Database Reference
In-Depth Information
Data analytics
To stay ahead of the times and take informed decisions, businesses now require run-
ning analytics on data that is moved in on a real-time basis and this data is usually
multi-structured, characterized in the previous section. Value is in identifying patterns
to make intelligent decisions and in influencing decisions if we could see the behavior
patterns.
Classically, there are three major levels of management and decision making within
an organization: operational, tactical, and strategic. While these levels feed one an-
other, they are essentially distinct:
•
Operational data
: It deals with day-to- day operations. At this level decisions
are structured and are usually driven by rules.
•
Tacticaldata
: It dealswith medium-term decisions andissemi-structured. For
example, did we meet our branch quota for new loans this week?
•
Strategic data
: It deals with long-term decisions and is more unstructured.
For example, should a bank lower its minimum balances to retain more cus-
tomers and acquire more new customers?
Decision making changes as one goes from level to level.
With increasing need for supporting various aspects of Big Data, as stated previously,
existing data warehousing and business intelligence tools are going through trans-
formation.
Big Data is not, of course, just about the rise in the amount of data we have, it is also
about the ability we now have to analyze these data sets. It is the development with
tools and technologies, including such things as
Distributed Files Systems
(
DFS
),
which deliver this ability.
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