John O’Brien is CEO of Radiant Advisors. With more than 25 years of experience delivering value through data warehousing and business intelligence programs, O’Brien’s unique perspective comes from the combination of his roles as a practitioner, consultant, and vendor CTO in the BI industry. As a globally recognized business intelligence thought leader, O’Brien has been publishing articles and presenting at conferences in North America and Europe for the past 10 years. His knowledge in designing, building, and growing enterprise BI systems and teams brings real-world insights to each role and phase within a BI program. Today, through Radiant Advisors, O’Brien provides research, strategic advisory services, and mentoring that guide companies in meeting the demands of next-generation information management, architecture, and emerging technologies. Follow him on Twitter: @obrienjw.
Articles by John O’Brien
There's no doubt that AI has taken center stage in the enterprise data and analytics world, as evidenced by the mass quantities of related headlines, conferences, and vendor marketing. But hype aside, business executives are now discovering how to leverage AI for improved decision making with augmented or assistive intelligence solutions or the competitive advantages in new products and services. AI is proving its viability in the real world, including enterprise data and analytics.
Posted December 23, 2019
As companies grow increasingly data-centric in their decision making, product and services development, and their overall understanding of the world they work in, speed and agility are becoming critical capabilities. A common theme in big data and analytics today is "Industry 4.0," representing a new wave of technology that enables the automation necessary for scaling. There's compelling justification for this as companies seek to unlock business value from big data with two broad approaches: the democratization of data with greater access by more users, and the enablement of automation everywhere possible.
Posted September 20, 2017
As the Internet of Things (IoT) revolution works its way through marketing hype and seeks its place of valuable contribution within companies and industries, you might pause to wonder how IoT can create opportunities for your company. Yet that assessment is difficult in part because the buzz does not always align with reality. In short, it's no simple task to discern the true potential of IoT today, leaving one to wonder: What is realistic, what difference could IoT make in my company, and how mature are other companies in embracing IoT potential?
Posted April 07, 2017
The data lake has been the subject of more than its fair share of critics since its inception. Pundits claim it's a source of chaos and risk. Analysts often slam the concept, calling it a "data swamp" or "data dump." As a result of this scrutiny, the definition and understanding of the definition of the data lake are rather murky.
Posted March 24, 2016
Anyone who thought Hadoop was a fly-by-night technology was wrong. Hadoop has rapidly evolved—improving and gaining mainstream adoption as a technology and framework for enabling data applications previously out of reach for all but the savviest of companies. The open source Apache Hadoop developer community (and distribution vendors) continuously contributes advances to meet the demands of companies seeking more powerful—and useful—data applications, while also focusing on requirements for improved data management, security, metadata, and governance. Hadoop is not only stable but worthy of consideration for core IT strategies.
Posted September 14, 2015
There is no one single path to the data lake within the data architecture of the organization. Likewise, each data lake is unique, with inputs and decisions from the organization contributing a variety of essential elements in organization, governance, and security.
Posted April 08, 2015
In 2014, we continued to watch big data enable all things "big" about data and its business analytics capabilities. We also saw the emergence (and early acceptance) of Hadoop Version 2 as a data operating platform, with cornerstones of YARN (Yet Another Resource Negotiator) and HDFS (Hadoop Distributed File System). In 2015, the mainstream adoption with enterprise data strategies and acceptance of the data lake will continue as data management and governance practices provide further clarity. The cautionary tale of 2014 to ensure business outcomes drive big data adoption, rather than the hype of previous years, will likewise continue.
Posted January 12, 2015
In 2013, two major shifts in the big data landscape occurred, which can be described as the Battle Over Persistence and the Race for Access Hill. The acceptance of leveraging the strengths of various database technologies in an optimized Modern Data Platform has more or less been resolved, but the recognition of a single point of access and context is next. Likewise, the race for access will continue well into 2014.
Posted January 07, 2014