For the Project The client has sent through: • 7 data sets - each data set contains different columns and values • A data model - this shows the relationships between all of the data sets, as well as any links that can use to merge tables. For these need to follow the below steps:
- Requirements gathering
- Data cleaning
- Data modelling Data sets : ->Reaction, Content, and Reaction Types as data sets. To clarify why these selection has made: • The brief carefully it states that the client wanted to see “An analysis of their content categories showing the top 5 categories with the largest popularity”. • As explained in the data model, popularity is quantified by the “Score” given to each reaction type. • It need to data show the content ID, category, content type, reaction type, and reaction score. • So, to figure out popularity, adding up the content categories which have the largest score.
Second: Clean the data by: • removing rows that have values which are missing, • changing the data type of some values within a column, and • removing columns which are not relevant to this task.
At end result should will be three cleaned data sets. Now we finding the top 5 categories,to complete the data modelling, follow bt the steps:
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Creating a final data set by merging your three tables together • Taking Reaction table as base table, then at first joining the relevant columns from Content data set, and then the Reaction Types data set. • By using “VLookUp” formula.
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Figuring out the Top 5 performing categories • Add up the total scores for each category. • By using “Sum If” formula.
At,the end result will be one spreadsheet which contains:
- A cleaned dataset
- The top 5 categories