visionaries, advocates, and change agents.  Darren Pedroza is the Vice President of Enterprise Data and Analytics at First Command Financial Services, with a mission of helping military families reach their financial goals. In addition to being a data and analytics savant, a major part of his success in this role is his acute understanding of how to transform a data strategy to keep pace with changing times and business needs. On this episode of The Data Chief, Darren explains how First Command transformed its data and cloud strategy to be more flexible, agile, and democratized. Darren also touches on a host of topics, including Databricks, what routinely leads to bad data, and leadership best practices.Main TakeawaysFuture-proof your cloud strategy: Your cloud data strategy shouldn’t end at scale. Focus on flexibility, agility, and democratization by adopting as many cloud-native tools as needed and consistently upskilling non-technical business users. Additionally, you want to be intentional about your build vs. buy strategies and make sure the vendors you partner with become allies.Remember that good data doesn’t just happen: All data has a lifecycle, but there are two unique challenges that plague companies when it comes to their data collection: silos and poor user experiences. The best data collection applications are the ones that have a simple workflow, and a clear and pleasant user experience.Align your team to your tech stack: When going through digital transformation it’s important to make sure that not only are you partnering with vendors that can integrate across multiple platforms, but also compliment the skillset of your team at hand.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com. -- For full show notes and more, go to thedatachief.com.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

In the age of data-driven decision making, an adage still bears true: People are a company's most valuable asset. No matter how technologically advanced and forward thinking your company is, it cannot operate without the individuals that make the organization go. So how are companies using data and analytics to not only make better decisions at the company level, but also improve the employee experience? And how are data and analytics predicting trends for the future of work that includes employee well-being and greater inclusivity?Serena Huang is the Global Head of People Analytics at the Kraft Heinz Company. On this episode of The Data Chief she shares insights into her work and why companies are turning to this important function to design more thoughtful employee experiences. Enjoy!Main TakeawaysStart with the problem, not the data: When solving a problem, don’t start with your data. Instead, understand what solution you are trying to solve for and then design your experiments around that problem. Once that’s in place, you can start gathering directional data that will lead to a solution. Share your progress and momentum: Transparency is key, so when you are conducting your analysis make sure the data you are collecting from employees not only benefits the company, but also the employee itself. If your employee feels as if the line of questioning does not benefit them, they are less likely to participate. Your data gathering process must be a two-way street that shows results both for the employees and the company.Create value beyond the obvious: Data and analytics should always be on the lookout for new ways to bring value to the business. For Kraft Heinz, this meant measuring different scenarios such as exit interviews, engagement surveys, and understanding why employees left, to create a more holistic view of the employee experience.About SerenaDr. Serena Huang is currently the Global Head of People Analytics at the Kraft Heinz Company. Serena is a thought leader in people analytics, HR technology, future of work, and employee experience with deep expertise spanning large multinationals including GE and Deloitte. Her recent interviews appeared on Workforce.com and Rallyware. Dr. Huang is also a long-time practitioner of mindfulness and leads guided meditations in corporate settings to boost employee well-being.As a data analytics executive, Dr. Huang is passionate about leading change, building high-performing global teams, and helping business leaders see data as an asset in large organizations. She excels at showing executives the “art of the possible” through both 1-on-1 dialogues and facilitated hands-on workshops, and co-creating customizable, scalable solutions in predictive analytics in HR, Workplace Strategy, Supply Chain and Litigation domains. Dr. Huang has built and led on-shore/off-shore analytics teams and capabilities from the ground up in highly matrixes multi-national corporations over the past 10 years. She welcomes global opportunities outside the U.S. or U.S. companies with significant global footprint.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com. -- For full show notes and more, go to thedatachief.com. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

