I am a tech enthusiast driven by a passion for data and innovation. With expertise in data
analytics, business intelligence, and process automation, I thrive on turning information into
strategic insights. From crafting solutions with Power Apps, Power BI, and Power Automate to
delving into machine learning with Python, I'm on a journey to harness the power of technology
for transformative impact.
Let's explore the possibilities together!
Skills
Experience
Education
Power BI
Power Apps
Python
CRYPTO PRICE INDICATOR is a Power BI report that displays the latest prices, volumes, and trends of various cryptocurrencies, such as Bitcoin, Ethereum, Binance, Dogecoin, Cardano, and Ripple. The report allows users to compare the performance of different coins, view candlestick and line charts, and zoom in and out of the data. The report is updated daily with the most recent data from reliable sources. Whether you are a crypto enthusiast, investor, or researcher, CRYPTO PRICE INDICATOR can help you stay informed and make better decisions.
This report simulates the popular FIFA PS game and shows insights on player transfers in the summer of 2022. The report has five pages: Nation, Leagues, Teams, Players, and Top 11 Players. Each page has different visuals and filters to display the data and analysis on player transfers.
The report is designed to provide a fun and interactive way to explore the world of football and player transfers. You can use the report to learn more about your favorite players, teams, and leagues, as well as discover new and emerging talents.
The Power BI dashboard shows a Substance Abuse Analysis based on data from the Survey on Drug Use and Health (NSDUH). The dashboard consists of four sections: Overview, Demographics, Substance Use, and Treatment. Each section contains interactive charts and filters that allow the user to explore the data and compare different groups and variables.
This enables stakeholders to better understand substance abuse trends, identify at-risk populations, and inform policymaking and intervention efforts.
The Power BI dashboard shows a Attrition Analysis for a company. The dashboard consists of four sections:
Employee Attrition by Department: Visualize the distribution of attrition across departments through a pie chart, providing a clear snapshot of turnover percentages within different organizational units.
Employee Attrition by Gender: Explore gender-based attrition differentials through a detailed donut chart, uncovering disparities and prompting proactive measures to address gender-related workforce challenges.
Employee Attrition by Age: Uncover trends in attrition rates across various age groups using an interactive line chart, enabling stakeholders to identify critical age ranges experiencing higher turnover rates and tailor retention strategies accordingly.
Key insights gleaned from this analysis include the identification of stress-prone departments, roles lacking in career advancement opportunities, gender-based attrition disparities, and age-related turnover patterns. Armed with actionable insights, organizations can implement targeted retention strategies to foster a more resilient and engaged workforce.
This report offers a comprehensive overview of the sales performance of Adidas products, analyzing data across different categories, regions, methods, and time periods. Through the use of charts and tables, the report provides visualizations and insights that enable stakeholders to understand sales trends, identify successful strategies, and make informed business decisions.
This report provides an in-depth analysis of Belaforia, a restaurant chain specializing in healthy and organic food. It covers key performance metrics such as revenue, profit, customer satisfaction, and food quality across various locations and time periods. By examining these metrics, stakeholders can gain valuable insights into the overall performance of the restaurant chain and identify areas for improvement.
Power Apps
Anonymous
21 Dec 2023
The Collection App is a comprehensive solution for efficient data management, tailored specifically for businesses seeking streamlined processes and actionable insights. The platform empowers users to effortlessly collect, analyze, and utilize data to drive informed decision-making and enhance business performance.
Power Apps
Anonymous
10 Sept 2020
The Student Assignment Portal is a user-friendly platform designed to simplify the process of managing academic assignments and tasks for students. It provides a centralized hub where students can access, submit, and track assignments efficiently, helping them stay organized and focused on their academic goals.
The project involved collecting financial data from multiple sources and conducting in-depth analysis to assess the performance of companies within a specific sector. By utilizing web scraping techniques and data preprocessing methods, a rich dataset encompassing a wide range of financial metrics over several years was compiled from stockanalysis.com. This dataset served as the foundation for the analysis, enabling the extraction of meaningful insights and the drawing of actionable conclusions.
# Import required libraries
from selenium import webdriver
from selenium.webdriver.chrome.service import Service as ChromeService
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from bs4 import BeautifulSoup
import pandas as pd
import time
import seaborn as sns
import matplotlib.pyplot as plt
# Set up Chrome WebDriver with headless option (no visible browser window)
chrome_options = Options()
chrome_options.add_argument("--headless")
driver_path = r"C:\Users\adeni\Shuttle_Websraper\chromedriver-win64\chromedriver.exe"
# Start the browser
chrome_service = ChromeService(executable_path=driver_path)
driver = webdriver.Chrome(service=chrome_service, options=chrome_options)
# Check the project link for the rest of code...
Analysis: ROA experienced fluctuations over the years, ranging from a low of approximately 4.73% in 2017 to a peak of nearly 9.98% in 2020.
