Best of TDWI's Data Digest
Online articles of interest in the last week include a focus on big data quality, predictive analytics, setting data policy, data retection, and agility among geographically dispersed teams.
Predictive Analytics Needs a Point
(Source: Tech Target)
The main purpose of predictive analytics is to anticipate what consumers want and then be able to give it to them. However, you cannot simply use analytics tools to collect and analyze data without an end goal in mind. A plan and a purpose must be behind any predictive analytics you want your enterprise to use.
Collecting Big Data: Quality, not Quantity
(Source: Tech Crunch)
Too many enterprises are focusing on collecting data first and asking questions later. Most of these enterprises are getting flooded with the amount of garbage data they collect and cannot analyze effectively. This article provides ideas for sharpening your data collection and cleansing to usability.
Writing the Right Data Policy
A data policy is not the top priority for many startup enterprises, but such a small thing helps quell the fears of consumers and helps make your enterprise trustworthy. This article provides pointers on coming up with the perfect data policy for you.
Smart Options for Retaining Enterprise Data
(Source: ZD Net)
Federal laws for data can be incomprehensible, so it can be hard to understand what data you need to retain and what you can dump. Furthermore, retaining so much data is difficult. This article explains several choices for data-retaining hardware helps you figure out what data you should retain.
Keeping Agile While Far Apart
(Source: Information Age)
Agile as a design method has its advantages, yet trying to use that method with a large, geographically distributed team can be difficult. This article provides tips on the best ways to keep your development agile despite distance between teams.
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.