Tableau

Projects that include this skill

Bike sharing Data Analysis for data-driven business decisions

Goal: Convert casual users of the service into paying members Source: primary data, 12 datasets containing data for 2022 Context: You are a junior data analyst working in the marketing analyst team at Cyclistic, a bike-share company in Chicago. The marketing director believes the company’s future success depends on maximizing the number of annual memberships.…

27th October 202315th December 2023

Posts that include this skill

I’m officially a Google Certified Data Analyst!

I’m excited to share that I recently earned the Google Data Analyst Certification. This is a significant achievement for me, and I’m proud of the hard work and dedication that went into earning it. What is it? The “Google Data Analytics Certificate” is a professional certificate that is designed to prepare learners for entry-level data…

18th October 202325th October 2023

Definition

Tableau is a data visualization and analytics software package that helps data scientists create interactive dashboards and reports. It is one of the most popular data visualization tools in the world, and is used by a wide range of organizations,including Fortune 500 companies, startups, and government agencies.

Tableau is easy to use and does not require any prior programming experience. Data scientists can simply drag and drop data fields onto the canvas to create visualizations. Tableau also includes a variety of built-in features that make it easy to create interactive and informative visualizations, such as:

Filters: Filters allow data scientists to focus on specific subsets of data.
Parameters: Parameters allow data scientists to create dynamic visualizations that can be updated by users.
Drill-downs: Drill-downs allow users to explore data in more detail by clicking on specific elements of a visualization.
Storytelling: Tableau allows data scientists to create stories that explain their findings and communicate insights to others.

Tableau is a valuable skill for data scientists because it allows them to:

Create effective data visualizations: Tableau makes it easy to create data visualizations that are both informative and visually appealing. This is important because data visualizations can help data scientists to identify patterns and trends in data, and to communicate their findings to others in a clear and concise way.
Collaborate with others: Tableau makes it easy to share and collaborate on data visualizations. This is important because data scientists often need to work with other stakeholders, such as business analysts and executives, to communicate their findings and make decisions.
Make better decisions: Tableau can help data scientists to make better decisions by providing them with insights into their data. For example, data scientists can use Tableau to identify trends, predict outcomes, and optimize processes.

Why it’s important in Data Science

Overall, Tableau is a valuable skill for data scientists because it allows them to create effective data visualizations,collaborate with others, and make better decisions.

Here are some examples of how Tableau is used in data science:

A data scientist uses Tableau to create a dashboard that shows the sales performance of a company by product category and region. The dashboard is used by the company’s sales team to track their progress and identify areas for improvement.
A researcher uses Tableau to create a visualization that shows the relationship between gene expression and disease risk. The visualization is used by the researcher to identify new drug targets and develop more effective treatments.
A financial analyst uses Tableau to create a report that shows the performance of the company’s stock portfolio over time. The report is used by the company’s executives to make investment decisions.

These are just a few examples of how Tableau is used in data science. Tableau is a powerful tool that can be used to solve a wide range of problems in data science.