The restaurant industry has been one of the hardest hit industries over the last year. Amid countless closures and reopenings, restaurants have overcome many obstacles in an effort to survive. Through these struggles, restaurant professionals have turned to data to optimize everything from takeout orders to new layouts, all the way to analyzing market recovery. Grant Parsamyan is the Senior Vice President for Data and Analytics at OpenTable, an online restaurant reservation service that is empowering restaurants of all sizes to operate more efficiently through the use of technology. On this episode of The Data Chief, Grant dives into OpenTable’s State of the Industry site, designed to illustrate how COVID-19 has impacted restaurants through powerful data storytelling. Grant and Cindi also discuss the importance of data literacy, and picking the right analytics tools to match business use cases. Enjoy!Main TakeawaysMeasuring success and proving value: Measuring success or measuring value from data and analytics is a difficult proposition. A recent study suggests less than 14% of businesses go back to do an ROI study, so it’s incumbent on data professionals to continuously be capturing anecdotes of the businesses benefits to prove value over time. A best practice for measuring value is to set a baseline and make sure that you pick the right tool to advance your use case and then measure that baseline to provide the value of those investments to gain the credibility to advance your analytics.Decline of the dashboard: The role of data professionals is becoming less about developing dashboards and more about creating tools that empower users to answer their own questions. Because data flows at such a quick pace, predetermined views and dashboards are often outdated as soon as they’re created.Data sharing leads to quicker results: Data sharing is enabling customers to monetize data without the messiness of manual file transfers. By being able to share data from one platform to another, data professionals are not constrained by time and volume.About GrantGrant Parsamyan serves as the Vice President - Data Engineering and Analytics of OpenTable. Grant started at OpenTable in March of 2017. Grant currently resides in the Greater Los Angeles area.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com. -- For full show notes and more, go to thedatachief.com.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Data and the power it wields has made its way into every industry over the last decade. From entertainment to real estate, all the way to the fashion industry, companies leading their industries are using data to create uniquely personalized digital experiences.Brad Klingenberg is the Chief Algorithms Officer at Daily Harvest, the direct-to-consumer brand that helps stock your home with fresh, plant-based foods. Brad leads the data team and is charged with using data and algorithms to create meals Daily Harvest customers will enjoy and keep coming back for. On this episode of The Data Chief, Brad and Cindi discuss the importance of aligning your customers’ wants with business value to create unique experiences, and how to go about sourcing data to get the desired outcomes. Brad also dives into his previous work at Stitch Fix, and provides insights on how to scale data teams and foster a data culture. Enjoy!Main TakeawaysThe personalization promise to customers: Customers aren’t giving you their data for free. They’re doing it so your business can get to know them in ways that make sense, and to use that information to create more personalized experiences for them. When the customer trusts what you’re going to use their information for, you have an opportunity - and obligation - to create a unique experience that is both beneficial for the customer and the business.Tools to solve data bias: It’s quite easy for biases to be introduced into your algorithms through the data that is used. While there is an emerging set of tools to help diagnose and evaluate data bias, it’s a hard problem to solve, and one that requires getting to the root - the data itself. Everything starts with the data you have. Data teams need to put an emphasis on the diversity in their data to recognize gaps and biases.Building a data-driven culture: Never before has it been more important for companies to champion a data-driven culture. Leaders need to lead by example in this shift. At the same time, data functions have a special role to play in helping companies reason with uncertainty, understand measurement and experimentation.About BradBrad Klingenberg is the Chief Algorithms Officer at Daily Harvest, the direct-to-consumer brand that helps you stock your home with clean, delicious food built on real fruit + vegetables and ready in minutes. Brad leads the data team and is charged with using data and algorithms to tailor the Daily Harvest experience to individual food values and taste preferences through the co-creation of food and digital personalization.Prior to Daily Harvest, Brad was the Chief Algorithm Officer at Stitch Fix, where he oversaw a team of more than 140 data scientists and engineers. As the leader of the Algorithms team, Brad was responsible for developing and improving the core algorithmic capabilities that leverage data to power Stitch Fix.Brad has also served as an advisor/consultant for Candidate Labs, Udacity, Opendoor.com, and Netflix. He currently lives in Boulder, CO with his family and holds a PhD from Stanford University, as well as a Bachelor of Science - Master of Science dual degree from University of Colorado at Boulder.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com. -- For full show notes and more, go to thedatachief.com. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

