Ivan Harold Gutierrez

About Me

Aspiring Data Analyst with strong foundational knowledge in Data Analysis and Power BI, specializing in ETL (Extract, Transform, Load) processes. Proficient in tools like Microsoft Excel, SQL, Power BI, and Python. Skilled in extracting data from various sources, transforming it for analysis, and loading it into Power BI to deliver meaningful insights. Highly adaptable, goal-oriented, and quick to learn, with a strong commitment to applying my skills in real-world scenarios. Passionate about continuous learning and staying updated with emerging technologies to optimize performance and contribute to business growth.I entered data analytics in January 2023 as a Data Analysis student. I started doing business through online online-based platform like "upwork". Most of the tasks of projects I completed was more on data cleaning and data visualization.Thanks for visiting my portfolio! While this page primarily demonstrates my technical ability, it's worth noting that my greatest strengths lie in my ability to collaborate with others, and tell a story with data.

Featured Projects

Visualization in Power BI

The client is an e-commerce company from Brazil, and requested a complete analysis of their operating performance. They want a detailed report covering three main parts: general dashboard, delivery performance, and product quality. Based on this analysis report, the company’s management will decide the future development of the business.The dataset contains information on 100k orders from 2016 to 2018 made at several market places in Brazil. Various order data are recorded: from order status, price, payment, and freight performance to customer location and product attributes. Also, I have access to customer reviews.

Clockster Data Analysis

Overview:

▪ Working as a data analyst team for the HR department in a medical company.
▪ The data provided by the HR department includes 10–15 parameters per day per year
(arrival/departure time, vacations, sick days, time off, etc.) on 1000+ employees of the company.
▪ Data analyst team were given task to answer the CEO formulated questions.

Data Analysis

1. Identify the most disciplined and undisciplined employees in the divisions.

From the data above, we can see that Medical Division is the most undiscipline department. They
have 26% absentee rating with 358 counts of late. It is followed by Support Center, Pharmacy, and
the most discipline among the four is the PBF.

The most undisciplined employee and also no. 1 in absent category, gathered a total of 257 undiscipline points who is an IT Supervisor. She has 221 recorded absents which is very high as this shows that she did not go to work for more than half of her scheduled workdays. She also
has 34 undertime, with 2 no recorded time outs.

To determine the most disciplined employee, the team decided that the employee should have
the least undiscipline points and with at least 22 days of duty rendered. The most disciplined
employee is 75848 with only 5 undiscipline points and already rendered 26 working days.

2. Create a visualization with the analysis of weekdays and months when most employees were late/absent (either for vacation or sick leave).

In terms of months and days, September is the peak month of employees with absences and
the highest recorded lates.

While Wednesday and Tuesday for the day of the week that has the highest absent employees.Good thing there are also a lot of present employees in that month to cover up for the absent and employees on leave. Management should keep this ratio to keep the good workflow of every department.

July on the other hand has the most recorded of present employees and the greatest number of on-time.

3. Answer the following questions. Which heads of departments tend to forgive employees for lack of discipline? Are there any favorites for any heads of departments (perhaps some employees are always forgiven for being late, given time off, etc.)?

Looking at the trend of the graph of the undiscipline points per department every month, we
can say that the all heads are always forgiving their employees as undiscipline action continues
to re-occur. Moving forward, department head should be more consistent in reminding their
subordinates in complying with the company policies. The team would like to inspect their salary if their lates and absents matches their performance however their salary table is incomplete.As for the head of the department that is always forgiven, it’s the IT supervisor. As mentioned, a
while ago he is the most undiscipline employee with 221 absents, 34 undertime, 2 no time out and he is still given 48 counts of time-off. His incompliance and misconduct should be reprimanded as this may affect the performance of his department. He should not be exempted from disciplinary action to encourage other employees to be compliant as well.

Certificates

1. Data Analytics Course2. Power BI Desktop Essentials3. Tableau Certification Course4. Python Certification Course

Thanks!

I appreciate you taking the time to visit my portfolio!If you'd like to chat about me joining your data team, feel free to contact me!

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