November 7, 2022

December 2, 2022 | The Evolution of Data Architecture in the Cloud | Beyond a Data Catalog: Improving a Data User’s Experience with Metadata

Topic 1: The Evolution of Data Architecture in the Cloud

Speaker: Eric Lealos


The state of the art for engineering in analytics has evolved significantly over the past 25 years. Early on the practice of data modeling emerged as a means to improve performance and make data more accessible and easier to use for authors, analysts and creators. Since the early days much has changed. On the technology side, we have seen advances in traditional relational databases to support analytics, the invention of databases designed specifically for analytics, analytic appliances, and now modern databases in the cloud, designed not only for analytics, but to streamline many of the workflows commonly used to engineer data.

There has been a similar evolution in the way companies use and expect to use data, analytics and tools. We have seen companies start with reporting, with cobol programs creating printed reports, literally distributed in mail boxes to a small number of users based on page ranges, to automating reporting and distribution with BI software, to creating enterprise reporting and analysis platforms that support reporting, ad hoc data access, and more advanced analytics, to establishing platforms that provide data not just for reporting, analysis and advanced analytics, but for ad hoc exploration and analysis, automating workflows and sophisticated operational activities.

Through all of these changes, I have found that many things have changed, and many have stayed the same. Massive improvements in performance have enabled different design patterns in ETL, and different physical models at the database level. Meanwhile usage patterns have taken advantage of these improvements and have driven different approaches to designing and approaching data warehouse workflows to make complicated tasks easier. All of these developments have created opportunities for new applications and tools to help data and analytics engineers create more value. I will walk through some of the significant evolutions in this industry over the past 20 years and connect them to the most significant changes I have seen in the state of the art of data modeling, ETL architecture, and data/analytics engineering.

Topic 2: Beyond a Data Catalog: Improving a Data User’s Experience with Metadata, Innovation and Trust Unlocked: Why Modern Data Catalog Approach Matters to Your Business

Speakers: Mark Phillips and Nik Acheson


Mark Phillips – Beyond a Data Catalog: Improving a Data User’s Experience with Metadata… Data catalogs are at the center of many organizations’ data initiatives with promises of data discovery, understanding, and trust and yet we often fail to use metadata as intended – an enabler of user satisfaction. In this presentation, we’ll explore how shifting our mindset about metadata and can accelerate data initiatives and help answer a critical question, “how can we improve a data user’s experience?

Nik Acheson – Innovation and Trust Unlocked: Why a Modern Data Catalog Approach Matters to Your Business… Contemporary data catalogs have massively evolved in recent years and the benefits are no longer being delivered for just technology teams. This presentation will break down the contemporary data catalog into a few key areas, what you should expect out of them, and how to begin delivering more Trusted business value while evolving architecturally. Examples to be shared include technologies, past experience from enterprise implementations across different industries, and others to help you navigate where you should start or scale next.

About the Speakers:

Eric Lealos:

Eric Lealos has worked in the data and analytics industry for approximately 25 years. He got his start as a software engineer at Information Advantage, one of the original Decision Support Software providers in the world. Customers included 3M, Target, Albertsons, and SuperValu. From there he went on to work in professional services for Cognos, leading projects at UnitedHealth Group, Boeing and LeapFrog. After leaving Cognos he went on to found Quantified Mechanix, a professional services, consulting and software firm in Minneapolis, which has been in business for nearly 20 years. Quantified Mechanix helps clients integrate and architect data, create data flows and create meaningful content from cloud and on premise applications to create analytics that improve business performance.

Eric has an undergraduate degree from the University of Vermont, and an MBA from the University of St Thomas. He has also been trained by Ralph Kimball, receiving certificates for Dimensional Modeling in Depth, Data Warehouse in Depth, and ETL Architecture in Depth through the Kimball Group. Eric is still a hands-on developer and really enjoys working with talented technical people and talented business people to create simple, elegant and effective solutions.

Eric Lealos articulates the “Evolution of Cloud Data Architectures in recent years and considerations for NOW!

Mark Phillips- Senior Consultant – Slalom Consulting

Mark Phillips is a consultant and leader in data management responsible for Metadata Management and Data Auth capabilities at Slalom Consulting. An avid problem solver with a breadth of experience, Mark has delivered data driven solutions across industries in data management and strategy, data viz, and data engineering. He is passionate about crafting human centered solutions that provide timely access and enable insight.

Mark Phillips discusses Data Catalog best practices followed by Nik Acheson’s, who articulates the Modern Data Catalog approach.

Nik Acheson- Field Chief Data Officer

Nik is a Customer, Mission, and business obsessed product and enterprise architecture leader with deep experience leading both digital and data transformations. Over 15 years of experience driving innovation and scale in complex enterprises such as NSA (National Security Agency), Philips, Concur, Nike, AEO, and Zendesk. Presents at conferences & meetups on advanced areas of Data & Analytics such as Data Mesh, Data Fabric, Distributed Intelligence/ Analytics, AI/ML & Data Science, Data Governance, Information Security, Personalization, 360 data strategy (product, customer, content, partner), and others.

Passionate about building, growing, and/or turning around teams and organizations by modernizing business, technology, process, and culture. Focuses on enabling data as an intelligent asset to help improve the lives and personalized experiences of customers, direct impact of teams, and rigorous & transparent prioritization. Have led portfolio and agile transformations and teams (including introducing and scaling SAFe); authored numerous policy & compliance business & technical certifications (including GDPR, ISO 20071, CMM, CMMI, etc.); served on CTO and Architecture boards/councils, change management leadership teams, enterprise transformation councils, and others; and has supported the discovery, qualification, recommendations, and integration of numerous acquisitions.

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