[…] the root of the true problems with big data are often not in how or what tools we use to analyze the data, but more so in how we capture, or fail to capture it in the first place. In essence, our failure to capture the data accurately and consistently often renders analysis of it a meaningless exercise due to the Garbage In = Garbage Out (GIGO) principle.
Firstly, what Paul calls “issues with data consistency” is about data corectness and freshness. And I think there is still a long way to answering the how and what tools are used to analyze and extract useful information from big data.
Original title and link: Real Life Issues With Big Data In The Enterprise (NoSQL databases © myNoSQL)