CALL FOR SPEAKERS: If you are interested in speaking at one of our 2018 meetings, please let us know here.
Next meeting is on April 19, 2018. Click here to register on EventBrite!
Location: Innovation Pavilion, 9200 E. Mineral Avenue, Centennial, CO 80112
We are excited to have two great presentations from local professionals in the Denver community. We have the unique opportunity to hear from individuals that have lived through very pertinent projects locally.
Title: The Trials and Tribulations of implementing a Business Glossary at JeffCo Public Schools: Lessons Learned
This discussion will present part of the “journey” of data governance at Jefferson County Public Schools; the challenges, the successes, the not so successful, and our future opportunities. We have a Data Governance Council and a great core team of Data Stewards but our initial Glossary implementation was based on using what tool we had on hand, not an intelligent analysis. This presentation will share our journey from chaos to a solid base that we are now leveraging including how to start a data governance program, picking the right data steward, the challenges of a wrong product fit, selecting a data governance product and the trials of installation.
Michael Armbruster is the Manager of Data Quality in Ed Tech Support for JeffCo Schools. His background includes over 25 years in IT focusing on data, including management, data governance and architecture, as well as technical data roles in health care, telecommunications, state government, aerospace, finance, and transportation. Michael has presented on data quality at both DGIQ and EDW. Michael’s educational credentials include a Masters in Information Systems from the University of Denver and he is a Certified Data Management Professional (CDMP) at the Mastery level.
Title: Case Study: Managing Highly Transactional Data in Digital Advertising
Every single time you load a webpage, you create hundreds of unique data points that are sent to multiple ad platforms. Effectively managing and understanding these transactions at scale has been key to the growth of the industry, which has just overtaken TV advertising in annual spend.
In this presentation, Manny Puentes will explain how this data is created and share the technologies used to store and manage highly transactional data and give real world examples of operational considerations leveraging technologies such as MapR, Cascading, and Druid.
Manny Puentes is an experienced executive leader in the digital advertising and software industries. He is the founder and CEO of Boulder-based startup Rebel AI. Rebel AI secures digital advertising using machine learning, blockchain, and encryption technologies. With more than 20 years of experience in digital advertising, Manny has led engineering and product teams to build a number of enterprise-scaled platforms for digital media trading by leveraging specialties in real-time bidding, data pipeline architecture, natural language processing, and machine learning.
Arrow Electronics Headquarters, 9201 E. Dry Creek Rd., Centennial, CO 80112, Room: 131
View in Google Maps
Parking information: Attendees should park their vehicles on the 5th floor of the Panorama building parking garage (9151 E. Panorama Circle, Centennial, CO) which is located across the road from Dry Creek HQ and and walk across to the front desk of the Dry Creek Building. We will have badges for everyone at the front desk.
Title: “The Role of Data Quality for Effective Merchandising in High Tech eCommerce”
Abstract: The complexity of electronic component data in the high-tech industry is orders of magnitude higher, compared to conventional retail. As the industry encounters disruption in the form of increasing online omnichannel ecommerce, there is an emergent need for ensuring marketability of millions of electronic components, maintaining complex and multiple-business focused product data and robust and scalable content management strategies.
The rise of the PIM platform for localized and flexible data quality management and as a holistic master data management tool has provided a tool for supporting customer focused marketing initiatives, as well as serving as a long term strategic platform for marketing and asset intelligence capabilities. The addition of a strategic marketing/asset intelligence layer to the PIM platform provides a potent and comprehensive solution for flexible and effective support for the disruptive nature of rapidly digitizing eCommerce. This intelligence also provides business and customer synergy by closely tracking business needs and providing inputs to the PIM system.
The combination of a powerful and flexible data management (PIM) platform with clear strategic vision and business alignment would serve as the foundation of an effective eCommerce organization and maintain the competitive advantage in a vertical undergoing rapid disruption.
– Complexity of Data compared to conventional retail business
– Importance of Data for Digital Transformation
– Necessity for a PIM platform
– Marketing/Asset Intelligence and Customer Alignment
– Data Quality Flywheel for Continuous Improvement
Bio: Pramit is the Data Strategy and Operations Manager for Arrow Digital, currently managing the commerce and merchandising focused data operations and strategic initiatives as part of the larger transformation initiative for Arrow Digital. His team is responsible for implementing effective merchandising strategies, ensuring part data quality and operational integrity of ecommerce data and for supporting the business and product teams across Arrow Digital.
He has 10+ years of experience as a business intelligence and data specialist across a range of verticals such as high tech, oil and gas, retail and academia. He has a master’s degree in Electrical and Computer Engineering from Colorado State University, Fort Collins and a bachelor’s degree in Electronics and Telecommunication Engineering from Utkal University, India.