Insights: The fluctuating trend in ROA suggests variations in the efficiency of asset utilization and profitability. The peak in 2020 indicates a period of particularly strong performance, potentially driven by improved operational efficiency or strategic initiatives.
Analysis: The quick ratio declined steadily from around 2.43 in 2016 to approximately 1.45 in 2022.
Insights: The consistent decrease in the quick ratio indicates a weakening short-term liquidity position over the years. This trend may raise concerns about the company's ability to meet its short-term financial obligations.
Analysis: Gross margin remained relatively stable throughout the period, fluctuating within a narrow range between approximately 66.64% and 68.72%.
Insights: Despite minor fluctuations, the stability of gross margin suggests consistent profitability in the company's core operations. However, a slight decline in recent years warrants further investigation into factors affecting profitability, such as cost structures or pricing dynamics.
Analysis: Book value demonstrated a consistent upward trend, rising from approximately $8.56 in 2017 to $10.32 in 2022.
Insights: The steady increase in book value reflects sustained growth in shareholder equity and asset value. This positive trajectory indicates a strengthening financial position and may enhance investor confidence in the company's long-term prospects.
Analysis: Accounts receivable days exhibited an increasing trend, rising from around 90.90 days in 2016 to approximately 122 days in 2022.
Insights: The prolonged collection period suggests challenges in efficiently managing accounts receivable, which could impact cash flow and working capital management. An upward trend in receivable days may require strategies to improve credit policies or streamline receivables management processes.
Analysis: Operating margin remained relatively stable, fluctuating between 0.24 and 0.29 over the years.
Insights: The consistency in operating margin indicates efficient cost management and revenue generation. Despite minor fluctuations, maintaining a stable operating margin reflects the company's ability to control operating expenses and generate profits from its core business activities.
The Python script showcased below is designed to run daily updates on a predefined list of cryptocurrency pairs. It utilizes the yfinance library to fetch detailed information about each pair, ranging from market cap and trading volume to opening and closing prices. The extracted data is then stored in a PostgreSQL database, ensuring seamless accessibility and organization.
Data Retrieval: By leveraging yfinance, the script efficiently retrieves real-time data for a wide range of cryptocurrency pairs. This ensures that investors have access to the latest market information, crucial for making informed decisions.
Data Storage: The PostgreSQL database serves as a robust repository for storing cryptocurrency data. With structured tables and efficient query capabilities, users can easily access historical information and track trends over time.
Updates: Scheduled to run daily via task scheduler, the script automates the process of data updates. This ensures that investors are consistently equipped with fresh insights without manual intervention, saving time and effort.
Timely Insights: With automated daily updates, investors can stay ahead of market movements and make timely decisions based on the latest data.
Streamlined Operations: By eliminating manual data collection and storage tasks, the project enhances operational efficiency, allowing investors to focus on analysis and strategy development.
Data Integrity: The use of PostgreSQL ensures data integrity and reliability, providing investors with confidence in the accuracy of the information accessed.
