Project

Cyclisitc Case Study by Chris Aboluwoye.pptx

Google Coursera Project

The Google Data Analytics Capstone: Cyclistic case study revolves around a fictional bike-sharing company in Chicago and their efforts to optimize their marketing strategy. Here's a summary of the key points:

Customer Segmentation: The case study focuses on understanding the differences between two customer segments: casual riders and annual members (Cyclistic members).
Usage Patterns: Analysis reveals distinct usage patterns. Casual riders, likely tourists or those using the service for recreation, tend to take longer rides on weekends and favor classic bikes. In contrast, Cyclistic members, likely local commuters, take shorter weekday rides and might opt for electric or docked bikes.
Marketing Strategy: The core challenge is to convert casual riders into annual members. Since casual riders already have some familiarity with Cyclistic, the strategy might involve targeted promotions or highlighting benefits that cater to their needs (e.g., discounted weekday passes).
Data-Driven Insights: By analyzing usage data, Cyclistic can gain valuable insights into customer behavior and tailor their marketing efforts to maximize the profitability of different customer segments.

Accenture: Data Analytics and Visualization

Accenture's Data Analytics and Visualization services offer a comprehensive approach to helping businesses leverage the power of their data. Here's a summary of their key offerings:

Focus:

Unlocking Data Potential: I was able to help businesses unlock the potential of their data, which might be fragmented or underutilized. I focused on ensuring data quality, transparency, and accessibility.
Data-Driven Decisions: The goal is to empower businesses to make informed decisions based on insights gleaned from data analysis.

Services:

Data Analytics Strategy: I was able to identify business priorities and develop custom data analytics solutions with the right talent and technologies.
Data Analysis and Insights: This involves exploring and analyzing data sets to uncover patterns, trends, and relationships that can provide valuable business insights.
Data Visualization: I created clear and compelling data visualizations (charts, graphs) to effectively communicate insights to stakeholders.

Benefits:

Improved Performance: Data analytics can help businesses optimize processes, improve efficiency, and ultimately boost performance.
Competitive Advantage: By leveraging data insights, businesses can gain a competitive edge by making data-driven decisions and identifying new opportunities.
Resilience and Growth: Data-driven strategies can help businesses adapt to changing market conditions and ensure long-term growth.

Chris Aboluwoye Accenture.pptx

Accenture Dashboard

School Result Dashboard

The school result dashboard describes how students can view their detailed academic performances over the years.

In this project, I created the dataset by randomly inserting their scores on an Excel worksheet in CSV format. The next step is linking the students' images to their profiles. Also, I created a table for image links and converted images in PNG format to base64. The Image conversion was done on base64.

Afterward, I did data visualization using Power BI to uncover data patterns by highlighting their monthly percentage total. Data modeling was the key to my project. I was able to connect tables with a unique identifier (primary key) i.e Name.

In line with this, the dashboard contains results in a comparative way where students can check their monthly scores and view their respective positions with other colleagues.

Lastly, I created a welcome message using SWITCH Statement "Good morning 'Username'"

This is the code.

"Welcome Text =

VAR HOUR = HOUR(NOW())

VAR Greeting =

SWITCH (

TRUE(),

HOUR >=0 && HOUR < 5, "Good Night",

HOUR >=5 && HOUR < 12, "Good Morning",

HOUR >=12 && HOUR < 18, "Good Afternoon",

HOUR >=18 && HOUR < 24, "Good Evening"

)

RETURN

Greeting & " " & SELECTEDVALUE(Data_Table[first name ]) "

PWC Dashboard

Firstly, i visited theforage.com for a virtual simulation internship at PWC Switzerland.

Also, I was given 3 different tasks to perform

Create a dashboard in Power BI for visualizing relevant KPIs and metrics in the dataset provided.
Utilize the resources provided, including podcasts and articles, to enhance my understanding of data visualization and upskilling.
Respond to the client's request by providing a well-designed Power BI dashboard reflecting the requested KPIs.

Findings

From the interactive dashboard, I identified call center trends such as customer satisfaction, call volumes, and agent performance. The dataset was spanned from January 2021 to March 2021.

For the Key Performance Indicator, I discovered that 81% of the calls were answered by the agents while 19% were not answered/declined. Also, resolving issues with customers is an essential key to managing business. From the dashboard, 72% of customers' complaints were resolved while 28% are pending.

Furthermore, The agent speed of answer in seconds is 67.52. PWC Switzerland Call Center had 5450 customer calls. 4504 were answered while 946 were unanswered. Looking at the number of calls per month, January had the highest number of calls with 1782 while March had the lowest number of calls with 1612.

Lastly, from the agent statistics, Martha, Dan, and Dane were the top 3 agents at the call center with satisfaction ratings 3.47, 3.45 and 3.41 respectively.

Recommendations

From the interactive and detailed call center dashboard, Here are my few recommendations to improve the performance at Call Center

Equip Call Center Agents with more intensive training with skills to handle calls efficiently and effectively.
Improve on resolution rate and reduce abandoned calls
Enhancing customer satisfaction by analyzing call hand times.
Optimizing call routing amongst call center agents so as to improve customer experience and reduce waiting time.

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