/IBM-DAC

Data Analyst Capstone

Primary LanguageJupyter Notebook

Data Analyst

Data Analyst Capstone on report identified trends in technology skills requirements on for an by a global IT solutions and business consulting services firm

Project Documentation

  1. Identified business problem, solution, and questions

    • First task is to collect the top programming skills that are most in demand from various sources including:
      • Job postings
      • Training portals
      • Surveys
    • Next task after collecting enough data, you will begin analyzing the data and identify insights and trends that may include:
      • What are the top programming languages in demand?
      • What are the top database skills in demand?
      • What are the popular IDEs?

  2. Data Collections and Descriptive Data Analysis

    • Collecting data using APIs
    • Collecting data using Web scraping
    • Explored data using descriptive and fundamental statistics

  3. Data Preprocessing and Data munging

    • Data Wrangling: Finding Duplicates, Removing Duplicates, Finding Missing Values, Imputing Missing Values, Normalizing data

  4. Statistical Programming and Exploratory Data Analysis

    • Exploratory Data Analysis: Distributions, Outliers, Correlations

  5. Data Visualization using Python

    • Visualized distribution of Data using histogram
    • Visualized relationship using scatter, bubble, and boxplot
    • Visualized composition & comparison using pie chart, bar chart, and stacked chart

  6. Dashboard Creation using IBM Cognos Analytics

    • Created impactive, attractive and interactive dashboards on Cognos

  7. Storytelling findings with presentation

    • Presented Project

Auxillary and Context

In order to get the IBM Data Analyst Professional Certificate I worked with a variety of concepts, resources, data sources, project scenarios, and data analysis tools thereby gaining practical experience with data manipulation and applying analytical techniques.

Gained professional experience and a firm grasp on the technical skills required to effectively gather, wrangle, mine, and visualize data, as well as soft skills for working with stakeholders and storytelling with data to engage the audience.

Technical Skills include:

  • Spreadsheet(i.e MS Excel)
  • Python Programming(i.e Modules such as Pandas, Numpy, Matplotlib, Plotly, etc)
  • Data Visualization(DataViz)
  • SQL(i.e DDL, DML)
  • Data Science
  • IBM Cognos Analytics
  • IBM Cloud Services
  • Dashoards