Reflections on the data-related challenges of today and tomorrow
.@philsimon chimes in about data-related accomplishments and challenges.
Author
Phil SimonRSS
Author, Speaker, and Professor
Author, Speaker, and Professor
Phil Simon is a keynote speaker and recognized technology expert. He is the award-winning author of eight management books, most recently Analytics: The Agile Way. His ninth will be Slack For Dummies (April, 2020, Wiley) He consults organizations on matters related to strategy, data, analytics, and technology. His contributions have appeared in The Harvard Business Review, CNN, Wired, The New York Times, and many other sites. He teaches information systems and analytics at Arizona State University's W. P. Carey School of Business.
The case against automating data management
Phil Simon flip-flops from his last post.
The case for automating data management
In the first post of a two-part series, Phil Simon plays point-counterpoint with himself.
Which data sources will organizations use to make AI as effective as possible?
Phil Simon weighs in on using data to make the most of AI.
How to improve data accuracy
Phil Simon says that the downsides of even a few discrepancies can be enormous.
Why organizations' AI efforts will require retiring data sources
There's a chasm in today's business world between "can" and "should." Let's hope that gap closes soon.
Questions on data literacy, part 2
Phil Simon raises two key questions to ask in his second post on data literacy.
Questions on data literacy, part 1
Phil Simon chimes in on the increasingly important topic of data literacy.
Making life easier for your data scientists
Phil Simon chimes in with some tips on how to set these folks loose.
Amazon's data train just keeps a rollin'
Think that the company has let up in the last two years? Think again.
The relationship between data management and analytics: Lessons from the field
Phil Simon shares some lessons from his consulting career.
Top data management trends among companies that succeed with analytics
@philsimon chimes in about how success in one area can lead to success in another.
US data regulation, part 2: What your organization can do about it now
In the second part of this series, Phil Simon argues that organizations can immediately take steps to handle likely legislation.
US data regulation, part I: What's (probably) coming?
In this first of two posts, Phil Simon chimes in on the prospect of data protection regulation in the US.
Analytics implications of record-level security
Phil Simon discusses some of the analytics considerations with record-level security.
What is record-level security?
Phil Simon chimes in on a way to lock down data
Marketing and the GDPR, Part 2: Examining the consent question
@philsimon provides more thoughts about the opportunity that GDPR provides marketing departments.
Marketing and the GDPR, Part 1: Carrots and sticks
@philsimon chimes in on a massive opportunity for organizations that process the data of EU residents.
Four things preventing your organization from becoming a data-driven business
What's stopping you from being a data-driven business? Phil Simon points to four common stumbling blocks.
What does it really mean to be a data-driven business?
It's easier said than done to be a data-driven business, but the squeeze is worth the juice.
The perils of self-service data preparation tools
Phil Simon chimes in on the tendency to rely upon these tools too much.
3 new outcomes you can expect from self-service data preparation
Phil Simon weighs in on the value of getting your own hands dirty using self-service data prep.
How do I know what data is available?
Phil Simon shares his thoughts on this simple yet often-overlooked question.
The pros and cons of data on demand
Phil Simon chimes in on the immediacy of enterprise data.
Hadoop's evolution, part 2: Thoughts on the past, present and the future
Phil Simon chimes in on the last five years of Hadoop with an eye toward the future.
Hadoop's evolution, part 1: Lessons from AWS
Phil Simon looks at AWS's evolution before making some predictions about the future of Hadoop.
Operational vs. analytical MDM
.@philsimon chimes in on some oft-overlooked differences.
The Moneyball effect moves from the field to industry
Billy Beane attained fame in baseball and analytics circles long before Brad Pitt portrayed him in the 2011 film Moneyball. In fact, Beane was making quite the name for himself prior to Michael Lewis’s 2004 book of the same name. It’s no overstatement to claim that, as general manager (GM)
