Google Data Analytics Certificate Flashcards
Data
A Collection of Facts
Data Analysis
The collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision making.
Data Analyst
Someone who collects, transforms, and organizes data in order to help make informed decisions.
Sherlock Holmes via Sir arthur Conan Doyle
Data! Data! Data!… I can’t make bricks without clay!
Data Analytics
The Science of data
Program Features
1) Video vignettes
2) Data Journal
3) Readings
4) Activities
5) Discussion Prompts
Course-1 Foundations
What you will learn:
1) Real-Life roles and responsibilities of a junior data analyst.
2) How businesses transform data into actionable insights.
3) Spreadsheet basics
4) Database and query basics.
5) Data visualization basics.
Skill sets you will build:
1) Using data in everyday life
2) Thinking analytically
3) Applying tools from the data analytics toolkit
4) Showing trends and patterns with data visualizations.
5) Ensuring you data analysis is fair.
Course-2 Ask
What you will learn:
1) How data analysts solve problems with data.
2) The use of analytics for making data-driven decisions.
3) Spreadsheet formulas and functions.
4) Dashboard basics, including an introduction to tableau.
5) Data reporting basics
Skills set you will build:
1) Asking SMART and effective questions.
2) Structuring how you think
3) Summarizing data
4)Putting things into context
5) Managing team and stakeholder expectations.
6) Problem-solving and conflict-resolution.
Course-3 Prepare
What you will learn:
1) How data is generated
2) Features of different data types, fields, and values.
3) Database structures
4) The function of metadata in data analytics
5) Structured Query Language(SQL) functions
Skill sets you will build:
1) Ensuring ethical data analysis practices.
2) Addressing issues of bias and credibility.
3) Accessing databases and importing data.
4) Writing simple queries
5) Organizing and protecting data.
Course-4 Process
What you will learn:
1) Data integrity and the importance of clean data.
2) The tools and processes used by data analysts to clean data.
3) Data-cleaning verification and reports.
4) Statistics, hypothesis testing, and margin of error.
5) Resume building and interpretation of job postings (optional)
Skill sets you will build:
1) Connecting business objectives to data analysis.
2) Identify clean and dirty data.
3) Cleaning small datasets using spreadsheet tools.
4) Cleaning large datasets by writing SQL queries.
5) Documenting data- Cleansing processes.
Course-5 Analyze
What you will learn:
1) Steps data analysts take to organize data.
2) How to combine data from multiple sources.
3) Spreadsheet calculations and pivot tables.
4) SQL calculations
5) Temporary tables
6) Data validation
Skills sets you will Build:
1) Sorting data in spreadsheets and by writing SQL queries.
2) Filtering data in spreadsheets and by writing SQL queries.
3) Converting data
4) Formatting data
5) Substantiating data analysis processes
6) Seeking feedback and support from others during data analysis.
Course-6 Share
What you will learn:
1) Design thinking
2) How data analysts use visualizations to communicate about data.
3) The benefits of tableau for presenting data analysis findings.
4) Data-driven storytelling
5) Dashboards and dashboard filters.
6) Strategies for creating an effective data presentation.
Skills sets you will build:
1) Creating visualizations and dashboards in Tableau.
2) Addressing accessibility issues when communicating about data.
3) Understanding the purpose of different business communication tools.
4) Telling a data-driven story
5) Presenting to others about data.
6) Answering questions about data.
Course-7 Act
What you will learn:
1) Programming languages and environments.
2) R packages
3) R functions, variables, data types, pipes, and vectors
4) R data frames
5) Bias and credibility in R
6) R Visualization tools
7) R Markdown for documentation, creating structure, and emphasis.
Skill sets you will build:
1) Coding in R
2) Writing functions in R
3) Accessing data in R
4) Cleaning data In R.
5) Generating data visualizations in R.
6) Reporting on data analysis to stakeholders.
Course- 8 Capstone
What you will lean:
1) How a data analytics portfolio distinguishes you from other candidates.
2) Practical, real-world problem,-solving.
3)Strategies for extracting insights from data
4) Clear presentation of data findings.
5) Motivation and ability to take initiative.
Skills sets you will build:
1) Building a portfolio
2) Increasing your employability
3) Showcasing your data analytics knowledge, skill, and technical expertise.
4) Sharing your work during an interview
5) Communicating you unique value proposition to a potential employer.
Businesses use ways to control data
1) Improve processes
2) Identify opportunities and trends
3) Launch new products
4) Server customers
5 ) Make thoughtful decisions
Data ecosystems
The various elements that interact with one another in order to produce, manage, store, organize, analyze, and share data.
Cloud
A place to keep data online, rather than a computer hard drive.
Data Science
Creating new ways of modeling and understanding the unknown by using raw data.
Data analytics
The science of data
Data-Driven decision-making
Using facts to guide business strategy
Dataset
A collection of data that can be manipulated or analyzed as one unit.
Analytical skills
Qualities and characteristics associated with solving problems using facts.
Analytical skill set 5 Essential Points
1) Curiosity
2) Understanding context
3) Having a technical mindset
4) Data design
5) Data strategy
Context
The condition in which something exists or happens .
A technical mindset
The ability to break things down into smaller steps or pieces and work with them in an orderly and logical way.
Data Design
How you organize information
Data strategy
The Management of people, processes and tools used in data analysis.
