Descriptive Analytics and Visualization Report: Sony Album Sales

This report delves into the descriptive analytics and visualization of a dataset pertaining to Sony album sales. It outlines the data elements, emphasizing their characteristics and significance in analysis. Various visualization techniques, including horizontal bar charts, maps, tree maps, and packed bubbles, are employed to represent the data effectively. The report also addresses ethical considerations in data presentation, highlighting the importance of privacy, transparency, and avoiding manipulation. Furthermore, it elaborates on the rationale behind selecting specific chart types, the use of color and hierarchy, interactive components, and support for user motivations. The analysis covers aspects such as advertising spend versus album sales, piracy rates across different regions, and the impact of streaming services, providing a comprehensive overview of the factors influencing Sony's album sales performance. The report concludes by reflecting on the data sources and any data manipulation performed to enhance the clarity and insights derived from the visualizations.

Running head: DESCRIPTIVE ANALYTICS AND VISULAIZATION
DESCRIPTIVE ANALYTICS AND VISULAIZATION
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1DESCRIPTIVE ANALYTICS AND VISULAIZATION
Table of Contents
Additional Information...............................................................................................................3
Home Page.............................................................................................................................3
About us.................................................................................................................................3
Contact...................................................................................................................................3
AUDIENCE...............................................................................................................................4
DATA ELEMENTS...................................................................................................................5
RIGHT FIT.................................................................................................................................7
ETHICS......................................................................................................................................8
SOLUTION COMPONENT......................................................................................................9
Type of charts selected and reasons for their selection..........................................................9
How have you used colour (or not)?....................................................................................11
How have you used hierarchy in your approach?................................................................11
What interactive components did you introduce?................................................................12
How have you supported the motivations of the persona you defined?..............................13
Comment on data sources and any data manipulation you may have performed................15
Bibliography.............................................................................................................................16

2DESCRIPTIVE ANALYTICS AND VISULAIZATION
Additional Information
The following additional information pages are needed for the Word Press website:
Home Page
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About us
We at Beautiful Data Inc. are the leaders in the data analytics and presentation industry. Our
company specialises in creating beautiful dashboards for any type of data. We here analyse
the data and then convert them in to meaningful forms like graphs, histograms, pie charts,
maps, heat maps and more. Our company specializes in creating dashboards that are
meaningful and insightful. Data analytics is another speciality of our company.
Contact
Please FILL yourself.

3DESCRIPTIVE ANALYTICS AND VISULAIZATION
AUDIENCE
The target audience are the business clients for whom the dashboards will be
showcased in the upcoming online marketing campaign. The audience are generally people
who are related to the business fields but do not have the technical knowledge of the business
data generated. These people will not have time to go through the entire data so they need to
be shown the overview of the entire data quickly. The use of live dashboards puts a greater
impact than normal presentations or data sheets because a live dashboard can be filtered and
selectively shown, putting emphasis on a specific country or topic to show the sales in that
area. The datasheet used in this project is of Sony Corporation which includes their album
sales figure over the years.
The sheet contains around 150 different albums and their sale figures across multiple
countries. The dashboards will help the business clients understand the sale dynamics with an
increased focus on the areas the sales are low. The questions the clients will generally have is
regarding the performance of the company in low sale zones and how to improve them. They
will also want to review the amount of piracy happening and in which areas it is more
dominant. The dashboards will provide the audience with a better understanding of the sale
performance with the help of heat maps and help them see the quantity of piracy happening
with their products in different streaming mediums around the world. Through the dashboard
I will want to showcase to the clients, the analysis of their datasheets and their sales
information in a more interactive and visual way.

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DATA ELEMENTS
The datasheet contains of multiple variables and each has their own importance. The column
variables are described and classified as below:
1. Album No. : This is the first column in the excel sheet. This column contains the different
album numbers based on which the rest of the columns are filled. It is in the numerical format
and are discrete numbers.
2. Adverts: This column contains the total amount spend on advertisements done on the
album. This may include advertisements done online and offline both. It is given in the data
sheet in the numerical format and are discrete values.
3. Sales: This column contains the sales data that represents the amount of albums sold by
Sony. It is given in the numerical format and are discrete values.
4. Airplay: This column represents the broadcasting time allotted to each individual album
on the Fox Radio. Each album is played a fixed number of times before its release. It is given
in the numerical format.
5. Attract: The column represents the attractiveness of the singer or the band to the general
audience. The scale starts from 1 as being the worst liked to 10 being the most loved. It is
given is numerical format and has discrete values.
6. Price: This column shows the price of the album in dollars. It is represented in the
numerical format.
7. Gender: The column represents the gender or sex of the album’s singer. This is of two
types either male or female. It is given in the form of two letters “F” for females and “M” for
males.
8. Streaming services: The column represents the streaming service the album is available
on. The streaming service can be Spotify or Pandora or none of them. It is denoted in the
form of “S” for Spotify, “N” for neither and “P” for Pandora.
9. Piracy: This column represents the total number of albums downloaded illegally in the
first two weeks after the release of the album. It is given in the form of numbers in numerical
format.