Title: “Transforming BI with Data Science and Machine Learning – Understanding how Business Intelligence differs from Data Science and Machine Learning trends”
Abstract: Data science projects have increased in adoption for their business value derived from new data products and embedding analytics in real-time business processes. However, many people fail to see how data science, machine learning and AI are a fundamental shift in how business intelligence has delivered analytics for many years. Each serves different purposes in the business and require different methodologies and skills to perform effectively. This presentation will clarify the terminology, definitions, relationships and methodologies for each. Topics covered include: spectrum of analytics capabilities, relationships, definitions and maturity, a very different approach to solving business problems, why data scientists are called unicorns and how data science teams work. We’ll also discuss what is machine learning.
Bio: With over 25 years of experience delivering value through data warehousing and BI programs, John O’Brien’s unique perspective comes from the combination of his roles as a practitioner, consultant, and vendor CTO in the data industry. As a recognized thought leader in data strategy and analytics, John has been publishing articles and presenting at conferences in North America and Europe for more than 15 years.
His knowledge in designing, building, and growing enterprise data systems and teams brings real-world insights to each role and phase within a data program. Today, John provides research, strategic advisory services, and mentoring that guide companies in meeting the demands of next-generation information management, architecture and emerging technologies.
Location: Jeffco Education Center, 1829 Denver West Drive, Building #27, Golden, CO 80401 View in Google Maps
First Speaker: Jed Summerton, Managing Director, Data Mindset, LLC
Title: “How to Tell Data Stories”
Abstract: In the digital economy, data is the new oil. Discovering a new insight from analyzing data is exciting – and just the beginning of the road to improvements in organizational performance. Getting started on that road requires by presenting your data with a story that is compelling and builds support for your plan (and your career).
This overview of data storytelling will cover how to marshal your discovery into relevant points – the What, the So What, and the Then What – and how you can deliver them as a narrative to any audience in a way that resonates and inspires people to action.
Bio: Jed Summerton is a senior leader of business analytics, specializing in applying the insights of data sciences to improve organizational performance. As a consultant he has served over 100 companies in developing and operating large-scale data and analytics systems in health care, telecommunications, financial services, manufacturing and retailing.
He has extensive experience as an IT executive in large, international IT organizations, including DaVita, GE Capital, Level 3 Communications, Qwest (now CenturyLink), CaridianBCT (now TerumoBCT) and Group Health Cooperative.
He has served as a faculty member of The Data Warehousing Institute and currently teaches in the MBA and MSBA programs at the Daniels College of Business at the University of Denver, where he also chairs the advisory board for the department of Business Information and Analytics.
Summerton has earned several industry awards for IT innovation and best practices.
First Speaker: Peter Aiken, Founding Director and Owner, Data Blueprint
Title: “Exorcising the Seven Deadly Data Sins – Improving data investments”
Abstract: The difficulty of implementing a new data initiatives often goes under-appreciated, particularly the challenges facing most organizations. Deficiencies in organizational readiness and core competence represent clearly visible problems faced by data professional, but beyond that there are common cultural and structural barriers that must be eliminated in order to leverage data effectively. This talk will discuss these barriers—the titular “Seven Deadly Data Sins”—and in the process will also:
– Elaborate upon the three critical factors that lead to data initiative failure
– Demonstrate a two-phase data strategy implementation process
– Explore the sources and rationales behind the “Seven Deadly Data Sins,” and recommend solutions and alternative approaches
In this manner data investments can be more accurately focused on your organization’s strategic priorities. Only when past the prerequisites, can organizations develop a disciplined, repeatable means of improving the data literacy, processes, and supply – the three key elements required to improve data support for strategy. Think of it as a repeatable process for identifying and removing data constraints.
Bio: Peter Aiken is an acknowledged Data Management (DM) authority. As a practicing data consultant, professor, author and researcher, he has studied DM for more than 30 years. International recognition has come from assisting more than 150 organizations in 30 countries including some of the world’s most important. He is a dynamic presence at events and author of 10 books and multiple publications, including his latest on Data Strategy. Peter also hosts the longest running and most successful webinar series dedicated to DM (hosted by dataversity.net). In 1999, he founded Data Blueprint Inc, a consulting firm that helps organizations leverage data for profit, improvement, competitive advantage and operational efficiencies. He is also Associate Professor of Information Systems at Virginia Commonwealth University (VCU), past President of the International Data Management Association (DAMA-I) and Associate Director of the MIT International Society of Chief Data Officers. Peter also hosts the longest running and most successful webinar series dedicated to DM (hosted by dataversity.net). In 1999, he founded Data Blueprint Inc, a consulting firm that helps organizations leverage data for profit, improvement, competitive advantage and operational efficiencies. He is also Associate Professor of Information Systems at Virginia Commonwealth University (VCU), past President of the International Data Management Association (DAMA-I) and Associate Director of the MIT International Society of Chief Data Officers.