Amazon Prime is another one of the most popular media and video streaming platforms. They have close to 10000 movies or tv shows available on their platform, as of mid-2021, they have over 200M Subscribers globally. This tabular dataset consists of listings of all the movies and tv shows available on Amazon Prime, along with details such as - cast, directors, ratings, release year, duration, etc.*
The data being used in this case study is taken from Kaggle and can be found here Amazon Prime Movies and TV Shows under CC0: Public Domain. It's a Business ready Dashboard that allows employees to perform data analysis for real world business related questions and scenarios such as
- Understanding what content is available in different countries
- Identifying similar content by matching text-based features
- Does Amazon Prime has more focus on TV Shows than movies in recent years
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The dashboard shows:
- The User can select the Title from the dropdown list to get the Type, Gengre, Duration, Release Year, Cast and Description about it.
- The Dashboard will provide interactive interface of list according to user choice of Country, Show Type and Genre.
- The Dashboard will show total number of movies and Tv shows released each year.
This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015. The data being used in this case study is taken from Kaggle and can be found here House Sales in King County, USA. You can use this dashboard to explore various aspects of house sales in the King County area, including pricing trends, property features, and geographical distribution.
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Map View: The map visualizes the geographical distribution of house sales in King County. You can zoom in/out and click on data points for more details. -
Price Distribution: This histogram shows the distribution of house sale prices in the dataset, helping you understand the price range of houses sold. -
Filters: Click on the calender to select particular day of the month on the left-hand side to refine the data displayed in the dashboard or filter by year built, sqft area to narrow down your analysis. -
Interactivity: Click on data points in the map or interact with other charts to highlight specific data and see details about individual house sales.
Netflix is one of the most popular media and video streaming platforms. They have over 8000 movies or tv shows available on their platform, as of mid-2021, they have over 200M Subscribers globally. This tabular dataset consists of listings of all the movies and tv shows available on Netflix, along with details such as - cast, directors, ratings, release year, duration, etc. The data being used in this case study is taken from Kaggle and can be found here Netflix Movies and TV Shows. It's a Business ready Dashboard that allows employees to perform data analysis for real world business related questions and scenarios such as
- Understanding what content is available in different countries
- Identifying similar content by matching text-based features
- Does Netflix has more focus on TV Shows than movies in recent years.
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This dashboard utilizes a dataset of cleaned and enhanced passenger reviews of British Airways from 2016 to 2023, originally sourced from the British Airline Review Dataset on Kaggle. Additionally, it integrates supplementary geographic data, enabling a deeper analytical dive into various demographics and regions.
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The dashboard provides a dynamic exploration of trends in customer satisfaction, segmented by demographics and geographic specifics. It features key performance metrics such as service quality, overall satisfaction, and value for money. Interactive elements allow users to filter data based on year, region, and type of flight, offering a customizable analysis experience.
Sheet 1: Average Metrics by Country Sheet Name: Average Metrics by Country. Displays average ratings of various metrics for each country. Parametric values include overall rating, cabin staff service, entertainment, food, ground service, seat comfort, and value. Filters applied for aircraft types, traveler type, seat type, and continent.
Sheet 2: Average Custom Metric by Month (Line Chart) Presents a line chart showing the average custom metric by month. Metrics include food satisfaction, entertainment quality, seat comfort, and overall rating.
Sheet 3: Monthly Average Metric Trends (Line Chart) Depicts a line chart illustrating the trend of average metrics over months.
Sheet 4: Average Metrics by Aircraft and Number of Reviews (Side-by-Side Bar Chart) Compares average metrics, including overall rating, cabin staff service, entertainment, food satisfaction, ground service, seat comfort, and value, across different aircraft types. Includes a side-by-side bar chart showing the number of reviews for each aircraft type.
Sheet 5: Integrated Dashboard Integrates all sheets into a single, cohesive dashboard. Provides a user-friendly interface with all metrics and parameters easily accessible.
- Trend Analysis: Track changes in passenger satisfaction over time to pinpoint specific periods of improvement or decline.
- Service Quality Assessment: Evaluate detailed feedback on different aspects of the service, from in-flight amenities to ground support.
- Regional Perceptions: Analyze how customer satisfaction varies across different regions, providing insights into localized market conditions. This dashboard serves as a vital tool for stakeholders involved in strategic planning and operational improvements at British Airways, providing a comprehensive view of the airline's performance from a passenger's perspective.
The UEFA Champions League (abbreviated as UCL) is an annual club football competition organized by the Union of European Football Associations (UEFA) and contested by top-division European clubs, deciding the competition winners through a group and knockout format. It is one of the most prestigious football tournaments in the world and the most prestigious club competition in European football, played by the national league champions (and, for some nations, one or more runners-up) of their national associations. The data being used in this case study is taken from Kaggle and can be found here UEFA Champions League Historical Dataset 1955-2023. This data includes statistics up to the final of the 2022/23 season. Note: This doesn't have any information about the European cup competition (1950-1992). It starts with the beginning of the Champions league (1992/93) season.
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According to the insights derived :
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Spanish, English, and Itallian clubs have highest number of titles with 19, 15, and 12 among them respectively.
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Real Madrid CF is the most successful club in the competition with 14 titles
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Real Madrid CF (476), FC Bayern Munchen (382), and FC Barcelona (339) have played the highest number of games.
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Cristiano Ronaldo has the highest number of appearance (183), highest number of goals by a player (140), and most goals in a single season (17).
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Carlo Ancelotti (191), Sir Alex Ferguson (190) and Arsene Wenger (178) are the top three coaches with the highest appearance.
As one of the world’s most influential reading sites, Goodreads provides a platform for people interested in talking about books. Word of mouth is one of the most powerful driving forces for book recommendation, and the social attributes of Goodreads have magnified the word-of-mouth effect of books. This goodreads datasets contains all the listed books on GoodRead books platform. The datset contain 12 columns, which include the books infromation and the rating and reviews count. The dataset in this project is from Kaggle about GoodReads books.
Through this, I've analyzed about
- Some of the top rated books and top 20 authors
- Different categories of books on Goodreads
- Publishers with highest number of books published
- Total books published Yearly
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- The User can select the Title from the dropdown list to get the book's information, rating and reviews count.
- Authors named Stephen King and P.G. Wodehouse has the highest number of books among all.
- Vintage Publishers has the highest number of books published, among those, 'The curious incident of the dog in the Night-Time' having over 2 million reviews.
The HR Analytics Dashboards project aims to leverage various data visualization and analysis tools to provide meaningful insights into HR data. By analyzing key HR metrics, such as job satisfaction, attrtion rates, education, and age, this dashboard can assist HR professionals in making informed decisions and identifying areas for improvement.
In this project, I developed HR analytics dashboards Tableau and SQL. I gathered HR data from various sources, transformed it using SQL queries, and then visualized the data using Tableau. The dashboards cover a wide range of HR metrics, including employee demographics, performance analysis, attrition rates, and department analysis. Each dashboard provides interactive visualizations and filters to allow users to explore the data and gain actionable insights.
Tools Used
- Tableau: Used for creating interactive dashboards and visualizations.
- SQL: Employed for querying and manipulating the HR data.
Link to the SQL Queries document
Screenshot of analysing Attrition Rate by Gender for different Age Group
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According to the insights derived :
- The average attrition Rate in the company is around 16% with males almost double the number of females, with an average age of 37 years. A lower attrition rate indicates better workforce stability.
- R&D department has the highest rate of attrition of 56% among others. Moreover, employees with Life Science as educational background are seen to be more prone to depart the organisation.
- Job Satisfaction is highest with job roles as Sales Executive and Research Scientist.