This dashboard is an analysis of the cause of deaths in Australia and its causes for the period 2017 to 2021. According to these graphs there's a low number of deaths in 2021 compared to year 2020. Year 2021 was the second year of pandemic and the doctors certified only the key causes which is cancers, heart diseases and dementia and the adequate time was not available to complete the coronial investigations. Females always hold a lower death rate through out the last 5 years and highest number of deaths has occurred in the age group 85 to 89. Males maintain a higher death rate compared to females and the higher deaths has transpired in the ages group of 90 to 94. All states and Australia as a whole has a mean age of death within 80 -83 and Northern Territory is in its 60s.

This dataset is about about combination of attendance rate for Semester 1 in SA Government Schools by year level and Index of Educational disadvantage by Government Schools in SA for year 2000. *Combination of this two datasets are to analyse the relationship between the attendance levels of students and the index of educational disadvantage.The most disadvantage schools have an index of 1 and the least disadvantaged have an index of 7.

This graph was published in the cricinfo website and the article was about which top cricket city would win the world cup in 2019. Under this main topic, author is talking on match winning factors and the primary objective of this graph was to portray the cricket cities with the best batting averages. But I believe the visualization was difficult to understand and had the following three main issues: * It is not visually supportive to understand the meaning of the graph. You need to read the text to know what this graph is visualising. According to the text in the graph highest batting averages are from Sydney but when you look at the visualization Sydney is the smallest compared to other four cities. The author has not given any values to the proportion of the outcomes. The shape's size, height or width doesn't present any difference as we can see the lowest average is Mumbai but it stands as the tallest in the graph. Therefore we cannot find a visual gist in this graph. * The colors used in this graph is not user friendly. Red and Blue are primary colors and they are very strong colors too. When the user looks into stronger colors and high contrast can produce after images when the viewer looks away from the screen. It is straining the eyes. * Also there's no clear description about the period of the data for this graph. It could be since the beginning of cricket to 2019 of world cups or starting from world cups of different period of time to 2019.

Why not watch is keen to remain sustainable in this competitive streaming market industry by experimenting new methodologies to increase viewer engagement (hours) in order to maximize advertising revenue and expand the customer base. One of the company’s strategies involves regularly changing the algorithm in the recommendation engine so it can dynamically suggest shows to viewers based on their viewing habits. The executives in WNW has handed over this project to its analytical team to find out if the new algorithm is worth rolling to their subscribers. This report details the findings of that analysis. Analytical team has performed various statistical tests on the full dataset, the control group and treatment group respectively to distinguish if any positive impact has triggered for the treatment group with the new algorithm.