Self-Service Business Intelligence: McDonaldization of Data
January 20, 2011
Drive into McDonald’s. Hear a recorded message about a special. Issue order. Get Big Mac and lots of questionable commercial food output. Leave.
Yep, business intelligence and “I’m loving it.”
No one pays much attention to the food production system and even less to what happens between the cow’s visit to the feedlot and the All American meal.
Ah, self-service. Convenience. Speed. Ease of use. Yes!
These days we pump our own gas (minus Oregon and NJ) and pour our own soft drinks. We Google instead of asking the reference librarian (usually).
Is this the future of Business Intelligence? “Soon Self-Service BI, SaaS to Dominate the Tech World” predicts that 2011 will bring an increase in self-service BI. According to SiliconIndia News: “Numerous vendors, including IBM, SAP, Information Builders, Tibco Software, QlikTech, and Tableau Software, already offer [self-service BI] tools, and adoption will accelerate as more companies try to deliver BI capabilities to nontechnical users, business analysts, and others.” The question becomes: Will the users know what the outputs mean? The SaaS part of the prediction I heartily agree with, in BI and everywhere else.
What if the data are dirty? Malformed? Selected to present a particular view of the Big Mac world? How about that user experience?
Alice Wasielewski, January 20, 2011
Comments
One Response to “Self-Service Business Intelligence: McDonaldization of Data”
-
- Subscribe to Beyond Search
Feature archive
News archive
-
Alice
I believe Self-service BI is the future for delivering value quickly, directly to business people. You’ve raised good questions, and I think a combination of intuitive interfaces, embedded knowledge and guidance, context setting and “every person” analytics that are self explanatory are important to good decision making.
Automated data management and maintenance (using meta-data synchronization, quarantines and aliases) is also important to ensure that decisions are made on quality data.