Database Reference
In-Depth Information
processing, like market value for each security to compute, and rate of return
on the overall value invested.
Features
In this section, we will understand the characteristic features of enterprise data. Each
of the listed characteristics describes a unique facet/behavior that would be elabor-
ated in the implementation perspective later in the
Data Science life cycle
section in
this chapter. Following are a few important characteristics of enterprise data:
•
Included
:Enterprisedataisintegratedandusually,butnotmandatorily,cent-
ralized to all applications within an enterprise. Data from various sources and
varied formats is either aggregated or federated for this purpose. (Aggrega-
tion refers to physically combining data sets into a single structure and loca-
tion while federation is all about getting a centralized way to access a variety
of data sources to get the required data without physically combining/mer-
ging the data.)
•
Standards compliance
: Data is represented/presented to the application in
context in a format that is either a standard to an enterprise/across enter-
prises.
•
Secure
: Data is securely accessible through authorization.
•
Scalable
: In a context where data is integrated from various sources, the
need to support larger volumes becomes critical, and thus the scalability,
both in terms of storage and processing.
•
Condensed/Cleansed/Consistent
: Enterprise data can possibly be con-
densed and cleansed to ensure data quality against a given set of data
standards for an enterprise.
•
Varied sources and formats
: Data is mostly combined from varied sources
and can continue to be stored in varied formats for optimized usage.
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