Data Analytics

INCO Academy Work in Tech

Prepare for a new career in the high-growth field of data analytics, no experience or degree required. Data analytics is the collection, transformation, and organisation of data in order to draw conclusions, make predictions, and drive informed decision making. You’ll prepare yourself for jobs that include junior or associate data analyst, database administrator, and more.

Application requirements: Prospective students must be able to think analytically (have good analytical skills) and be comfortable with working in spreadsheets (such as Excel).

Duration: 188 hours of learning material

With 10-12 hours per week of online learning => 16-19 weeks (4-5 months) to complete, without wrap-around hours.

Modules Overview

What is this course about?

Foundations: Data, Data, Everywhere

These courses will equip you with the skills you need to apply to introductory-level data analyst jobs. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions. By the end of this course, you will: - Gain an understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job. - Learn about key analytical skills (data cleaning, data analysis, data visualization) and tools (spreadsheets, SQL, R programming, Tableau)

Ask Questions to Make Data-Driven Decisions

The material will help you learn how to ask effective questions to make data-driven decisions, while connecting with stakeholders’ needs. By the end of this course, you will: - Learn about effective questioning techniques that can help guide analysis. - Gain an understanding of data-driven decision-making and how data analysts present findings. - Explore a variety of real-world business scenarios to support an understanding of questioning and decision-making. - Discover how and why spreadsheets are an important tool for data analysts. - Examine the key ideas associated with structured thinking and how they can help analysts better understand problems and develop solutions. - Learn strategies for managing the expectations of stakeholders while establishing clear communication with a data analytics team to achieve business objectives

Prepare Data for Exploration

You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives and how to organize and protect your data. By the end of this course, you will: - Find out how analysts decide which data to collect for analysis. - Learn about structured and unstructured data, data types, and data formats. - Discover how to identify different types of bias in data to help ensure data credibility. - Explore how analysts use spreadsheets and SQL with databases and data sets. - Examine open data and the relationship between and importance of data ethics and data privacy. - Gain an understanding of how to access databases and extract, filter, and sort the data they contain. - Learn the best practices for organizing data and keeping it secure.

Process Data from Dirty to Clean

In this course, you’ll continue to build your understanding of data analytics and the concepts and tools that data analysts use in their work. You’ll learn how to check and clean your data using spreadsheets and SQL as well as how to verify and report your data cleaning results. By the end of this course, you will be able to do the following: - Learn how to check for data integrity. - Discover data cleaning techniques using spreadsheets. - Develop basic SQL queries for use on databases. - Apply basic SQL functions for cleaning and transforming data.

Analyze Data to Answer Questions

In this course, you’ll explore the “analyze” phase of the data analysis process. You’ll take what you’ve learned to this point and apply it to your analysis to make sense of the data you’ve collected. You’ll learn how to organize and format your data using spreadsheets and SQL to help you look at and think about your data in different ways. You’ll also find out how to perform complex calculations on your data to complete business objectives. You’ll learn how to use formulas, functions, and SQL queries as you conduct your analysis.

Share data Through the Art of Visualization

You’ll learn how to visualize and present your data findings as you complete the data analysis process. This course will show you how data visualizations, such as visual dashboards, can help bring your data to life. You’ll also explore Tableau, a data visualization platform that will help you create effective visualizations for your presentations. By the end of this course, you will: - Examine the importance of data visualization. - Learn how to form a compelling narrative through data stories. - Gain an understanding of how to use Tableau to create dashboards and dashboard filters. - Discover how to use Tableau to create effective visualizations. - Explore the principles and practices involved with effective presentations. - Learn how to consider potential limitations associated with the data in your presentations

Data Analysis with R Programming

In this course, you’ll learn about the programming language known as R. You’ll find out how to use RStudio, the environment that allows you to work with R. This course will also cover the software applications and tools that are unique to R, such as R packages. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways.

Google Data Analytics Capstone: Complete a Case Study

you’ll have the opportunity to complete an optional case study, which will help prepare you for the data analytics job hunt. Case studies are commonly used by employers to assess analytical skills. For your case study, you’ll choose an analytics-based scenario. You’ll then ask questions, prepare, process, analyze, visualize and act on the data from the scenario. You’ll also learn other useful job hunt skills through videos with common interview questions and responses, helpful materials to build a portfolio online, and more.