Top 5 data quality mistakes organizations make
.@philsimon lists the gravest data-quality errors.
Search Results: divide (26)
Do organizations need to adopt formal data strategies?
.@philsimon begins a four-part series on the need for a proper data strategy.
Provisioning data for advanced analytics in Hadoop
The data lake is a great place to take a swim, but is the water clean? My colleague, Matthew Magne, compared big data to the Fire Swamp from The Princess Bride, and it can seem that foreboding. The questions we need to ask are: How was the data transformed and
Crowdsourcing data improvement: Part 3
In this blog series, I am exploring if it’s wise to crowdsource data improvement, and if the power of the crowd can enable organizations to incorporate better enterprise data quality practices. In Part 1, I provided a high-level definition of crowdsourcing and explained that while it can be applied to a wide range of projects
Building an analytics culture from the ground up
With all the industry emphasis and collateral available on high performance analytics, business intelligence and visual analytics, it can be difficult to know exactly where to begin, especially if you don’t have a team of statisticians standing by. Thankfully, analytics covers a huge range of opportunities to empower your business, and
The evolution of problem solving
My previous post was inspired by what Andrew McAfee sees as the biggest challenge facing big data: convincing people to trust data-driven algorithms over their expertise-driven intuition. In his recent VentureBeat blog post, Zavain Dar explained that the real promise of big data is that it will change the way
Make data quality dimensions work for you
One of the most common questions I get asked by our members on Data Quality Pro is, “Can you do more articles on data quality dimensions?” Part of the reason for this request is when people first start getting involved with data quality, they invariably buy data quality books and
Carbon, silicon and the bonds of collaboration
Jim Harris (@ocdqblog) discusses how business and IT can use technology to improve collaboration.
Customer analytics: classification vs. segmentation
David Loshin (@davidloshin) on using analytics to pinpoint your best customers.
Data management: the next generation
In a galaxy far, far away, @ocdqblog explains how data management relates to his favorite sci fi movies.