Big data: A great way for database management
Big data is the term for a collection of data sets so large and complex that it becomes
difficult to process using on-hand database management tools or traditional data
processing applications. The challenges include capture, curation, storage,search,
sharing, transfer, analysis,and visualization. The trend to larger data sets is due to the
additional information derivable from analysis of a single large set of related data, as
compared to separate smaller sets with the same total amount of data, allowing
correlations to be found to "spot business trends, determine quality of research,
prevent diseases, link legal citations, combat crime, and determine real-time roadway
traffic conditions."
processing applications. The challenges include capture, curation, storage,search,
sharing, transfer, analysis,and visualization. The trend to larger data sets is due to the
additional information derivable from analysis of a single large set of related data, as
compared to separate smaller sets with the same total amount of data, allowing
correlations to be found to "spot business trends, determine quality of research,
prevent diseases, link legal citations, combat crime, and determine real-time roadway
traffic conditions."
As of 2012, limits on the size of data sets that are feasible to process in a reasonable
amount of time were on the order of exabytes of data.Scientists regularly encounter
limitations due to large data sets in many areas, including meteorology, genomics,
connectomics, complex physics simulations,and biological and environmental research.
The limitations also affect Internet search, finance and business informatics. Data sets
grow in size in part because they are increasingly being gathered by ubiquitous information-
sensing mobile devices, aerial sensory technologies (remote sensing), software logs,
cameras, microphones, radio-frequency identification readers, and wireless sensor
networks.[The world's technological per-capita capacity to store information has roughly
doubled every 40 months since the 1980s;as of 2012, every day 2.5 quintillion (2.5×1018)
bytes of data were created.The challenge for large enterprises is determining who should
own big data initiatives that straddle the entire organization.
amount of time were on the order of exabytes of data.Scientists regularly encounter
limitations due to large data sets in many areas, including meteorology, genomics,
connectomics, complex physics simulations,and biological and environmental research.
The limitations also affect Internet search, finance and business informatics. Data sets
grow in size in part because they are increasingly being gathered by ubiquitous information-
sensing mobile devices, aerial sensory technologies (remote sensing), software logs,
cameras, microphones, radio-frequency identification readers, and wireless sensor
networks.[The world's technological per-capita capacity to store information has roughly
doubled every 40 months since the 1980s;as of 2012, every day 2.5 quintillion (2.5×1018)
bytes of data were created.The challenge for large enterprises is determining who should
own big data initiatives that straddle the entire organization.
Big data is difficult to work with using most relational database management systems
and desktop statistics and visualization packages, requiring instead "massively parallel
software running on tens, hundreds, or even thousands of servers".What is considered
"big data" varies depending on the capabilities of the organization managing the set, and
on the capabilities of the applications that are traditionally used to process and analyze the
data set in its domain. "For some organizations, facing hundreds of gigabytes of data for the
first time may trigger a need to reconsider data management options. For others, it may take
tens or hundreds of terabytes before data size becomes a significant consideration."
and desktop statistics and visualization packages, requiring instead "massively parallel
software running on tens, hundreds, or even thousands of servers".What is considered
"big data" varies depending on the capabilities of the organization managing the set, and
on the capabilities of the applications that are traditionally used to process and analyze the
data set in its domain. "For some organizations, facing hundreds of gigabytes of data for the
first time may trigger a need to reconsider data management options. For others, it may take
tens or hundreds of terabytes before data size becomes a significant consideration."
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