Data Science Dojo

JANUARY 22, 2023

Descriptive statistics Grouping and aggregating: One way to explore a dataset is by grouping the data by one or more variables, and then aggregating the data by calculating summary statistics. This can be useful for identifying patterns and trends in the data.

Exploratory Data Analysis 370

Exploratory Data Analysis EDA Data Analysis Data Analysis 370

Smart Data Collective

OCTOBER 17, 2022

The final point to which the data has to be eventually transferred is a destination. The destination is decided by the use case of the data pipeline. It can be used to run analytical tools and power data visualization as well. Otherwise, it can also be moved to a storage centre like a data warehouse or lake.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Data Lakes 145

phData

NOVEMBER 4, 2024

By providing a single, unified platform for data storage, management, and analysis, Snowflake connects organizations to leading software vendors specializing in analytics, machine learning, data visualization, and more.

Machine Learning 69

Machine Learning Machine Learning Data Science ML 69

Analytics Vidhya

OCTOBER 10, 2022

This article was published as a part of the Data Science Blogathon. Introduction to Data Storytelling Storytelling is a beautiful legacy that is a part of our great Indian culture, from the legendary Mahabharata era to Puranas and Jataka fables. The post The Understated Art of Data Storytelling appeared first on Analytics Vidhya.

Data Science 336

Data Science Analytics Analytics Clean Data 336

How to Learn Machine Learning

APRIL 26, 2025

Data scientists try multiple models, evaluate their performance, and fine-tune some parameters to get better accuracy. Data Visualization and Interpretation To make the data understandable to stakeholders, visualizations are created in the form of charts, graphs, and dashboards.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Analytics Vidhya

SEPTEMBER 21, 2021

This article was published as a part of the Data Science Blogathon Introduction You must be aware of the fact that Feature Engineering is the heart of any Machine Learning model. How successful a model is or how accurately it predicts that depends on the application of various feature engineering techniques. In this article, we are […].

Machine Learning 343

Machine Learning Machine Learning Data Science Analytics 343

Analytics Vidhya

MAY 12, 2019

Introduction Data scientists spend close to 70% (if not more) of their time cleaning, massaging and preparing data. The post A Beginner’s Guide to Tidyverse – The Most Powerful Collection of R Packages for Data Science appeared first on Analytics Vidhya. That’s no secret – multiple surveys.

Data Science 307

Data Science Data Scientist Analytics Analytics 307

Analytics Vidhya

JANUARY 27, 2023

Introduction Effective data management is crucial for organizations of all sizes and in all industries because it helps ensure the accuracy, security, and accessibility of data, which is essential for making good decisions and operating efficiently.

AI 329

AI AI Analytics Analytics 329

Analytics Vidhya

JUNE 21, 2023

Introduction Stress is a natural response of the body and mind to a demanding or challenging situation. It is the body’s way of reacting to external pressures or internal thoughts and feelings.

Machine Learning 328

Machine Learning Machine Learning Analytics Analytics 328

Dataconomy

MAY 16, 2023

They employ statistical and mathematical techniques to uncover patterns, trends, and relationships within the data. Data scientists possess a deep understanding of statistical modeling, data visualization, and exploratory data analysis to derive actionable insights and drive business decisions.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Analytics Vidhya

OCTOBER 26, 2023

Introduction Python is a versatile and powerful programming language that plays a central role in the toolkit of data scientists and analysts. Its simplicity and readability make it a preferred choice for working with data, from the most fundamental tasks to cutting-edge artificial intelligence and machine learning.

Data Scientist 319

Data Scientist Python Artificial Intelligence Artificial Intelligence 319

Towards AI

OCTOBER 18, 2023

In-depth data analysis using GPT-4’s data visualization toolset. dallE-2: painting in impressionist style with thick oil colors of a map of Europe Efficiency is everything for coders and data analysts. With GPT-4’s Advanced Data Analysis (ADA) toolset, this process becomes significantly more streamlined.

