Secrets of Data Analytics Leaders

Why is Data Quality still an issue after all these years? To get an answer to the prevalent question, Wayne Eckerson and Jason Beard engage in a dynamic exchange of questions which lead us to the root cause of data quality and data governance problems. Using examples from his past projects, Jason shows the value of business process mapping and how it exposes the hidden problems which go undetected under the standard IT lens. In his most recent role as Vice President of Process & Data Management at Wiley, a book publisher, he was responsible for master data setup and governance, process optimization, business continuity planning, and change management for new and emerging business models. Jason has led business intelligence, data governance, master data management, Process Improvement, Business Transformation, and ERP projects in a variety of industries, including Scientific and Trade publishing, Educational Technology, Consumer Goods, Banking, Investments, and Insurance.

Being a change agent is hard. It's tough to inspire people and get them motivated to work on a shared vision. To understand the mechanics of digitalization and tactics required to implement them, Wayne Eckerson invited Andrea Ballinger so that she could share her hard-won lessons from her illustrious career as a technology leader.   Andrea is currently leading a transformation program at LSU, revamping the university’s information technology resources across multiple campuses. Prior to that, she served as Interim CEO and President for the University of Illinois  Alumni Association and CTO of Illinois State University. She began her data career at the University of Illinois where she earned a reputation as the foremost data warehousing expert in higher education.

The road to AI adoption is far more complex than one can imagine. Building data science models and testing them is only one piece of the puzzle. To understand the roadblocks and best practices, Wayne Eckerson invited Nir Kaldero in our latest episode to learn why organizations need to start paying more attention to people, culture and processes to make data science projects a success and how democratization skills pays off in the long run. Nir Kaldero is the Head of Data Science, Vice President at Galvanize Inc. and the creator of the GalvanizeU Master’s of Science in Data Science program. A tireless advocate for transforming education and reshaping the field of data science, his vision and mission is to make an impact on a wide variety of communities through education, science, and technology. In addition to his work at some of the world’s largest international corporations, Kaldero serves as a Google expert/mentor and has been named an IBM Analytics Champion 2017 & 2018, a prestigious honor given to leaders in the field of science, technology, engineering, and math (STEM).

In this episode, Daniel Graham dissects the capabilities of data lakes and compares it to data warehouses. He talks about the primary use cases of data lakes and how they are vital for big data ecosystems. He then goes on to explain the role of data warehouses which are still responsible for timely and accurate data but don't have a central role anymore. In the end, both Wayne Eckerson and Dan Graham settle on a common definition for modern data architectures. Daniel Graham has more than 30 years in IT, consulting, research, and product marketing, with almost 30 years at leading database management companies. Dan was a Strategy Director in IBM’s Global BI Solutions division and General Manager of Teradata’s high-end server divisions. During his tenure as a product marketer, Dan has been responsible for MPP data management systems, data warehouses, and data lakes, and most recently, the Internet of Things and streaming systems.

Recent technology developments are driving urgency to modernize data management. What do you do about architecture, modeling, quality, and governance to keep up with big data, cloud, self-service, and other trends in data and technology? Examining some best practices can spark ideas of where to begin. Originally published at https://www.eckerson.com/articles/stepping-up-to-modern-data-management

Data catalogs have become the centerpiece of modern data management. They are the means to connect self-service analysts with the right data, the “go to” technology for data curation, and the new gold standard for metadata management. With many data catalog tools available, choosing the right data catalog is an important decision.

In this episode, Wayne Eckerson asks Steve Dine about the approach needed to migrate to the Cloud and architecture required to run analytics in the Cloud. Steve Dine talks extensively about the pitfalls to avoid during Cloud migration and finishes off by saying that even though security is a big issue, most organizations will have part of their architecture in the Cloud during the next two-three years. Steve Dine is a BI and enterprise data consultant and industry thought leader who has extensive experience in designing, delivering and managing highly scalable and maintainable modern data architecture solutions.

BI teams often work extremely hard but have little to show for their effort, and they can never get ahead of a continuous backlog of requests. The business rewards their hard work by reducing their budget and staff. Even if they know what needs to be done, they have little authority to make it happen. To succeed, BI leaders need to partner with the business and deliver quick wins to turn the tide of adoption in their favor. Originally published at https://www.eckerson.com/articles/why-bi-teams-struggle-the-tipping-point-of-success

In this Episode, Wayne Eckerson asks Charles Reeves about his organization’s Internet of Things and Big Data strategy. Reeves is senior manager of BI and analytics at Graphics Packaging International, a leader in the packaging industry with hundreds of worldwide customers. He has 25 years of professional experience in IT management including nine years in reporting, analytics, and data governance.

Exploring the evolution of data analyst tools from manual spreadsheets to modern self-service technologies. Importance of integrating data catalog, preparation, and analysis functions for improved productivity. Role of data virtualization tools in enabling versatile data access and integration in analyst workbenches.