We’re at the dawn of a new era in decision making made possible by the intersection of business intelligence and artificial intelligence. Rather than replace BI, AI will make BI more pervasive. AI-infused BI tools will be easier to use, generate more useful insights, and make business users more productive. Rather than replace human decision makers, AI will free them to focus on value-added activities and make decisions with data rather than rely solely on gut instinct. Originally published at https://www.eckerson.com/articles/the-impact-of-ai-on-analytics-machine-generated-intelligence

In this episode, Wayne Eckerson and Rich Galan discuss the obstacles to delivering timely analysis, the problems that large volumes of data create, solutions to those issues, and where BI is headed in the near future. Rich is a veteran data analytics leader with 20 years of experience in a variety of data-driven organizations.

Discover how power user networks are the key to successful self-service analytics, providing data analysts with the training and support they need. Learn about the role of peer-based learning and collaboration in enhancing skills and satisfaction. Explore the benefits of tool standardization and data catalogs in improving data access and knowledge sharing among analysts.

In this episode, Wayne Eckerson and Steve Dine discuss modernizing data architectures. They cover the definition of a modern data architecture, telltale signs you need to modernize, best practices to modernize, and much more. Dine is the President of Datasource Consulting, an EXL company. He has extensive experience designing, delivering, and managing successful, highly scalable and maintainable modern data architecture solutions.

Data pipelines become chaotic with pressures of agile, democratization, self-service, and organizational “pockets” of analytics. From enterprise BI to self-service analysis, data pipeline management should ensure analysis results are traceable, reproducible, and of production strength. Robust data pipelines rely on eight critical components. Originally published at https://www.eckerson.com/articles/the-complexities-of-modern-data-pipelines

In this episode, Wayne Eckerson and Jen Underwood explore a new era of analytics. Data volumes and complexity have exceeded the limits of current manual drag-and-drop analytics solutions. Data moves at the speed of light while speed-to-insight lags farther and farther behind. It is time to explore intelligent, next generation, machine-powered analytics to retain your competitive edge. It is time to combine the best of the human mind and machine. Underwood is an analytics expert and founder of Impact Analytic. She is a former product manager at Microsoft who spearheaded the design and development of the reinvigorated version of Power BI, which has since become a market leading BI tool. Underwood is an IBM Analytics Insider, SAS contributor, former Tableau Zen Master, Top 10 Women Influencer and active analytics community member. She is keenly interested in the intersection of data visualization and data science and writes and speaks persuasively about these topics.

In this podcast, Carl Gerber and Wayne Eckerson discuss Gerber’s top five data governance best practices: Motivation, Assessment, Data Assets Catalog, CxO Alliance, and Data Quality. Gerber is a long-time chief data officer and data leader at several large, diverse financial services and manufacturing firms, who is now an independent consultant and an Eckerson Group partner. He helps large organizations develop data strategies, modernize analytics, and establish enterprise data governance programs that ensure data quality, operational efficiency, regulatory compliance, and business outcomes. He also mentors and coaches Chief Data Officers and fills that role on an interim basis.

With today’s unprecedented velocity of change in data and technologies, the single version of the truth (SVOT) is sometimes looked upon as a nice to have. But SVOT is not optional. Despite the difficulties in constructing a single version of the truth, it is now needed more than ever to keep CEOs happy and to stay compliant with new regulations like the GDPR. Originally published at https://www.eckerson.com/articles/single-version-of-the-truth-not-optional

Ethics is challenging because right and good are not always clear. More data, more kinds of data, and advanced analysis of data often conflict with concerns of data privacy, security, anonymity, and ownership. Resolving these conflicts requires acknowledgment, discussion, and the hard work of defining ethics-based policies and creating a culture of ethical conduct. Originally published at https://www.eckerson.com/articles/data-ethics-the-new-data-governance-challenge

In this episode, Wayne Eckerson and Jeff Magnusson discuss the data architecture Stitch Fix created to support its data science workloads, as well as the need to balance man and machine and art and science. Magnusson is the vice president of data platform at Stitch Fix. He leads a team responsible for building the data platform that supports the company's team of 80+ data scientists, as well as other business users. That platform is designed to facilitate self-service among data scientists and promote velocity and innovation that differentiate Stitch Fix in the marketplace. Before Stitch Fix, Magnusson managed the data platform architecture team at Netflix where he helped design and open source many of the components of the Hadoop-based infrastructure and big data platform.