Data With Sarah
WELCOME
ABOUT ME
Welcome to Data with Sarah!I’m Sarah, a Data Analyst with an academic background in Mathematical & Statistical Sciences and Psychology, which I believe gives me a unique perspective on data.With over a decade of experience in the Foreign Exchange and Treasury sectors, I have obtained a robust skill set in problem-solving, investigation, and data reporting.I'm proficient with tools like Excel, SQL, Power BI, Tableau, BigQuery, Looker, and Looker Studio. I love digging into data to uncover trends that improve decision-making and efficiency.What really excites me about data analysis is its constant evolution—I'm always learning something new. I’m currently learning Python and eager to add it to my toolkit.I’m passionate about using data to help businesses and organizations make smarter decisions and achieve their goals.If you're looking for a data analyst eager to take on new challenges, let’s connect! Check out some of my projects or send me a message.Thanks for visiting my site!
SKILLS
Microsoft Excel / Google Sheets: VLOOKUP/XLOOKUP, IF formula, SUMIFS/COUNTIFS, pivot tables and charts, Power Query
SQL: BigQuery, MySQL, Microsoft SQL Server
Tableau, Power BI
Looker (LookML Development), Looker Studio
Data Cleaning, Analysis, and Visualization
Critical Thinking and Problem-Solving
Beginner R and Python skills
Statistics (SPSS)
Financial Analysis: Jedox tool, Variance Analysis, Commission Calculations, Ad-hoc Analysis, KPI trend analysis and dashboards
EDUCATION & CERTIFICATIONS
PROJECTS
FEATURED PROJECT
Hospital Patient Waitlist Analysis with Power BI
Cleaned and prepared hospital patient waitlist data using Power Query to allow for analysis and visualization in Power BI.
Created a dynamic dashboard using custom DAX measures to answer questions related to average and median wait lists between inpatients and outpatients.
EDUCATION & CERTIFICATIONS
EDUCATION
CERTIFIED TREASURY PROFESSIONAL
Association for Financial Professionals
Knowledge and skills related to treasury operations, corporate liquidity, and capital and risk management.
BACHELOR OF SCIENCE
University of Alberta
Mathematical & Statistical Sciences
BACHELOR OF SCIENCE
University of Alberta
Psychology
CERTIFICATIONS
DATA ANALYSIS WITH KUSTO QUERY LANGUAGE
Microsoft
Analyzing data in Azure Data Explorer using the Kusto Query Language.
PYTHON FOR BEGINNERS
Microsoft
Learning to create programs and projects in Python and working with strings, lists, loops, dictionaries, and functions.
INTRODUCTION TO PYTHON PROGRAMMING FOR DATA SCIENCE
Dataquest.io
Developing custom dimensions and measures with LookML and designing insightful dashboards in Looker.
DEVELOPING DATA MODELS WITH LOOKML
Building and maintaining scalable LookML models in Looker, enabling standardized, ready-to-use data for business users.
ANALYZE AND VISUALIZE LOOKER DATA SKILL BADGE
Developing custom dimensions and measures with LookML and designing insightful dashboards in Looker.
PREPARE, CLEAN, TRANSFORM, AND LOAD DATA USING POWER BI
Coursera
Using Power Query to load, clean, and transform data (including merging, appending, and creating aggregations) in Power BI.
DATA ANALYTICS WITH GOOGLE CLOUD BIGQUERY AND LOOKER STUDIO
Using SQL in BigQuery to analyze data and import for use in Looker Studio.
LOOKER STUDIO FOR BEGINNERS
Introduction to Google Data Studio.
SPSS STATISTICS ESSENTIAL TRAINING
Refresher introductory/intermediary course on SPSS fundamentals.
MYSQL DATA ANALYSIS
Maven Analytics
Comprehensive SQL course using MySQL.
GOOGLE DATA ANALYTICS CERTIFICATE
Foundational data analytics training program covering Google Sheets, SQL, Tableau, and R programming.
21 DAYS TO DATA CHALLENGE
Data Career Jumpstart
Introduction to SQL, Tableau, and Python.
PROJECTS
Hospital Patient Waitlist Analysis with Power BI
Power BI, Power Query
Cleaned and prepared hospital patient waitlist data using Power Query to allow for analysis and visualization in Power BI.
Created a dynamic dashboard using custom DAX measures to answer questions related to average and median wait lists between inpatients and outpatients.
Cleaning, Preparing, And Analyzing IMDb Box Office Data in Power BI
Power Query
Cleaned and prepared IMDB Box Office data from 2019 and 2020 using Power Query in Power BI so that a cursory analysis could be made.
Renamed columns, amended data types, appended the two datasets, and performed aggregations on the appended table.
How to Create a Dynamic Dashboard in Excel Using Call Center Performance Data
Excel
Created an interactive dashboard in Excel using Call Center Performance data.
Calculations include the use of SUMPRODUCT, XLOOKUP, and IF formulas.
Dynamic dashboard shows data by week, by clicking on a scroll bar and selecting the KPIs of interest.
Global COVID-19 Death and Infection Rates, Visualized - A Tableau Project
SQL, Tableau
Used SQL queries in BigQuery to analyze global COVID-19 death and vaccination data.
Tables from SQL queries were exported as CSV and then uploaded into Tableau to create visualizations and a final dashboard of global infection and death rates.
COVID-19 Data Exploration Using BigQuery - A SQL Project
SQL
Used SQL to analyze global COVID-19 death and vaccination data.
Exploratory data analysis using BigQuery to compare stats across countries.
Analyzing the MavenMovies Dataset: A SQL Project Using MySQL
SQL
Used SQL to analyze the MavenMovies dataset.
Provided actionable insights to the insurance company and business prospects regarding the company's processes, inventory, and customers.
Google Data Analytics Capstone: Bike Share
Excel | SQL | Tableau
Analyzed the data of a bike-sharing company and created visualizations to identify historical trends in annual and casual ridership.
Used Excel, SQL, and Tableau.
Provided actionable insights to help convert casual riders into annual members.
21 Days to Data Challenge: What I've Learned
SQL | Python | Tableau
Analyzed a subset of the NYPD crime complaint data from 2018 to help identify the areas and types of crime in the different boroughs.
Used SQL, Python, and Tableau.
Proposed solutions to the high crime rates by determining where and when more officers should be deployed.
