Tag: data quality

Jim Harris 0
Big data hubris

While big data is rife with potential, as Larry Greenemeier explained in his recent Scientific American blog post Why Big Data Isn’t Necessarily Better Data, context is often lacking when data is pulled from disparate sources, leading to questionable conclusions. His blog post examined the difficulties that Google Flu Trends

Jim Harris 0
What magic teaches us about data science

Teller, the normally silent half of the magician duo Penn & Teller, revealed some of magic’s secrets in a Smithsonian Magazine article about how magicians manipulate the human mind. Given the big data-fueled potential of data science to manipulate our decision-making, we should listen to what Teller has to tell

Jim Harris 0
What Mozart for Babies teaches us about data science

Were you a mother who listened to classical music during your pregnancy, or a parent who played classical music in your newborn baby’s nursery because you heard it stimulates creativity and improves intelligence? If so, do you know where this “classical music makes you smarter” idea came from? In 1993, a

Matthew Magne 0
MDM Foundations: Adding data governance to get to MDM

In my previous post, I outlined the main components needed for a phased approach to MDM. Now, let's talk about some of the other issues around approaching MDM: data governance and the move to enterprise MDM. Where does governance come in? Throughout your MDM program, it's important that deep expertise

Jim Harris 0
Behavioral data quality

For decades, data quality experts have been telling us poor quality is bad for our data, bad for our decisions, bad for our business and just plain all around bad, bad, bad – did I already mention it’s bad? So why does poor data quality continue to exist and persist?

Jim Harris 0
The four noble truths of data quality

Loraine Lawson recently used the Eight-Fold Path of Buddhism, in which practitioners are encouraged to pursue right views, intentions, speech, actions, livelihood, efforts, mindfulness and concentration, as inspiration for her blog post The Five-Fold Path for Ensuring Data = Information. The post offered five recommendations for ensuring that data is transformed into

Jim Harris 0
Preventing the zombie data-pocalypse

Since tomorrow is How-long-has-it-been-since-you-used-this-data-ween, it’s time to review your organization’s preparedness for preventing the zombie data-pocalypse. (Please Note: This should not be confused with your organization’s preparedness for preventing the zombie apocalypse, for which check out the resources provided by the Centers for Disease Control and Prevention by ever-so-carefully clicking on

Jim Harris 0
The architects of the invisible

In the era of big data, Kenneth Cukier and Viktor Mayer-Schonberger noted in their book Big Data: A Revolution That Will Transform How We Live, Work, and Think, “we are in the midst of a great infrastructure project that in some ways rivals those of the past, from the Roman aqueducts

Daniel Teachey 0
Hold on to that receipt: data management inaction

I've written, talked and thought about  data management for an entire decade now. In that time, I've collected examples of how data – and the processes for managing that data – can affect our everyday life. For years I used the "Have you ever gotten multiple pieces of mail from

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