Dana Gardner: We’re not just dealing with an increase in data, but we have all these different data sources. We’re still dealing with mainframes.
It seems to me that you can’t just deal with big data. You have to deal with the right data. What’s the difference between big data and right data?
Noel Yuhanna: It’s like GIGO, Garbage In, Garbage Out. A lot of times, organizations that deal with data don’t know what data they’re dealing with. They don’t know that it’s valuable data in the organization. The big challenge is how to deal with this data.
The other thing is making business sense of this data. That’s a very important point. And right data is important. […]
That’s where there’s a huge opportunity for organizations that are dealing with such big data. First of all, you need to understand what this big data means, and ask are you going to be utilizing it. Throwing something into the big data framework is useless and pointless, unless you know the data.
Todd Brinegar: Noel is 100 percent correct, and it is all about the right data, not just a lot of data. It’s interesting. We have clients that have a multiplicity of databases. Some they don’t even know about or no longer use, but there is relevant data in there.
So the ability to come in, attach, and get the right data and make that data actionable and make it matter to a company is really key and critical today. And being able to do that with the lowest cost of ownership in the market and the highest time to value equation—so that the companies aren’t creating a huge amount of tech on top of the tech that they already have to get at this right data—that’s really the key critical part.
I see things differently:
Big Data => Right Data => Valuable Information
Nobody can access directly the right data.
Original title and link: Big Data vs Right Data ( ©myNoSQL)