EDA helps data scientists to manipulate data sources to get the answers they need, and as a result making the data analysis process easy for discovering patterns, testing a hypothesis, spotting anomalies, or checking assumptions.
Posts by Priya Telang
Data Wrangling and Exploratory Analysis
Data wrangling and exploratory analysis are part of data science and play an important role in the data analysis process as they help in properly structuring the data through data detection, data cleaning, data summarizing, etc.
Introduction to Descriptive Statistics
Descriptive statistics provide simple, quantitative summaries of datasets, usually combined with descriptive graphics. After data collection, the first step is to get basic information of the data using descriptive statistics. This provides easy-to-understand information that helps answer basic questions based on the average, spread, deviation of values and so on. They give analysts a rough idea about what the data is indicating so that later they can perform more formal and targeted analyses.
Exploratory Data Analysis using Data Visualization Techniques!
We can define exploratory data analysis as the essential data investigation process before the formal analysis to spot patterns and anomalies, discover trends, and test hypotheses with summary statistics and visualizations.
What is ETL (Extract, Transform, Load)?
How is modern ELT different from the traditional ETL?
Tableau Certification – A Comprehensive Exam Guide
Tableau is currently one of the most popular and fastest-growing business intelligence and visual analytics platforms in the industry. Hence, It helps users explore and analyze data to share meaningful insights that change the way businesses operate. It is evolving intuition-driven decisions to data-driven business decisions. Without any coding requirements,…
A Beginner’s Guide to Data Analysis Using Excel
Excel has been around since the early 1990s way before sophisticated Business Intelligence tools like Power BI and Tableau. So, people trust Excel, are familiar with it, and can start with their analyses without spending time learning a new tool.
