My Certificate: Acceenture Forege Certificate

Task 1: Project Understanding

Key roles and responsibilities of a Data Analyst

A data analyst sits between the business and the data.

What do we mean by that?

The Business refers to the client and your internal team members who won’t be involved in detailed data analysis.

They rely on your analysis to make strategic business decisions.

Importantly, not everyone will have a strong understanding of data. Your job is to communicate your data findings simply and clearly for everyone to understand.

 

The Data refers to the relevant data sources that you will clean, process, and use to generate interesting insights for the business.

As a Data Analyst at Accenture, you’ll get to work across a range of different clients and projects. This keeps things interesting, as there are always new problems to solve and new topics to learn about.

However, our clients often want accurate results in a tight timeframe. The pace of work is fast and you’ll need to get up to speed on new projects as quickly as possible.

Now you know a bit more about the role, let’s get back to the project with Social Buzz.

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User ID: Unique ID of the user (automatically generated) Name: Full name of user Email: Email address of user Profile User ID: Unique ID of a user that exists in the User table Interests: Interests of the associated user Age: Age of the associated user Location User ID: Unique ID of a user that exists in the User table Address: Full address of the user Session User ID: Unique ID of a user that exists in the User table Device: Mobile device that they used for this session on the application Duration: Amount of time in minutes that this user stayed active on the application during this session Content ID: Unique ID of the content that was uploaded (automatically generated) User ID: Unique ID of a user that exists in the User table Type: A string detailing the type of content that was uploaded Category: A string detailing the category that this content is relevant to URL: Link to the location where this content is stored Reaction Content ID: Unique ID of a piece of content that was uploaded User ID: Unique ID of a user that exists in the User table who reacted to this piece of content Type: A string detailing the type of reaction this user gave Datetime: The date and time of this reaction ReactionTypes Type: A string detailing the type of reaction this user gave Sentiment: A string detailing whether this type of reaction is considered as positive, negative or neutral Score: This is a number calculated by Social Buzz that quantifies how “popular” each reaction is. A reaction type with a higher score should be considered as a more popular reaction.

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Task 2: Data Cleaning & Modeling

Data cleaning is a common and very important task when working with data

What you need to do:

First: Open the three data sets below

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.
  • Think about how each column might be relevant to the business question you’re investigating. If you can’t think of why a column may be useful, it may not be worth including it.

 

Your end result should be three cleaned data sets. 

If you get stuck, we’ll provide some guidance in the next step. But we encourage you to give it a go first!

Quick explanation - how to clean the data set

Nice work cleaning the data. If you got stuck, here is a quick video on how to clean your data set.

Once you’re ready move onto the next step.