Data Digest: Data Mashups, Toy Story 2 Disaster, and Data Modeling and Bias
A data disaster almost destroyed Toy Story 2, plus how to model data with and without bias, and getting the most from data mashups.
Get the Most Information with Data Mashups
(Source: Tech Target)
The more data you have, the sharper your image of the data will be. This truth has led to enterprises beginning to mashup data from many sources in order to paint the clearest picture of BI. This article explains what enterprises have done for data mashups and some tools to get yours started -- as well as some things to watch out for when mashing up data.
Toy Story 2 Survived Poor Data Recovery Testing
(Source: Information Age)
Toy Story 2 was almost entirely deleted from Pixar’s database because of a command line. Backup systems in place were no help in recovering the lost files. It was just luck that Toy Story 2 survived. This article reviews best practices when testing data-recovery-as-a-service options so your enterprise does not have to rely on luck to survive a data disaster.
Accurately Modeling Data with and without Bias
Data modeling is an important piece of predictive analytics. However, making a great predictive model requires weeding out biases and making sure you model something close to reality. This article explains everything you need to pay attention to when modeling predictive data.
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Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.