“Garbage in, garbage out.” It’s a philosophy every data leader is familiar with. Your algorithms and models are only as good as the data you put in them -- so how do you ensure the data you are leveraging is reliable and trustworthy? Joining Cindi today is Opendoor Co-founder and CTO, Ian Wong. Opendoor is on a mission to remove the guesswork from homebuying, and in this episode, Ian details how the company’s algorithms provide future homebuyers peace of mind about getting the best possible offer for their home. Ian explains how the team harnesses multiple data sources and uses machine learning to maintain a competitive advantage. Plus, Ian and Cindi discuss how to turn those valuable data insights into measurable business results. All that and more on today’s episode with Opendoor’s Ian Wong.Main TakeawaysTrust in the numbers: All great algorithms start with great data, but having a high fidelity of data is one of the key differentiators for any high-performing model. When you’re mixing first-party data with third-party data, be intentional about how you create strategic data models that fit your business. Data scientists need to hone business skills: As a data professional, it’s not enough to have a breadth of technical skills, coding, algorithms, statistics, and mathematics -- you must also have a firm grasp of business needs with solid communication skills. Remember: your research is not helpful if it does not meet the immediate needs of the business. Being able to find that balance is an integral skill for any young data scientist looking to break into the field.Fail fast and experiment: When it comes to machine learning, there's a lot of opportunity for failure. Launching a prototype quickly and iterating as you go  is the name of the game. It shouldn’t take a quarter to make and deploy a new algorithm. The more time between inception and deployment, the less likely you will be able to use the insights gathered. Stay agile, move quickly, and follow the data.About IanIan Wong is the co-founder and Chief Technology Officer of Opendoor, where he is responsible for the development of product and technology. Ian is building a team of engineers, data scientists, product managers and designers to modernize the real estate industry. He was previously pursuing his PhD in electrical engineering at Stanford when he left to join Square as their first data scientist. At Square, Ian developed tools and algorithms to handle risk. He has earned Masters degrees in electrical engineering and statistics from Stanford University. As a mission-driven real estate marketplace that radically simplifies home buying and selling, Opendoor has been used by over 85,000 customers in more than 25 metros nationwide.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Ajeet Singh is a risk taker. There’s no other way to describe someone who's done the things he has and accomplished so much in such a short amount of time. An immigrant, entrepreneur, and and most importantly a disruptor, Singh has constructed two multi-billion dollar entities from the ground up. Throughout his journey, he’s been guided by two principles: his out-of-the-box thinking and curiosity about how he can improve people’s lives.As a young entrepreneur working in Silicon Valley during the big data days, Singh noticed the data and analytics space was ripe for disruption. So he did something about it. First with Nutranix and now with ThoughtSpot, where he's working to solve some of the world's biggest problems by democratizing data for all. On this episode of The Data Chief, Singh, Co-founder and Executive Chairman at ThoughtSpot, dives into some of the biggest challenges facing CDOs in 2021, why organizations must empower their leadership teams to drive meaningful change, and how big tech can be utilized for good moving forward.Main Takeaways:- The cloud is here to stay: Large enterprises are increasingly moving their data to the cloud. The challenge now for CEOs and CDOs is not “if” they will adopt cloud but “when,” and how quickly they can get there while maintaining their current momentum.- Empower your leaders to drive change: It’s easy to create new C-level positions, but real innovation and transformation starts with empowering your leadership with the required mandates and resources to empower their teams.- Build your culture with intention: Every organization inherently has a culture and you must be deliberate about how you build that culture. Every department should reflect your core principles and create a space for individuals and teams to thrive.About AjeetAjeet Singh is the co-founder and Executive Chairman at ThoughtSpot, a company revolutionizing analytics with search and AI. Driven by his passion for creation, Ajeet has built two multi-billion dollar technology companies from the ground up - ThoughtSpot and Nutanix. Prior to starting ThoughtSpot, he was a co-founder and Chief Products Officer at Nutanix, the leader in the enterprise cloud industry and largest tech IPO of 2016. Prior to Nutanix, Ajeet learned the ropes of enterprise technology startups as the Senior Director of Product Management at Aster Data, later acquired by Teradata for $300M. Ajeet has also held business and technical roles at Oracle, where he was part of the team that first launched Oracle Database to the Amazon EC2 cloud. Ajeet holds an MBA from the Indian Institute of Management, Calcutta, and a Bachelor of Science in Chemical Engineering from the Indian Institute of Technology, Kanpur, where he graduated at the top of his class.