Data Analysis 52

Data Analysis Data Analysis Data Visualization Data Analyst 52

Analytics Vidhya

APRIL 17, 2023

Are you a data enthusiast looking to break into the world of analytics? The field of data science and analytics is booming, with exciting career opportunities for those with the right skills and expertise. So, let’s […] The post Data Scientist vs Data Analyst: Which is a Better Career Option to Pursue in 2023?

Data Analyst 306

Data Analyst Data Scientist Data Science Analytics 306

Analytics Vidhya

JUNE 22, 2023

Let’s dive into the fascinating world of H1B visa data from the Office of Foreign Labor Certification […] The post Is H1B Visa Approved Based On The Insights Of Data Analysis? Introduction The H1B visa program opens doors for skilled individuals worldwide to bring their expertise to the United States.

Data Analysis 290

Data Analysis Data Analysis Analytics Analytics 290

Dataconomy

AUGUST 16, 2023

Imagine data scientists as modern-day detectives who sift through a sea of information to uncover hidden patterns, trends, and correlations that can inform decision-making and drive innovation. At the heart of the matter lies the query, “What does a data scientist do?” Work Works with larger, more complex data sets.

Data Scientist 172

Data Scientist Data Science Machine Learning Machine Learning 172

Tableau

OCTOBER 8, 2021

“This partnership makes data more accessible and trusted. With Looker’s secure, trusted and highly performant data governance capabilities, we can augment Tableau’s world-class data visualization capabilities to enable data-driven decisions across the enterprise. Operationalizing Tableau Prep flows to BigQuery.

Tableau 138

Tableau Analytics Analytics Machine Learning 138

Tableau

OCTOBER 8, 2021

“This partnership makes data more accessible and trusted. With Looker’s secure, trusted and highly performant data governance capabilities, we can augment Tableau’s world-class data visualization capabilities to enable data-driven decisions across the enterprise. Operationalizing Tableau Prep flows to BigQuery.

Tableau 98

Tableau Analytics Analytics Machine Learning 98

Pickl AI

NOVEMBER 2, 2023

Here, we’ll explore why Data Science is indispensable in today’s world. Understanding Data Science At its core, Data Science is all about transforming raw data into actionable information. It includes data collection, data cleaning, data analysis, and interpretation.

Data Scientist 52

Data Scientist Data Science Data Visualization Machine Learning 52

Pickl AI

SEPTEMBER 25, 2023

It has a dedicated community and numerous packages like ggplot2 for Data Visualization. Understanding Data Visualization Data visualization is a critical aspect of Data Science.

Data Science 52

Data Science Data Analysis Data Analysis Data Visualization 52

Tableau

JANUARY 27, 2021

We also reached some incredible milestones with Tableau Prep, our easy-to-use, visual, self-service data prep product. In 2020, we added the ability to write to external databases so you can use clean data anywhere. Tableau Prep can now be used across more use cases and directly in the browser.

Tableau 102

Tableau Business Intelligence Business Intelligence Analytics 102

Flipboard

FEBRUARY 2, 2023

Her research interest includes model interpretability, causal analysis, human-in-the-loop AI and interactive data visualization. He has collaborated with the Amazon Machine Learning Solutions Lab in providing clean data for them to work with as well as providing domain knowledge about the data itself.

Cross Validation 123

Cross Validation ML ML Machine Learning 123

Pickl AI

AUGUST 15, 2023

Data Analyst Without Coding While coding skills are highly beneficial for Data Analysts, some entry-level positions may not require extensive programming knowledge. Companies often hire Data Analysts for roles that focus primarily on data visualization, reporting, and using pre-built tools and dashboards.

Analytics 52

Analytics Analytics Data Analyst Data Analysis 52

Mlearning.ai

FEBRUARY 21, 2023

Pandas is a powerful data manipulation library in Python, which we'll be using to load, transform and analyze the data. We'll also use numpy and matplotlib libraries for numerical computations and data visualization. data = data.dropna() We can also use the drop_duplicates() method to remove duplicated rows.

