Accenture plc is a US multinational professional services company based in Dublin, specializing in information technology services and consulting. A Fortune Global 500 company, it reported revenues of $64.1 billion in 2023. Accenture embraces the power of change to create 360° value and shared success for our clients, people, shareholders, partners, and communities.
A data analyst sits between the business and the data.
What do we mean by that?
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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.
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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.
- 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 you can use to merge tables.
There is a lot of information here and it’s easy to get lost in the data. So, to make sure you are using the right data to answer the business questions you’ll follow these steps:
- Requirements gathering
- Data cleaning
- Data modelling
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
Now we want to figure out the top 5 categories. To complete your data modelling, follow these steps:
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Create a final data set by merging your three tables together
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Figure out the Top 5 performing categories
The end result should be one spreadsheet which contains:
- A cleaned dataset
- The top 5 categories
We know that the client wants to understand the top 5 content categories. Have a think about what are the best ways to present this? In a pie chart? In a bar chart?
There are also some other interesting insights that we might want to share with them. For example:
- How many unique categories are there?
- How many reactions are there to the most popular category?
- What was the month with the most posts?
When presenting to the client there are a few things that you should remember:
They may not all be familiar with data, so you need to make sure you talk to them in business-friendly language.
You want to show them that you’ve understood their business and requirements, so use their terminology and language relevant to the task.
This is your time to shine and to show them how great you are! Try to present your work with confidence and conviction, if you don’t feel confident talking about your results then it’s a good indication that you don’t understand them fully or may need to revisit the dataset! Speaking about your results should feel natural when you explain what you’ve done.
A good presentation always takes a lot of preparation. The more you practice presenting your content, the more confident you will be when the time comes. Practice with your housemates, friends, family, and anyone who is free! Ask for feedback and keep improving until you’re happy with your presentation and you’re confident in presenting your content.
- Completed a simulation focused on advising a hypothetical social media client as a Data Analyst at Accenture
- Cleaned, modeled and analyzed 7 datasets to uncover insights into content trends to inform strategic decisions
- Prepared a PowerPoint deck and video presentation to communicate key insights for the client and internal stakeholders
I recently participated in Accenture’s Data Analytics & Visualization job simulation on the Forage platform, and it was incredibly useful to understand what it might be like to participate in a typical project team at Accenture, and to use Excel and data analytics and visualization skills in a realistic context. Through this program I realized that I really enjoy cleaning, modelling and analyzing client data, creating slides to communicate findings and presenting insights back to the client. I would love to apply what I've learned in a diverse project team at a company like Accenture.