Archive for 'Data Governance'

The Decision Wobegon Effect

The Decision Wobegon Effect

May 15, 2013 by

In his book The Most Human Human, Brian Christian discussed what Baba Shiv of the Stanford Graduate School of Business called the decision dilemma, “where there is no objectively best choice, where there are simply a number of subjective variables with trade-offs between them. The nature of the situation is such that additional information probably won’t even help. In these cases – consider the parable of the donkey that, halfway between two bales of hay and unable to decide which way to walk, starves to death – what we want, more than to be correct, is to be satisfied with our choice (and out of the dilemma).”

 

Change = WIIFM > WMETP

Change = WIIFM > WMETP

May 08, 2013 by

My previous post about change management, which advocated nudges not mandates, received an excellent comment from Karen Way: “What I’ve found that works to nudge people into accepting data quality as part of their norm is to demonstrate the benefit to them, the WIIFM (what’s in it for me) factor. This is especially true…

 

Bursting Your Filter Bubble

Bursting Your Filter Bubble

Apr 24, 2013 by

In a previous post about data visualization, I discussed how our expectations can distort the data we visualize a lot more than we may realize, causing us to mistake dashboards for magic mirrors reflecting back our own image of what we want our data to show us.

 

Leveraging Master Data Management as a Tool for DW Consolidation

Leveraging Master Data Management as a Tool for DW Consolidation

Apr 23, 2013 by

In the past few postings we looked at some of the issues that emerge as a result of uncontrolled creation of data warehouses and data marts. I suggested that the goals of a data warehouse consolidation project should not only include the creation of a new data asset that accommodates the users of the “to-be-consolidated” warehouses and marts, but that those systems should be retired and replaced by the new asset.

 

Use a No Brown M&M’s Clause

Use a No Brown M&M’s Clause

Apr 17, 2013 by

There is a popular story about David Lee Roth exemplifying the insane demands of a power-mad celebrity by insisting that Van Halen’s contracts with concert promoters contain a clause that a bowl of M&M’s has to be provided backstage with every single brown candy removed, upon pain of forfeiture of the show, with full compensation to the band.

 

Considering Success Factors for Data Warehouse Consolidation

Considering Success Factors for Data Warehouse Consolidation

Apr 16, 2013 by

The last thing you want to result from a data warehouse consolidation project is the creation of yet another siloed data asset that must be populated and managed with respect to the requirements of the downstream users.

To really benefit from a consolidation project, your newly-created consolidated warehouse should replace the data marts and warehouses that are used to populate…

 

Don’t Mess with Data

Don’t Mess with Data

Apr 03, 2013 by

In Nudge: Improving Decisions About Health, Wealth, and Happiness, Richard Thaler and Cass Sunstein recounted the story of the campaign to reduce littering on Texas highways called Don’t Mess with Texas.  Prior to launching it, Texas officials were enormously frustrated by the failure of their previous, well-funded, and highly publicized advertising campaigns, which attempted to convince people that it was their civic duty to stop littering.

 

20 Encounters of the Information Management Kind – #4 No Data Strategy

20 Encounters of the Information Management Kind – #4 No Data Strategy

Mar 18, 2013 by

I cannot tell you how many times I have had customers that do not have a specific vision for their data.  What I mean by this is that there is no data strategy. 

 

Do the Eyes Have It?

Do the Eyes Have It?

Feb 27, 2013 by

In my previous post, I looked into the magic mirrors of business leaders, more commonly called dashboards, as one example of how data visualization is used.  In this post, I want to look at what we use to look — our eyes — and how they process whatever data we visualize.