The goal of big data management is to ensure a high level of data
quality and accessibility for business intelligence and big data
analytics applications. Corporations, government agencies and other
organizations employ big data management strategies to help them contend
with fast-growing pools of data, typically involving many terabytes or
even petabytes of information saved in a variety of file formats.
Effective big data management helps companies locate valuable
information in large sets of unstructured data and semi-structured data
from a variety of sources, including call detail records, system logs
and social media sites.
Most big data environments go beyond relational databases and
traditional data warehouseplatforms to incorporate technologies that are
suited to processing and storing nontransactional forms of data. The
increasing focus on collecting and analyzing big data is shaping new
platforms that combine the traditional data warehouse with big data
systems in a logical data warehousing architecture. As part of the
process, the must decide what data must be kept for compliance reasons,
what data can be disposed of and what data should be kept and analyzed
in order to improve current business processes or provide a business
with a competitive advantage. This process requires careful data
classification so that ultimately, smaller sets of data can be analyzed
quickly and productively
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