Google Data Analytics Certification

Database

Collection of data stored in computer system

Data life cycle

Plan → capture → manage → analyze → archive → destroy

Plan

What data do we need? How will it be managed? Who’s responsible for it? What are the optimal outcomes?

Capture

Collecting data from variety of sources and brought into the organization

Manage

Where to store data? What tools to keep it secure? Actions needed for proper maintenance?

Analyze

Data is used to solve problems, make decisions, support business goals

Archive

Storing data in a place where it’s available, but may not be used again

Destroy

Important for protecting company’s private information and private data about customers

Steps of data analysis

Ask→ Prepare → Process → Analyze → Share → Act

Ask

Define problem and make sure we understand stakeholder expectations.

Defining problem involves looking at current state and identify how it’s different from the ideal state.

Who are the stakeholders? Maintain strong communication with stakeholders.

Stakeholder

People who help make decisions, influence actions and strategies, and have specific goals they want to meet.

Prepare

Collect and store data that will be used for analysis process.

Process

Find and eliminate errors/inaccuracies that can get in the way of results

Cleaning data, transforming it into more useful format, combining datasets, removing outliers

Fix typos, inconsistencies, or missing/inaccurate data

Veryfing and sharing data cleansing with stakeholders

Analyze

Using tools to transform/organize info to make useful conclusions, make predictions, and drive informed decision-making

Share

Interpreting results and sharing them with others to help stakeholders make effective data-driven decisions.

Data visualization is key

Act

Business taking all insights you have provided and uses them to solve the original business problem.

Formula

Set of instructions that performs a specific calculation using the data in a spreadsheet.

Function

Preset command that automatically performs a specific process or task using the data in a spreadsheet.

Query language

Programming language that allows you to retrieve and manipulate data from a database.

Database

A collection fo data stored in a computer system.

Query

Request for data/info from a database

Issue

Topic/subject to investigate

Business task

Question/problem data analysis answers for a business

Fairness

Ensuring that your analysis doesn’t create or reinforce bias

Structured thinking

Process of recognizing the current problem or situation, organizing available info, revealing gaps/opportunities, and identifying options

Making predictions problem type

Using data to make informed decision about how things may be in future

Categorizing things problem type

Assigning info to different groups or clusters based on common features

Spotting something unusual problem type

Identifying data that’s different from norm

Identifying themes problem type

Grouping categorized info into broader concepts

Discovering connections problem type

Finding similar challenges faced by different entities and combining data and insights to address them

Finding patterns problem type

Using historical data to understand what happened in the past and is therefore likely to happen again

Closed-ended questions

Only answered with yes or no, doesn’t really provide useful insights

SMART questions

Specific - simple, significant, focused on single topic or a few closely related ideas

Measurable - can be quantified and assessed

Action-oriented - encourage change

Relevant - matter, important, have significance to the problem you’re solving

Time-bound - specify the time to be studied

Data-inspired decision-making

Explores different data sources to find out what they have in common

Report

Static collection of data given to stakeholders periodically

Pros:

• High-level historical data

• Easy to design/use

• Pre-cleaned and sorted data

Cons:

• Continual maintenance

• Less visually appealing

• Static

Dashboard

Monitors live incoming data

Pros:

• Dynamic, automatic, interactive

• More stakeholder access

• Low maintenance

• More visually appealing

Cons:

• Labor-intensive design

• Can be confusing

• Long time to fix bugs

• Potentially uncleaned data

Pivot table

Data summarization tool used in data processing, used to summarize, sort, reorganize, group, count, total, or average data stored in database

Metric

Single, quantifiable type of data that can be used for measurement

Can help calculate customer retention rates

Metric goal

Measurable goal set by company and evaluated using metrics

Mathematical thinking

Looking at problem and logically breaking it down step-by-step so you can see the relationship of patterns in data, using that to analyze the problem

Small data

• Specific

• Short time period

• Day-to-day decisions

• Ex:) How much water you drink a day

Big data

• Large and less specific

• Long time period

• Usually need to be broken down

• Big decisions

Operator

Symbol that names type of operation or calculation to be performed

Cell reference

A cell or range of cells in a worksheet that can be used in a formula

RowNum like A1

Common errors

#ERROR! - Formula can’t be interpreted as input (parsing error)

#N/A - data in formula can’t be found

#NAME? - formula/function name isn’t understood

#NUM! - formula/function can’t be performed as specified

#VALUE! - general error that could indicate problem with formula or referenced cells

#REF! - formula is referencing a cell that is no longer value or has been deleted

Problem domain

Specific area of analysis that encompasses every activity affecting or affected by the problem

Scope of work (SOW)

An agreed-upon outline of the work you’re going to perform on a project

Before communicating…

1. Who is my audience?

2. What do they already know?

3. What do they need to know?

4. How can I communicate that effectively to them?