DataWiz

Data 
Analyst

This course will introduce students to the essentials of collecting information and communicating insights to an audience using the magic of data. Students will be exposed to techniques in Excel, SQL and Python to tell a story with data in a meaningful way. At the end of this course, students will develop a foundation on how to explore data and present findings to a business problem. Students will complete case studies to solidify concepts and will practice communicating these insights to a wider audience. 

What is a Data Analyst?

A Data Analyst is someone who collects, processes and performs statistical analysis of data. They play a unique role among the many other data-related fields found in today’s businesses. Data Analysers also work on identifying patterns and  trends in data set as well, working alongside organizations. He or she can translate  numbers and data into plain English in order to help various companies make better financial and business decisions. They will take the data and use it to better the  company’s financial problems and deal with issues that cost the company money.

According to the World Economic Forum, due to the increasing amount of data collection and usage, the data analyst field will be in high demand after 2020. Data Analysis is viewed as a crucial factor for the future because of the value that can be derived from data. The value of Data Analyzers is continuing to grow, which is creating more jobs and more career advancement opportunities. It is also said by the Bureau of Labor Statistics (BLS), employment of data analysts is projected to grow 11% from 2014 to 2024, faster than the average for all occupation.

The position of Data Analyst is a very safe career to pursue with lots of job security as the field of Data is always growing. About 2.5 quintillion bytes of data is created each day at the current pace and more and more Data Analyst positions are opening up. According to Glassdoor, Data Analysts earn an average pay of $67,377 in 2019.

As a data analytics professional, you are not restricted to working in a particular industry. Every industry requires data analytics. You are free to be working in any industry in the sector of Data. Some core industries that require Data Analysts are in financial, healthcare, retail, logistics and human resource management. 

Tools that will be covered in this course

trifacta icon

Course Pathway

Module 1

Intro to Data Analytics

We will begin this course by exploring the importance of data analytics and where it can be applied. We will look at the various careers available in data analytics. Finally, we will introduce the CRISP-DM analytics process.

Learning Objectives
By the end of this module, you should be able to:

1. Recognize the different types of data analytics
2. Identify the opportunities and use cases provided by data analytics
3. Understand the analytics lifecycle
4. Develop an appreciation for identifying the business problem prior to performing data analysis
1
Module 1
Module 2

Descriptive Statistics

In this module, we will introduce basic statistical concepts as well as common measures used in the field of descriptive statistics.

Learning Objectives
By the end of this module, you should be able to:

1. Understand and apply various statistical concepts such as measures of central tendency and measures of dispersion

2. Use the Data Analysis Toolpak in Excel to produce summary statistics in a dataset

2
Module 2
Module 3

Data Analysis in Excel

In this module, we will be exposed to the many possibilities of using Excel for data analysis.

Learning Objectives
By the end of this module, you should be able to:

1. Create Pivot Tables and Pivot Charts
2. Analyze data using formulas and advanced excel functionalities
3. Develop basic dashboards in Excel using tables and charts
4. Use Power Pivot for more complex data needs

Requirements
Students should have access to Microsoft Excel to follow along with class exercises and complete the week 3 project. Excel 2013 or later is recommended.
3
Module 3
Module 4

Data Analysis using SQL

In this module, we will look at understanding common database concepts and developing basic competency using SQL.

Learning Objectives
By the end of this module, you should be able to:

1. Understand the basic terminology of SQL
2. Apply best practices when writing queries/code in SQL
3. Use SQL to pull custom data for analysis

Requirements
Students should have the Anaconda software downloaded.
https://www.anaconda.com/products/individual

4
Module 4
Module 5

Exploratory Data Analysis (EDA) and Feature Engineering using pandas

In this module, we will look at the various stages of EDA in Python.

Learning Objectives
By the end of this module, you should be able to:

1. Understand the stages of EDA
2. Apply these concepts to a dataset using the pandas package in Python
3. Create custom numerical and categorical variables to supplement data

Requirements
Students should have the Anaconda software downloaded.
https://www.anaconda.com/products/individual

5
Module 5
Module 6

Data Visualization using matplotlib/seaborn

In this module, we will understand the best practices of using data visualization to communicate findings.

Learning Objectives
By the end of this module, you should be able to:

1. Identify the best visual for a specific type of analysis
2. Apply best practices when creating dashboards or visualizations used to supplement an analysis and communicate insights
3. Create visualizations using the matlotlib or seaborn packages in Python

6
Module 6
Module 7

Introduction to Machine Learning with scikit-learn

In this module, we will learn about the basic types of machine learning. Students will develop their own model to create predictions or identify clusters in their data.

Learning Objectives
By the end of this module, you should be able to:

1. Understand basic machine learning terminology
2. Develop a simple linear regression model using the sklearn package in Python
3. Identify clusters within data using unsupervised learning


Requirements

Students should have the Anaconda software downloaded.
https://www.anaconda.com/products/individual

7
Module 7

Start your career in Data Analytics. Enroll today!