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Data Analytics Essentials: Analyze, Visualize, Interpret
Rating: 3.9 out of 5(173 ratings)
13,359 students

Data Analytics Essentials: Analyze, Visualize, Interpret

Foundations of Data Analytics: Learn to Analyze, Visualize, and Interpret Data for Informed Decision-Making
Created byLearntoupgrade Course, Makeintern Course, Learntoupgrade Online
Last updated 6/2025
English
English [Auto],

What you'll learn

  • Understand the fundamentals of data analytics and its applications.
  • Learn data collection, cleaning, and preprocessing techniques.
  • Work with datasets using Excel, SQL, and Python.
  • Apply statistical methods to analyze and interpret data.
  • Create data visualizations and dashboards to present insights.
  • Develop data-driven decision-making skills.
  • Understand the basics of machine learning and predictive analytics.
  • Communicate data findings effectively using storytelling techniques.

Course content

1 section • 11 lectures • 1h 49m total length

  • 1.1. Introduction To Data Analytics Using Tableau10:01

    Learn data analytics with Tableau by installing the free Tableau Public, creating charts and dashboards, and deriving insights from interactive visuals.

  • 1.2. Tableau Public10:35

    Learn how to install Tableau Public, verify a 64-bit Windows system, and complete setup steps from downloading the 500 MB installer to accepting license terms.

  • 1.3. Connect Tableau10:39

    Master Tableau and Power BI to visualize data, compare leading BI tools, and leverage Excel and SQL basics to interpret regional and category sales quickly.

  • 1.4. Tableau Product10:09

    Explore Tableau products, including Tableau Public for data visualization, and load Excel, CSV, JSON, text, and PDF files to analyze data, visualize patterns, and discuss outliers.

  • 1.5. Upload Data9:03

    Identify how to load and structure data by distinguishing dimensions from measures, using examples like order dates, regions, and sales, quantities, discounts, and profits.

  • 1.6. Tableau Desktop Public Edition10:07

    Distinguish dimensions as qualitative fields for categorizing data and measures as numerical values for aggregation in Tableau; connect Tableau Public to Excel and create a category versus sales bar chart.

  • 1.7. Tableau Desktop Public Edition11:50

    Create a bar chart in Tableau Desktop Public Edition by dragging category and sales, explore dimensions and measures, and customize color, size, labels, and tooltips to reveal insights.

  • 1.8. By Order ID9:42

    Drag sales into size to adjust bar widths by value; add labels showing sum of sales per category, sort, swap rows and columns, and remove grid lines.

  • 1.9. Data Validation10:34

    Format axis in data visuals by editing the axis, setting a fixed start at seven lakhs, and labeling revenue generated, with tick marks, scale options, and reference lines.

  • 1.10. Data Validation10:49

    Save the chart locally, format sales as thousands with no decimals, and build a stacked bar chart by region, using color and dynamic, descending sales sorting.

  • 1.11. Stacked Bar Chat6:17

    Explore stacked bar charts, clustered bar charts, and side-by-side bar charts, learn how to create running totals and compare category values in a visual analytics workflow.

Requirements

  • Basic computer literacy and internet access.
  • Interest in data analytics and problem-solving.
  • No prior programming or analytics experience required (but helpful).
  • Willingness to learn and practice hands-on exercises.

Description

In today’s data-driven world, organizations rely on data analytics to make informed decisions, optimize processes, and gain valuable insights. This course is designed for learners who want to develop a strong foundation in data analytics, from understanding key concepts to applying practical techniques using industry-relevant tools.

The course covers essential topics such as data collection, cleaning, visualization, and analysis. Learners will explore structured and unstructured data, work with datasets, and gain hands-on experience using tools like Excel, SQL, and Python. Additionally, the course introduces statistical methods and data storytelling techniques to help interpret and communicate findings effectively.

Through step-by-step guidance and real-world examples, students will develop analytical thinking skills and learn how to work with data in different scenarios. Whether you are looking to enhance your analytical skills, transition into a data-focused role, or apply data-driven insights to your current profession, this course provides practical knowledge that can be applied across various industries.

By the end of this course, learners will have gained the confidence to work with data, apply analytical techniques, and make informed decisions based on data-driven insights. No prior experience in data analytics is required—just a curiosity to learn and a willingness to explore the world of data.

Join us on this learning journey and take the first step in building your data analytics skills.

Who this course is for:

  • Students and professionals looking to build data analytics skills.
  • Business professionals seeking data-driven decision-making insights.
  • Aspiring data analysts, business analysts, or data enthusiasts.
  • Anyone interested in exploring data analytics for career growth or personal learning.

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