If you’re anything like me, you have a love/hate relationship with marketing. Marketing can be delightful, obnoxious or somewhere in-between, depending on content and context. Most of us remember an ad from our youth that has given us a life-long emotional connection to a brand or product. Most of us also remember that obnoxious sales call or email campaign that made us swear never to buy from the offending company again. In this episode of Leaders of Analytics, you will learn from Ikechi Okoronkwo why data-driven marketers have a leg-up when it comes to designing and executing impactful campaigns that hit the right audiences and create delight. Ikechi is Executive Director, Managing Partner and Head of Business Intelligence & Analytics at Mindshare. Mindshare is a global media and marketing agency, and part of global marketing powerhouse GroupM. Listen to this episode to learn: What Ikechi sees as the biggest opportunities in data-driven marketingWhat kinds of analytics to invest in to optimise the impact of your marketing effortsWhat kinds of data is needed to take advantage of these opportunities, and how to collect itHow Ikechi and colleagues use data and analytics to distinguish between rational and emotional reactions to advertisingHow to drive a culture of experimentation and measurement among colleagues and stakeholders who are more creatively than analytically minded, and much more.Ikechi on LinkedIn: https://www.linkedin.com/in/ikechi-okoronkwo-0318579/

Every company, regardless of size, is dealing with a barrage of data. In any typical organisation, there is more information on hand than we know how to use or manage. While every team in the organisation is screaming for analytics professionals to turn data into insight, a strong data and analytics tech stack is foundational to being able to make sense of it all. The need for a robust and efficient data and analytics tech stack has created a sprawling industry for new technology solutions that sell the promise of seamless integration and faster insights. Today, there are a plethora of data and analytics platforms available, most with very high valuations attached to them. But do we really need all these tools to make us super-powered data users? To answer this question and many more related to the data and analytics tech stack, I recently spoke to Benn Stancil. Benn is the co-founder and Chief Analytics Officer at Mode. Mode is a modern analytics and BI solution that combines SQL, Python, R and visual analysis to answer questions for its users. In this episode of Leaders of Analytics, you will learn: What the perfect analytics tech stack looks like and why.Programmatic automation of the analytics workflow.What will cutting-edge analytics tech be able to do 5-10 years from now.Why Been thinks the Chief Analytics Officer role should be redefined, and much more.Connect with Benn Benn on LinkedIn: https://www.linkedin.com/in/benn-stancil/ Benn on Twitter: https://twitter.com/bennstancil Benn's (brilliant) Substack blog: https://benn.substack.com/

In a recent conversation with data warehousing legend Bill Inmon, I learned about a new way to structure your data warehouse and self-service BI environment called the Unified Star Schema. The Unified Star Schema is potentially a small revolution for data analysts and business users as it allows them to easily join tables in a data warehouse or BI platform through a bridge. This gives users the ability to spend time and effort on discovering insights rather than dealing with data connectivity challenges and joining pitfalls. Behind this deceptively simple and ingenious invention is author and data modelling innovator Francesco Puppini. Francesco and Bill have co-written the book ‘The Unified Star Schema: An Agile and Resilient Approach to Data Warehouse and Analytics Design’ to allow data modellers around the world to take advantage of the Unified Star Schema and its possibilities. Listen to this episode of Leaders of Analytics, where we explore: What the Unified Star Schema is and why we need itHow Francesco came up with the concept of the USSReal-life examples of how to use the USSThe benefits of a USS over a traditional star schema galaxyHow Francesco sees the USS and data warehousing evolving in the next 5-10 years to keep up with new demands in data science and AI, and much more.Connect with Francesco Francesco on Linkedin: https://www.linkedin.com/in/francescopuppini/ Francesco's book on the USS: https://www.goodreads.com/author/show/20792240.Francesco_Puppini

Modern analytics teams are central business functions directly and indirectly responsible for increasing revenue, reducing costs, optimising processes and improving customer and employee satisfaction. But there are many obstacles along the way. Data needs collecting, projects need careful design and execution and stakeholders need convincing. Analytics teams are required to cover a wide range of technical knowledge, business acumen and leadership skills to be impactful. What is the recipe for creating analytics teams that deliver impactful solutions and drive real business value? What are the technical, interpersonal and leadership skills required to lead the business through change and adoption of analytics? To answer these questions, and many more relating to the art and science of building excellent analytics functions, I recently spoke to John K. Thompson. John is an international data and technology executive with over 30 years of experience in business intelligence and advanced analytics and author of the best-seller ‘Building Analytics Teams’. In this episode of Leaders of Analytics, we discuss: The hallmarks of an excellent analytics teamWhat a perfect analytics team looks likeThe skills, personality traits and behaviours you need in an analytics teamThe common traits of highly effective analytics leadersHow analytics leaders set themselves up to meet the expectations of business stakeholdersHow to select and prioritise the right projects to work onWhere organisations typically fail when designing analytics teamsThe lowdown on John’s upcoming book, and much more.John on LinkedIn: https://www.linkedin.com/in/johnkthompson/ John's book 'Building Analytics Teams': https://www.packtpub.com/product/building-analytics-teams/9781800203167

Data is eating the world and every industry is impacted. In most modern businesses, customer and employee activities create a plethora of data points and information that can be analysed and interpreted to make better decisions for the business and its customers. Unfortunately, this sounds a lot easier than it is. Despite the huge mountains of data being created, many organisations struggle to get their business intelligence to serve them in the best way. This is not due to a shortage of reports and dashboard floating around – in many cases there are too many ways to get an answer to the same question.  So, why are so many organisations lacking good BI and what should they do about it? I recently spoke to Jen Stirrup to get an answer to this question and many more relating to producing and consuming business intelligence effectively. Jen is the CEO & Founder of Data Relish, a global AI, Data Science and Business Intelligence Consultancy. She is a leading authority in AI and Business Intelligence Leadership and has been named one of the Top 50 Global Data Visionaries and Top 50 Women in Technology worldwide. In this episode of Leaders of Analytics, you will learn how to avoid data paralysis and discover how to create business intelligence that gives your organisation new superpowers. Jen's website: https://jenstirrup.com/ Jen's LinkedIn profile: https://www.linkedin.com/in/jenstirrup/ Jen on Twitter: https://twitter.com/jenstirrup

In my opinion, any organisation with respect for its data should have a Chief Data & Analytics Officer (CDAO) as part of their C-suite. Although the CDAO role is still nascent, business leaders across many industries are starting to appreciate the need for a data and analytics voice at board and executive level. So, what does a CDAO do? How should they spend their time to balance strategic influence with operational delivery of data products? To answer these questions and many more related to the principal analytics role, I recently spoke to Kshira Saagar, who is the Chief Data Officer at Latitude Financial. As the CDO at one of Australia’s largest consumer financial services firms, Kshira is responsible for the end-to-end journey of data through the organisation, from extraction to value creation through data products. He leads a large team of Data Scientists, Data analysts, Data Architects, Data Engineers, Machine Learning Engineers, Data Warehouse Developers, BI Developers and Data Governance experts, who are responsible for bringing the company’s data and analytics strategy to life. In this episode of Leaders of Analytics, we discuss: What a week in the role of a CDAO looks likeHow to secure strategic support and executive sponsorship for analytics projectsWhat’s required of CDAOs and their teams to foster a data literate organisationHow to structure data and analytics functions for successThe future of the CDAO role, and much more.Learn more about Kshira at https://www.kshirasaagar.com/