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How Exploratory Data Analysis Helped Me Solve Million-Dollar Business Problems

Towards AI

Photo by Luke Chesser on Unsplash EDA is a powerful method to get insights from the data that can solve many unsolvable problems in business. In the increasingly competitive world, understanding the data and taking quicker actions based on that help create differentiation for the organization to stay ahead!

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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. These tools will help make your initial data exploration process easy.

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Data Analysis vs. Data Visualization – More Than Just Pretty Charts

Pickl AI

Summary: Data Analysis focuses on extracting meaningful insights from raw data using statistical and analytical methods, while data visualization transforms these insights into visual formats like graphs and charts for better comprehension. Is Data Analysis just about crunching numbers?

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Exploratory Data Analysis on Stock Market Data

Mlearning.ai

Exploratory Data Analysis on Stock Market Data Photo by Lukas Blazek on Unsplash Exploratory Data Analysis (EDA) is a crucial step in data science projects. It helps in understanding the underlying patterns and relationships in the data. Load the Dataset The first step is to load the dataset.

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The project I did to land my business intelligence internship?—?CAR BRAND SEARCH

Mlearning.ai

The project I did to land my business intelligence internship — CAR BRAND SEARCH ETL PROCESS WITH PYTHON, POSTGRESQL & POWER BI 1. Figure 15: Step 4 — Loading data Once we’ve clicked on “Load”, Power BI will connect with pgAdmin4. Finally, it will show us the data. Figure 16: Dashboard data 4.3.

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Different Python Libraries for Data Visualisation

Pickl AI

Choosing the proper library improves data exploration, presentation, and industry decision-making. Introduction Data visualisation plays a crucial role in Data Analysis by transforming complex datasets into insightful, easy-to-understand visuals. It helps uncover patterns, trends, and correlations that might go unnoticed.

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Announcing the Winners of ‘The NFL Fantasy Football’ Data Challenge

Ocean Protocol

AI / ML offers tools to give a competitive edge in predictive analytics, business intelligence, and performance metrics. Fantasy Football is a popular pastime for a large amount of the world, we gathered data around the past 6 seasons of player performance data to see what our community of data scientists could create.