Smart Dublin Project 11 Assessment 2022

Smart Dublin Project 1
Smart Dublin City Project
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Smart Dublin Project 2
Table of Contents
Sources of Data Collection..................................................................................................3
Online services and digital communication.........................................................................5
Improving Marketing Decisions and Reduce City Council Expenses using Data Analytics
Methods...........................................................................................................................................8
Critical Evaluation.............................................................................................................10
Assessment........................................................................................................................11
Presentation of the Findings..............................................................................................11

Smart Dublin Project 3
Sources of Data Collection
Data collection is a useful process within the initial phases of conducting research. Smart
Dublin has the best plan for conducting a study in the whole world. At times, the collection of
data is an extremely challenging task. It needs planning exhaustively, diligent working,
determination, and comprehension of data diversities. The process of data collection commences
with understanding the types of data required. After that, the researcher takes the imitative of
collecting samples of a particular segment of a population (Bachiochi. and Weiner 2002, p.162).
Then, the researcher has to employ a specific device to collect data from an example that has
been chosen. Data is obtained from the two major sources. These incorporate primary and
secondary. Primary data refers to data collected via questionnaire review within a set of
characteristics. It is an illustration of data acquired from an uncontrolled situation.
In the Smart Dublin project, primary data shall be collected to get firsthand information
from the people residing within the Dublin city. Primary data would make the project authentic
with accurate information to be used during data analysis. Primary data, by its nature would be a-
meeting-the people method, in which the researchers would be capable of knowing what things
which impacts in people’s life.
On the other hand, secondary data is obtained from sources such as books, journals,
magazines, reports, and webs, among others. Primary data are collected with the aim of a
research venture. To be specific, primary data leverage is customized to the needs of the
researcher’s analysis. The major demerit of this form of data is its costly nature. Primary data are
raw information acquired from the first source is controlled or uncontrolled circumstances. The

Smart Dublin Project 4
primary data sources are populace tests from where information is collected. The early stage of
the process is selecting the targeted populace. The origins of primary data include accounts of
eyewitnesses, interviews, drawings, autobiographies, statistical data, as well as journals reporting
original studies.
The secondary source of data describes, summarizes reviews, interprets, and analyses
primary sources. Secondary data can be categorized into internal and external sources.
Associations or individuals collect external secondary data from outer environments. Internal
data include sources that exist and are kept within an organization. Internal data sources are
attained from balance sheets, sales figures, past marketing studies, and profits and loss
statements. Similarly, some of the external data can be collected from foundations, government
sources, corporate filings, and media incorporating both telecasts and prints.
The data collected can be converted to useful information by using analytical tools.
Analytical tools such as Excel, SPSS, STATA, and R-program aid in analyzing data available to
data that are helpful to an organization. Data gathered is exported to an analytic tool for the
system then converted into information. The main issue is the stepping beyond printouts and list
then commence analysis of the data in a manner which is meaningful as per the corporate
responsibilities. Different forms of data are analyzed. Majorly, the data analyzed for information
include structured and unstructured as well as numeric, nominal, and ordinal. The structured data
models are often predefined in texts only easier to search. Structured data resides in data
warehouse s and relational databases. Examples of structured data are like phone numbers,
addresses, product numbers and names, information on tractions credit numbers, among others.