Question

Share your reflection, and engage with your peers on the importance of developing a data management plan to ensure data quality within an organisation. Also elaborate on whether you think data quality will have an effect on the interpretation phase of the business research process.

Answer 1

According to me and data related researchers there is much and very high importance of the data , Data quality it may be fighter of qualitative or quantative or ready data .......As we think on data quality we have,,,**Data quality is the capability of data to be used effectively, economically and rapidly to inform
and evaluate decisions , Data quality is an old problem that has acquired urgent new dimensions. Once it was largely a scientific
issue, with roots in measurement error and survey uncertainty. But for today’s world of massive electronic
data sets and difficult policy decisions, data quality (DQ) problems can create significant economic and
political inefficiencies. Modern research on DQ improvement draws upon multiple disciplines and presents
a rich set of scientific, technological, and process control challenges to statisticians.
DQ merits more attention from the statistical community, especially among academics. Faculty engage-
ment in the problem has been virtually nil. At a National Institute of Statistical Sciences (NISS)-sponsored
session on DQ at JSM 2002, only two of more than 70 attendees were from universities, and both of them
had prior connection with NISS.
This paper is meant to help generate academic attention, in part by framing modern DQ from a statistical
perspective. First, in §2, we present a conceptual overview of DQ. Next, in §2, we describe DQ as a multi-
disciplinary problem that entails ideas from computer science, quality control, human factors research, and
the statistical sciences; in any application, these all linked by domain knowledge to the specific context of the
problem. In §4 we use show that statistical visualization provides powerful tools for DQ improvement. This
point is illustrated by applications in two case studies undertaken by NISS. Finally, based on our survey of
the field, we outline in §5 DQ research challenges for statisticians that range from theory and methodology
to new software tools.
2 What is Data Quality?
We begin with a definition:. As we see above definition of data quality of true data I.e.Data quality is the capability of data to be used effectively, economically and rapidly to inform
and evaluate decisions.......Comment We Decisions drive both the generic need and context-specific requirements for DQ(Data Quality). Decisions are of two
kinds: those based on the data (Example: government policies) and those about the data.....

As above we clearly knows that if our research data is true data and is in clearer and simplest form and having high quality information.....then obviously our research interpretation are very much better or good one than usual data........

.

So ......Data Quality is one of the main tool for the prediction or interference of the concern activity or researchers research.