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Data Analytics

at General Assembly - Online

(2640)
Course Details
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$3,950
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Except: Nov 11 & Nov 25
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Description
Class Level: All levels
Age Requirements: 18 and older
Average Class Size: 20

Flexible Reschedule Policy: This provider has flexible, free rescheduling for any-in person workshop. Please see the cancellation policy for more details

What you'll learn in this data analyst training:

This is a part time course.

This course will teach you how to use large datasets to make critical decisions.

Unit 1: Exploring Data with Excel

Understanding the Value of Data

  • Explore the value of data.
  • Work your way through the data analytics workflow.
  • Unlock the power of Microsoft Excel to utilize its analytical tools — no matter your experience level.
Preparing Data in Excel
  • Learn best practices for collecting and cleaning data in Excel to ensure accurate analysis results.
  • Manipulate real-world data sets using advanced nested logical functions (IF, OR, and AND).
Cleaning Data in Excel
  • Clean large, unruly data sets by removing duplicate rows and performing text manipulations.
  • Transform and rearrange columns and rows within spreadsheets to prepare data for analysis.
  • Gain insight into data analysis by manipulating data formats.
Referencing Data in Excel
  • Use the VLOOKUP and HLOOKUP functions to manipulate data sets.
  • Look up values in other tables using the functions INDEX and MATCH.
Aggregating Data in Excel
  • Summarize data using pivot tables.
  • Execute Excel aggregation commands (SUM, AVERAGE, COUNT, etc.) and their conditional variants (COUNTIF, COUNTBLANKS, etc.) to summarize data sets.
Visualizing Data in Excel
  • Derive insights from data by highlighting cells based on conditionals.
  • Use scatter plots, bar graphs, and histograms to visualize data.
  • Explore color theory and how it applies to data visualization.
  • Build your own data dashboard using industry best practices.
  • Apply visual design principles to your dashboard to present your findings clearly.
Applying Statistics for Data Analysis
  • Understand the value of descriptive and inferential statistics.
  • Learn to describe data and identify outliers using its mean, median, mode, range, and variance.
  • Make predictions about larger populations using sample data.
Building Data Narratives
  • Learn best practices for describing analysis techniques.
  • Communicate insights and implications for stakeholders.
  • Deliver short, effective presentations sharing your findings.
  • Provide context for your audience by identifying and presenting the salient statistics.
Unit 2: Managing Data with SQL

Understanding the Fundamentals of Databases and SQL
  • Practice the fundamentals of Structured Query Language (SQL).
  • Use database schema to design appropriate queries using SQL.
  • Explore the differences between relational databases (tabular data storage) and document-based databases (key-value pairs).
Querying Large Databases in SQL
  • Collect data using standard SQL commands (Create, Update, Truncate, etc.).
  • Filter data using advanced SQL commands (Where, Group By, Having, Order By, Limit).
  • Obtain data by creating relationships between tables using Joins.
  • Gather filtered data using SQL Boolean operators (AND and OR) and SQL conditional operators (=,!=,>,<,IN, and BETWEEN).
Aggregating Data in SQL
  • Create relationships between tables and data points (including has_many and many_to_many) using Join tables.
  • Write Boolean statements with SQL conditional operators (=,!=,>,<,IN, and BETWEEN) and null functions (“IS NULL,” “IS NOT NULL,” and “NVL”).
  • Clean data using SQL mathematical functions (ABS, SIGN, MOD, etc.).
  • Summarize data sets by employing aggregation commands (“Sum,” “Average,” “Count,” etc.).
  • Determine data trends by applying aggregation methods.
Writing Efficient, Dynamic Queries
  • Use CASE statements to structure data and create new attributes.
  • Combine multiple subqueries into one using “WITH AS.”
Creating a Local Database
  • Create a local database using data sets you bring into the classroom.
  • Upload and export data using a local database.
Unit 3: Communicating Data Analysis with Tableau

Exploring the Fundamentals of Tableau

  • Get hands-on, practical experience navigating the Tableau software interface.
  • Connect your data to Tableau and identify the best ways to visualize and display your results.
Visualizing Data and Mapping in Tableau
  • Use bubble graphs to visualize data.
  • Display geocoded information for your data.
Designing Data Dashboards in Tableau
  • Contextualize analysis results by creating Tableau dashboards.
  • Incorporate charts and conditional formatting into your dashboard using supporting information specific to a particular data set.
Working with Data Across Excel, SQL, and Tableau
  • Understand the use of specific data analysis software.
  • Apply all the tools and skills you’ve acquired in Excel, SQL, and Tableau to analyze a data set from start to finish.
Final Project Presentations
  • Identify strengths and areas for improvement in your analytical skills with feedback from peers, instructors, and guest panelists.

Remote Learning

This course is available for "remote" learning and will be available to anyone with access to an internet device with a microphone (this includes most models of computers, tablets). Classes will take place with a "Live" instructor at the date/times listed below.

Upon registration, the instructor will send along additional information about how to log-on and participate in the class.

School Notes:
For students enrolling in 12 week part time and immersive classes, it is not recommended that you book more than one class simultaneously.

Still have questions? Ask the community.

Refund Policy
If you can't make it to a class/workshop, please email us at [email protected] at least 7 days before the scheduled event date. No refunds will be given after this timeframe.

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