Challenges and thoughts on Big Data/Data Quality

Take in the article here to catch up on FIVE major factors that you need to consider for Big Data or Data Quality.  These are challenges, thoughts, and ideas that you really should have percolating in the back of your mind when you have to deal with either Big Data or Data Quality issues.

Big Data and Data Management

Are you using Big Data?  Do you know how to combine Data Management principles with Big Data to take a bigger step forward?  Visit this article on the subject and then follow the link within to read the C-CENTRAL article to get on the same page as CIO's about this issue!  Getting on the same page as your CIO will certainly help you navigate future Support issues on this topic!

Do you have data quality issues?

Yesterday I shared an article that talked about if data quality issues are worth fixing, but today I share an article that asks how you know if you have issues with data quality in the first place!  Does that sound pretty straightforward?  Well, check out all the questions you can be asking the different departments in your company (or maybe user groups your team interfaces with) to see just how much data quality drift there is between reality and what you think reality is.  After you have digested this, make up questions that you can ask your own integrated teams to see how Development, Project or DBA teams are thinking about the issue of data quality and find out what they think about data quality (integrity) from their vantage points!

Data Quality: What is it good for? Absolutely nothing! Right?

Recently I have read several great articles about data, and the quality of it, so I am going to have a Data Quality week to highlight the different dimensions surrounding data and data quality.  I will start with this article asking if data quality is worth the effort, and how we can quantify it.  I thought it was a stroke of genius to put forward the idea that not every data quality issue needs to be fixed because in today's hypersensitive environment of "Big Data" or "Business Intelligence" having the right data, in the right format, with the correct delivery seems like the only recipe for success.  Well, that is the only story I really see being put out there because nobody is suggesting we have bad, or incorrect, data in our systems and that is exactly what data quality means in this context.  So I will ask again, what is data quality good for?