#Run daily update (crypto_pairs table)
import yfinance as yf
import psycopg2
import logging
# create a list of pairs to load
pairs = ['BTC-USD', 'ETH-USD', 'XRP-USD', 'LTC-USD', 'BCH-USD', 'ADA-USD',
'LINK-USD', 'BNB-USD', 'XLM-USD', 'DOGE-USD', 'XMR-USD','EOS-USD',
'TRX-USD', 'XTZ-USD', 'VET-USD', 'THETA-USD', 'ETC-USD','WBTC-USD',
'USDC-USD', 'AAVE-USD', 'XEM-USD','MIOTA-USD', 'DASH-USD', 'MKR-USD',
'FTT-USD', 'OMG-USD', 'ZEC-USD', 'ALGO-USD', 'SNX-USD', 'AVAX-USD',
'CHZ-USD', 'RUNE-USD', 'BAT-USD', 'HT-USD', 'CRO-USD', 'FTM-USD',
'HOT-USD', 'CEL-USD', 'DCR-USD', 'HBAR-USD', 'NEXO-USD', 'ZIL-USD',
'SC-USD', 'ENJ-USD', 'LSK-USD', 'RVN-USD', 'QTUM-USD', 'KSM-USD',
'MANA-USD', 'CRV-USD', 'REN-USD', 'ICX-USD', 'STMX-USD', 'SAND-USD',
'YFI-USD', 'LRC-USD', 'ZRX-USD', 'SXP-USD', 'BTT-USD', 'CVC-USD',
'DGB-USD', 'ANKR-USD', 'SRM-USD', '1INCH-USD', 'RLC-USD', 'STPT-USD',
'RLY-USD', 'OCEAN-USD', 'REP-USD', 'PERP-USD', 'HNT-USD', 'SUSHI-USD',
'AKRO-USD', 'STMX-USD', 'CTSI-USD', 'LPT-USD', 'UTK-USD', 'BTG-USD',
'EGLD-USD', 'ORN-USD', 'NKN-USD', 'AUDIO-USD', 'PAXG-USD', 'ANT-USD',
'RSR-USD', 'KP3R-USD']
# Set up the logging configuration
logging.basicConfig(filename='crypto_pair_data_upload.log', level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
# Establish a connection to the database
conn = psycopg2.connect(
host="DBhostname",
database="crypto_base",
user="DBusername",
password="yourDBpassword"
)
# Create a cursor
cursor = conn.cursor()
# Fetch detailed information for each cryptocurrency pair
for pair in pairs:
ticker = yf.Ticker(pair)
info = ticker.info
# Extract the required information
symbol = info.get('symbol', '')
short_name = info.get('shortName', '')
long_name = info.get('longName', '')
currency = info.get('currency', '')
coin_market_cap_link = info.get('coinMarketCapLink', '')
market_cap = info.get('marketCap', '')
avg_volume = info.get('averageVolume', '')
previous_close = info.get('regularMarketPreviousClose', '')
open_price = info.get('regularMarketOpen', '')
high_price = info.get('regularMarketDayHigh', '')
low_price = info.get('regularMarketDayLow', '')
volume = info.get('volume', '')
description = info.get('description', '') # Use empty string if description is not available
website = ''
# Extract website URL from description
start_index = description.find("https://")
end_index = description.find(".org/") + 4
if start_index != -1 and end_index != -1:
website = description[start_index:end_index]
# Insert the information into the crypto_pairs table
insert_query = """
INSERT INTO crypto_pairs (symbol, short_name, long_name, currency, coin_market_cap_link,
market_cap, avg_volume, previous_close,
open_price, high_price, low_price, volume, website)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
ON CONFLICT (symbol) DO UPDATE
SET symbol = EXCLUDED.symbol, short_name = EXCLUDED.short_name, long_name = EXCLUDED.long_name,
currency = EXCLUDED.currency, coin_market_cap_link = EXCLUDED.coin_market_cap_link,
market_cap = EXCLUDED.market_cap, avg_volume = EXCLUDED.avg_volume, previous_close = EXCLUDED.previous_close,
open_price = EXCLUDED.open_price, high_price = EXCLUDED.high_price,
low_price = EXCLUDED.low_price, volume = EXCLUDED.volume, website = EXCLUDED.website
"""
values = (symbol, short_name, long_name, currency, coin_market_cap_link,
market_cap, avg_volume, previous_close,
open_price, high_price, low_price, volume, website)
try:
cursor.execute(insert_query, values)
conn.commit()
logging.info(f"Inserted pair '{symbol}' successfully.")
except psycopg2.Error as e:
conn.rollback()
logging.error(f"Error inserting pair '{symbol}': {e}")
# Close the cursor and connection
cursor.close()
conn.close()
"Ahmod is hardworking and self-motivated! As an analyst, he has developed an analytical mind and is eager to offer or recommend solutions to a lingering problem. I strongly recommend him to anyone who is interested in a resourceful analyst."
Adeyemi Adegbite Product Manager at Airtel
"Adeniyi is smart, passionate and good at what he does. He is a great asset to any organisation. He is highly recommended"
Chigbogu Ofodum Product Lead at SmartCash PSB
"Working with Ahmod has been a remarkable experience for our BI team. His exceptional analytical skills and profound understanding of BI tools have significantly enhanced our data-driven decision-making processes. Ahmod's dedication and technical proficiency make him a valuable asset for any organization."
Josiah Joseph Business Intelligence Lead at Airtel
"I had the pleasure of mentoring him and witnessing firsthand his remarkable dedication to learning and rapid skill development. His humility is matched only by his ability to continually improve in his areas of expertise. It was a rewarding experience to work with him, and I have no doubt that he will excel in any future endeavors."
Monday Gabriel Senior Data Analyst at Roppi