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10. Top20: This column tracks the number of albums that has songs which have appeared in
the top 20 in the Billboard’s list after the first two weeks. It is given in the yes or no format.
11. Age: This column represents the age of the singers of the albums given in the datasheet.
This is given in the numerical format and is discrete.
12. No. of previous albums: This column represents the number of albums the singer had
released earlier to the current album. It is given in numerical format.
13. ITunes download: This column represents the total number of times the album has been
downloaded after the first two weeks of its release. It is given in the numerical format.
14. Genre: This column represents the different genres of the music album. It classifies the
type of genre the album falls into. It is given in categorical format.
15. Year released: This column represents the year the album was first released. It is given in
the year format.
16. Language: This column represents the language the album is sung in. It can be English,
German, Spanish or any other language. It is given in the categorical format.
17. Country: This column represents the singer or band’s own country. It is given in the
geographical country format.

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RIGHT FIT
The data types earlier mainly relate to the characteristics related to the album, its
singer and the sales of the album. The best way to represent these information is with the help
of graphs, pie charts, histograms, maps and tree maps. An important example is the use of
maps to represent the huge increase in the piracy of albums globally. The map created using
the Tableau software shows all the albums of the artists their region wise and displays the
total number of albums sold against the total number of albums pirated. Another map graph
shown in the dashboard reveals the number of singers or bands based on their countries and
the number of Top 20 albums they have. The colour of the map in a specific country deepens
as the number of top 20 albums in that country increases. The previously mentioned map also
shows the singers and their countries with the most pirated albums using darker colours. The
horizontal bar charts used here represents the total sales against the total money spent of the
advertisement of the albums and is slotted according to the origin country of the
singers/bands. Overall, all the modes of graphs used complement the data it shows or
illustrates.

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ETHICS
The main data ethics should be always maintained while displaying the information to
the clients. For example, the private customer data and the identities of the customers should
be kept private and should not be published or used without the consent of their owners.
There are major limitations on how the third party data are supposed to be used. Sensitive
third party data or crucial information cannot be shared publicly without the permission of the
concerned party. These type of data generally have restrictions on their sharing. The
dashboards should have a transparent aspect and all the data used should be mentioned
clearly. Any data without or hidden can be considered unethical. The dashboards constructed
should not try to change the minds of the people it is being shown to for gaining illegal or
undue advantages. This must be kept in mind while constructing a dashboard that it should
not interfere with the people’s mind. The graphs or the dashboards generated should not have
any racist or sexist comments or remarks shown to the clients. Such actions when made
public to large masses can have a negative impact on the society which is a very unethical
practice.

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SOLUTION COMPONENT
Type of charts selected and reasons for their selection.
The types of charts selected in this dashboard includes horizontal bars, maps, tree
maps and packed bubbles. The first chart taken is a horizontal bar chart which displays the
total amount spend by singers or bands from their respective countries on their album’s
advertisement along with the total number of albums sold. This graph fits the purpose as it
shows the money spend on advertisements and see the result on the number of albums sold
compared to the advertisements. The second graph used is a packed bubble which shows
artists from different countries in separate bubbles along with their album genre and the

9DESCRIPTIVE ANALYTICS AND VISULAIZATION
number of iTunes downloads. The larger the bubble means more the iTunes download and
the smaller bubble means low iTunes download. The genre of the albums can be
distinguished from each other with the help of the different colours.
The third graph is the map which classifies the albums based on their country of
origin and reports the total number of albums sold compared to the total number of albums
pirated. From the map it can be clearly inferred that United States of America artists are
pirated more and also sell the highest number of albums followed by the United Kingdom
singers or bands. This map is a great fit as it displays the depth of the information in a
geographical view which helps in better understanding. The fourth graph is another packed
bubble which shows the gender of the singers or artists and the language they speak or sing in
along with their average age. The graph is a good fit because it helps in demonstrating the
multiple information in a single chart. The last graph is a tree map shows the albums genre
wise and the number of airplay those albums received. The bigger and darker the box, the
more the number of airplays. These graphs are best for the dashboards as they fit perfectly
into the system.

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How have you used colour (or not)?
Yes colours have been used to separate each of the different graphs from one another. The
colours even help in separating different genres or genders from each other. In some cases,
the different shades of the same colour has been used to signify the quantity of the variables.
For example, in the piracy graph, the darker shades of the colour red signifies more number
of albums pirated.

11DESCRIPTIVE ANALYTICS AND VISULAIZATION
How have you used hierarchy in your approach?
The hierarchy concept in this data sheet is prevalent. For example, the main
component of the data sheet are the album. All other are just direct or indirect characteristics
of these albums. For example, the album number is a unique identifier based on which rest of
the album criteria’s like artists, sales, adverts, attract, price, gender, etc. variables are based.
Even in these there are subcategories like the singer or the bands have categories under them
like their gender, country of origin, age, language, attracts and number of previous albums
released. Even under the album sales there are other subcategories like airplay, adverts,
piracy, sales and price. The categories and subcategories are divided into multiple
interdependent as well as depended segments. The dependent segments are needed for the
proper understanding of the other components. For example, the adverts are depended on the
album and the artists. The “attracts” are depended on the singers or bands and cannot exist
without them. The price of the albums and the number of sales are different independent
variables and can exist independently. Overall, the system has a set hierarchy which is
followed in the dashboards created.
What interactive components did you introduce?
FULL DATA MAP:
ONLY USA DATA: