Big Data is about harnessing largesse and being adaptive enough to respond to change.
Big Data is still a big puzzle for many organizations. The
term "Big Data" was first used as a reference for all the data
generated by/through the internet...the largest amount of data ever generated
by mankind... afterward. "Big Data" is a concept where at its purist
and fundamental level is the attempt to try to leverage the inner-connected
nature of data that is collected during the operation of any enterprise.
Big Data is still a big puzzle for many organizations. The
term "Big Data" was first used as a reference for all the data
generated by/through the internet...the largest amount of data ever generated
by mankind... afterward. "Big Data" is a concept where at its purist
and fundamental level is the attempt to try to leverage the inner-connected
nature of data that is collected during the operation of any enterprise.
So in a nutshell, "BIG DATA" means
crap lots of data -it is data that needs more than just the standard
commodity products, databases and systems to support it. If it can be supported
by commodity products (traditional load balancing engines, etl tools,
shared-everything SMP servers and standard network devices), and if it can be
said that the query turnaround time doesn't really matter, then the enterprise
has no real "big data" issue. Their data's not big enough to qualify
and their data demands are not pressing enough to move-the-needle. On the other hand if an enterprise has
data tables that are in the tens-of-billions of rows, of structured data, then
it is very difficult to disqualify this as "big data". It's data and
it's pretty big.
Five “V”s
of Big Data: Volume, Velocity, Variety, Veracity, and Value. Big Data
can mean large data sets but is more about the combination of different types
of data together that allow you to answer key questions about your business. It
can be as big and complex as you want it to be but needs to answer the
critical questions you can't answer by looking at multiple systems with tidbits
of data. Big Data is nothing more nothing less than data with
more Volume, at insane Velocity, coming from a variety of sources and with high
Variety when it comes to the metadata. It also has to be true (Veracity) and it
has to bring value to your working environment
Big Data
initiative: Many organizations are taking Big Data initiatives,
such initiatives may have more than one of the following characteristics:
- Petabytes of data used for analytics
- denormalized / semi-structured and unstructured data used for analytics
- the implementation of Hadoop and related technology
- the use of analytic data for predictive analyses and data mining
- Petabytes of data used for analytics
- denormalized / semi-structured and unstructured data used for analytics
- the implementation of Hadoop and related technology
- the use of analytic data for predictive analyses and data mining
- How many types of Data you are gathering / generating/creating / capturing as our Inputs for our Organization?
-Whether the present Inputs (if any) are sufficient for the Organizational Goals / Aims?
-Whether any duplication s found in the present Inputs? Can it erected & shorten the Inputs?
-What & where you should add new Points / information in previous Inputs Formats to get the proper results?
-Whether the present Inputs (if any) are sufficient for the Organizational Goals / Aims?
-Whether any duplication s found in the present Inputs? Can it erected & shorten the Inputs?
-What & where you should add new Points / information in previous Inputs Formats to get the proper results?
The "big data" realm is not about
unstructured data, but about harnessing largesse and being adaptive enough to
respond to change. To put simply, Big Data is not the end, the end is how to
capture the business insight from the big data, and leverage it for enabling
business growth and improving customer satisfaction.
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