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Much like a roller coaster, 2020 was full of many loops, twists, and turns. From accelerated digital transformations to expedited migrations to the cloud, you were asked to do it all— often with far less time and resources. Through it all, The Data Chief was right there with you, along for the unprecedented ride. From the beginning this podcast had a vision: To bring you learnings and best practices from the brightest minds in our industry to help you all become better data stewards. On this episode of The Data Chief, we look back at some of the key themes from season one, including the rise of the CDO, the intricacies of aligning your department’s goals with that of the businesses, and how you coped with accelerated timelines. While we relive these important conversations, we also discuss why culture and data fluency continue to be the biggest hurdles to becoming a truly data-driven business.Main TakeawaysThe Rise of the Data Chief: The role of the CDO now goes beyond getting your data house in order. You must become a true analytics leader and business partner by developing a deep understanding of how to properly build a team and nurture strategic partnerships.Aligning with Your Business Values: Data is the lifeline of every organization but in order to achieve buy-in from your stakeholders, your data and analytic investments have to be aligned with the goals of your company. This means asking what projects are right for your team to pursue and which ones make the most sense for the overall direction of the organization.Rapid Technical Innovation and the Shift to Cloud: How we store and manage our data is changing rapidly. Many companies are moving their data to the cloud and their vendors are often the ones helping drive this change.Technology Reflects Culture: Technology and culture are two sides of the same coin. A culture of fear, protecting the status quo, and settling for “good enough” often engenders legacy tech saddled by inefficient processes. At the other end of the spectrum, organizations who are embracing cloud and augmented analytics are empowering new decision makers at the speed business demands.Assessing your Data Fluency: Investing in data fluency and partnering with business stakeholders to build these skills across your organization is part of your mandate as a Data Chief. As an industry, we need to flip the emphasis from technical training to using data in a business context.About CindiCindi Howson is an analytics and BI expert with 20-plus years’ experience and a flair for bridging business needs with technology. Cindi was previously a Gartner Vice President in data and analytics, lead author of the Analytics and BI Magic Quadrant, data and analytics maturity model, as well as research in data and AI for good, NLP/BI Search, and augmented analytics. She introduced the BI bake-offs and innovation panels at Gartner events globally and is a popular keynote speaker. Prior to this, she was the founder of BI Scorecard, a resource for in-depth product reviews based on exclusive hands-on testing, a contributor to Information Week, and the author of several books including Successful Business Intelligence: Unlock the Value of BI & Big Data and SAP BusinessObjects BI 4.0: The Complete Reference. She served as The Data Warehousing Institute (TDWI) faculty member for more than a decade. Prior to founding BI Scorecard, Howson was a manager at Deloitte & Touche and a BI standards leader for Dow Chemical. She has an MBA from Rice University and a BA from the University of Maryland.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com. -- For full show notes and more, go to thedatachief.com. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Joining Cindi today is Ruha Benjamin, a professor of African American Studies at Princeton University and the founding director of the IDA B. WELLS Just Data Lab. She has studied the social dimensions of science, technology, and medicine for over 15 years and speaks widely on issues of innovation, equity, health, and justice in the U.S. and globally. Ruha is the author of Race After Technology: Abolitionist Tools for the New Jim Code and People's Science: Bodies and Rights on the Stem Cell Frontier, and the editor of Captivating Technology: Race, Carceral Technoscience, and Liberatory Imagination in Everyday Life.In this episode, Ruha and Cindi discuss how flawed data can have disastrous, real-world consequences for women and people of color. Ruha also describes a multidisciplinary approach to recognizing and refurbishing the processes for gathering and governing data.Key Takeaways:The least apparent bias is often the most dangerous. We can't prevent the consequences of bias or even take it seriously if we're not aware of it — or worse, choose to ignore its less obvious manifestations.Widen the lens and don't settle for 'happy talk.' Diversity is not the status quo for most organizations, therefore it should make us uncomfortable. If it’s not, it may be a sign that you’re stopping the conversation short.Focus on building the right team before you start building AI systems. Diversity needs to start from the groundwork that happens before the foundation is poured."Big me up." Surround yourself with role models and people who build you up rather than tear you down — and be a support system for them as well. More About Ruha:Ruha Benjamin is a professor of African American Studies at Princeton University and the founding director of the IDA B. WELLS Just Data Lab. She has studied the social dimensions of science, technology, and medicine for over fifteen years and speaks widely on issues of innovation, equity, health, and justice in the U.S. and globally.Ruha's second book, Race After Technology: Abolitionist Tools for the New Jim Code, examines the relationship between machine bias and systemic racism, analyzing specific cases of “discriminatory design,” and offering tools for a socially-conscious approach to tech development. She is also the editor of Captivating Technology.Ruha also recommends the workbook, Advancing Racial Literacy in Tech.--The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com. -- For full show notes and more, go to thedatachief.com. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.