Data gone awry, Part 2: What to do when your business data deceives you.
.@philsimon on what to do when the data breaks bad.
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.
Data gone awry, Part 1: Will your business data deceive you?
.@philsimon on whether big data and analytics offer true guarantees.
Data quality and cloud computing: What are the risks?
.@philsimon on the specific risks to data quality posed by cloud computing.
Five data quality lessons from Amazon
@philsimon on what we can learn about data quality from Jeff Bezos's behemoth.
Top 5 data quality mistakes organizations make
.@philsimon lists the gravest data-quality errors.
Who's in charge of data quality?
.@philsimon chimes in on this pivotal question.
Where does Hadoop fit into an effective data strategy?
.@philsimon on the convergence between tools such as Hadoop and strategy.
Can an effective data strategy help an organization build a sustainable competitive advantage?
.@philsimon provides insights on whether a data strategy can result in competitive advantage.
What does an effective data strategy look like?
.@philsimon on the need to play offense and defense with your organization's data.
Do organizations need to adopt formal data strategies?
.@philsimon begins a four-part series on the need for a proper data strategy.
Thoughts on big data and new tools
.@philsimon with some thoughts on the panoply of available tools out there.
Data beyond boundaries: Reexamining the role of the data-governance council
.@philsimon on whether data governance is still relevant.
Managing big data, Part 2: Human questions and considerations
.@philsimon on the soft skills that Big Data requires.
Managing big data, Part 1: Technical questions
With Big Data, there are far more technical questions than answers.
Overcoming the IT-Business Divide in an era of big data, Part 3
.@philsimon on bridging the IT-business divide once and for all.
Overcoming the IT-Business divide in an era of big data, Part 2
.@philsimon on the new role of IT.
Overcoming the IT-Business Divide in an era of big data, Part 1
.@philsimon on the new challenges of an old problem.
Data integration: Comparing traditional sources and big data
While not on the same level of Rush, I do fancy myself a fan of The Who. I'm particularly fond of the band's 1973 epic, Quadrophenia. From the track "5:15": Inside outside, leave me alone Inside outside, nowhere is home Inside outside, where have I been? The inside-outside distinction is rather apropos
Big data integration: The case against an "all-in" approach
I've spent a great deal of time in my consulting career railing against multiple systems of record, data silos and disparate versions of the truth. In the mid-1990s, I realized that Excel could only do so much. To quickly identify and ultimately ameliorate thorny data issues, I had to up
What is big data integration?
.@philsimon offers his definition of the term.
What Zappos' bold moves teach us about data governance
.@philsimon on whether companies should apply some radical tactics to DG.
Is effective data governance possible in an era of big data?
.@philsimon on the new challenges of data governance.
Why data visualization matters
.@philsimon says that you shouldn't bring a knife to a gun fight.
Social media: The case for event stream data
@philsimon on the need to adopt new tools to understand events.
Data management lessons from Google
@philsimon says that, yes, we can learn a great deal.
Analytics lessons from Amazon
.@philsimon on what we can learn from Seattle's juggernaut.
The need for speed: A look at real-time analytics
You may feel like the world is moving faster than ever. If so, then you can take solace in two facts: You're not alone in feeling this way. You're right. It is. Celebrating the 25-year anniversary of the Web, The Economist ran a piece examining the increasingly rapid adoption of new technologies.
Finding the signal in the analytics noise
.@philsimon looks under the hood of 'analytics.'
What skills will be required to make sense of big data?
Small data is akin to algebra; big data is like calculus.
What's the future of data? In a word, more.
When asked what his movement wanted around a century ago, the iconic American labor leader Samuel Gompers famously gave a one-word answer: "More." This annoyed his opponents at the negotiating table and many in the business community. He was not demanding a specific wage increase or fighting for a distinct cause like