Study notes from data analysis training on Google, IBM and Yandex educational programs.
Data Analitics Study Notes
Guidelines and pro tips Refer to the table below for recommended guidelines and style checks for headlines, subtitles, labels, and annotations in your data visualizations. Think of these guidelines as guardrails to prevent your visualizations from becoming too crowded or busy. This can confuse or distract the audience with unnecessary
Data Analitics Study Notes
Introduction to Data Visualization and Design Principles
Data Analitics Study Notes
© Google This text outlines the purpose, examples, and limitations of six data validation types. The first five are linked to the data itself: type, range, constraint, consistency, and structure. The sixth type pertains to application code validation that accepts user input. As a junior data analyst, you may not conduct
Data Analitics Study Notes
* As a data analyst, familiar tools and processes are frequently used, but learning new ones is essential for growth. * SQL can significantly improve efficiency when pulling data and conducting analysis. * Spreadsheets, conditional formulas, the SUMPRODUCT function, and pivot tables are useful tools for performing calculations in data analysis. * Pivot tables
Data Analitics Study Notes
WarehouseWarehouse.csv484 Bytesdownload-circleOrdersOrders.csv352 KBdownload-circle HAVING function Allows you to add a filter to your query instead of the underlying table that can only be used with aggregate functions CASE function Returns records with your conditions by allowing you to include if/then statements in your query Aliasing When you
Data Analitics Study Notes
Open BigQuery and create a free account there, upload bigquery-public-data and select new_york_citibike. Scenario Review the following scenario. Then complete the step-by-step instructions. You work for an organization that is responsible for the safety, efficiency, and maintenance of transportation systems in your city. You have been asked to
Data Analitics Study Notes
Common JOINs * INNER JOIN: a function that returns records with matching values in both tables * LEFT JOIN: a function that returns all the records from the left table (first mentioned) and only the matching records from the right table (second mentioned) * RIGHT JOIN: a function that returns all records from
Data Analitics Study Notes
Data aggregation The process of gathering data from multiple sources in order to combine it into a single summarized collection * Puzzle pieces = data * Organization = aggregation * Pile of pieces = summary * Putting the pieces together = gaining insights The aggregation process helps to identify trends, make comparisons, and gain insights that wouldn'
Data Analitics Study Notes
VLOOKUP core concepts Spreadsheet functions can be used to quickly find information and perform calculations using specific values. VLOOKUP, or Vertical Lookup, is one such function that vertically searches for a certain value in a column to return a corresponding piece of information. In this reading, you’ll examine the
Data Analitics Study Notes
Review * Practices of EDA * PACE workflow * Ethics of working with data * Data visualizations Exploratory data analysis (EDA) The process of investigating, organizing, and analyzing datasets and summarizing their main characteristics, often employing data wrangling and visualization methods. EDA is an important first step in understanding any new dataset or question.
Data Analitics Study Notes
Check and change data type Check your data for inconsistent units of measurement to prevent problems during data analysis. Convert temperatures from Fahrenheit to Celsius Use the CONVERT function to change units of measurement. Convert function formula as =CONVERT(CELL, from Fahrenheit to Celsius. Enter "F", "C&
Data Analitics Study Notes
The analysis process Analysis – The process used to make sense of the data collected The goal of analysis is to identify trends and relationships within data so you can accurately answer the question you're asking The 4 phases of analysis 1. Organize data 2. Format and adjust data