This post explains that becoming a successful organization in any industry is not about being data-driven, but whether data, and regardless of its source, is driving your organization to make better business decisions.
This post, inspired by Jeffrey Ma’s book The House Advantage: Playing the Odds to Win Big In Business, explores the possibility that our intuition has always been more data-driven than we gave it credit for.
If ignorance is bliss, what is digital abundance? This post posits a contrarian’s view on the quantified self movement, wondering if we are ready for the impact that big data will have on self-awareness.
An example of the challenge of data accuracy and the possible misinformation provided by key performance metrics inspired by the investigative reporting of the HBO satirical news show Last Week Tonight with John Oliver.
While the era of big data inundates us with huge quantities of data in a wide variety of formats and questionable levels of quality, it may also be making us more literate in more ways.
This post ponders how the focusing illusion, the illusion-of-truth effect, and the illusion-of-quality effect can affect the metrics your organization is relying on to support its data-driven business decisions.
This cautionary post, based on a Wired article by Felix Salmon, is a reminder that while becoming data-driven is a laudable goal, be wary of becoming too driven by data.
Inspired by Nate Silver, this blog post examines the journey from anecdote to data and how hard it can be to find the way back, especially after data becomes doctrine.
During this OCDQ Radio episode, guest Phil Simon discusses concepts from his book The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions.
The data accuracy challenges and data privacy implications associated with tracking our fitness and health with wearable devices.
Borrowing from the strategies and mottos of the United States Army and Marine Corps, this blog post explains how successful data governance is always faithful to its principles and always flexible in its policies.
While the use of a postal validation service is a highly recommended best practice for ensuring valid addresses are entered when data is created, just because you have valid data doesn’t guarantee that you have accurate data.
A follow-up to my previous post, arguing that even when real-world alignment makes data fit for the purpose of every use, you still need to keep track of, and track changes in, each use to keep the data supporting all your business objectives in context.
A sunny point of view about the importance of relative data quality standards, inspired by the illusion of a rising and setting Sun caused by our rotating frame of reference on the Earth’s spinning surface as our planet revolves around the Sun.
Timeliness refers to the time expectation for the accessibility of data. Due to the increasing demand for real-time data-driven decisions, timeliness is the most important dimension of data quality.
As Jack Olson explained in his book Data Quality: The Accuracy Dimension, in order to be accurate, data must have both the right value and be represented in an unambiguous form.
During this OCDQ Radio episode, guest William McKnight discusses concepts from his book Information Management: Strategies for Gaining a Competitive Advantage with Data.