Data Wrangling 52

Data Wrangling Python Data Analysis Data Analysis 52

Pickl AI

DECEMBER 3, 2024

Raw data often contains inconsistencies, missing values, and irrelevant features that can adversely affect the performance of Machine Learning models. Proper preprocessing helps in: Improving Model Accuracy: Clean data leads to better predictions. Matplotlib/Seaborn: For data visualization.

Python 52

Python ML ML Exploratory Data Analysis 52

Pickl AI

JULY 12, 2023

Moreover, this feature helps integrate data sets to gain a more comprehensive view or perform complex analyses. Data Cleaning Data manipulation provides tools to clean and preprocess data. Thus, Cleaning data ensures data quality and enhances the accuracy of analyses.

Data Analysis 52

Data Analysis Data Analysis Database Clean Data 52

Pickl AI

MARCH 12, 2023

Accordingly, Data Analysts use various tools for Data Analysis and Excel is one of the most common. Significantly, the use of Excel in Data Analysis is beneficial in keeping records of data over time and enabling data visualization effectively. How to use Excel in Data Analysis and why is it important?

Data Analysis 52

Data Analysis Data Analysis Data Analyst Power BI 52

Flipboard

MARCH 22, 2023

Data Wrangler simplifies the data preparation and feature engineering process, reducing the time it takes from weeks to minutes by providing a single visual interface for data scientists to select and clean data, create features, and automate data preparation in ML workflows without writing any code.

AWS 123

AWS Data Preparation Azure Data Scientist 123

Pickl AI

MAY 30, 2024

Overview of Typical Tasks and Responsibilities in Data Science As a Data Scientist, your daily tasks and responsibilities will encompass many activities. You will collect and clean data from multiple sources, ensuring it is suitable for analysis. Data Cleaning Data cleaning is crucial for data integrity.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

AUGUST 28, 2023

Key Features of Power BI: Power BI is a powerful business intelligence tool developed by Microsoft that enables users to visualize and analyze data from various sources. It offers a wide range of features that make it a popular choice for data professionals, analysts, and organizations.

Power BI 52

Power BI Data Analysis Data Analysis Data Visualization 52

Mlearning.ai

JANUARY 26, 2023

Presenters and participants had the opportunity to hear about and evaluate the pros and cons of different back end technologies and data formats for different uses such as web-mapping, data visualization, and the sharing of meta-data. These can be cleaned to remove artifacts and/or outdated elements.

AWS 98

AWS Database Data Science Clean Data 98

Dataconomy

JULY 28, 2023

Data scientists must decide on appropriate strategies to handle missing values, such as imputation with mean or median values or removing instances with missing data. The choice of approach depends on the impact of missing data on the overall dataset and the specific analysis or model being used.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Mlearning.ai

APRIL 25, 2023

Let’s explore the dataset further by cleaning data and creating some visualizations. The type column tells us if it is a TV show or a movie. df.isnull().sum() sum() #checking for null values.

Data Analysis 52

Data Analysis Data Analysis Python Exploratory Data Analysis 52

Pickl AI

JULY 20, 2023

Descriptive Analytics Projects: These projects focus on summarizing historical data to gain insights into past trends and patterns. Examples include generating reports, dashboards, and data visualizations to understand business performance, customer behavior, or operational efficiency.

Analytics 40

Analytics Analytics Big Data Big Data 40

Pickl AI

JANUARY 17, 2023

In a business environment, a Data Scientist is involved to work with multiple teams laying out the foundation for analysing data. This implies that as a Data Scientist, you would engage in collecting, analysing and cleaning data gathered from multiple sources.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 14, 2023

So, let me present to you an Importing Data in Python Cheat Sheet which will make your life easier. For initiating any data science project, first, you need to analyze the data. Alongside Matplotlib, a key tool for data visualization, and NumPy, the foundational library for scientific computing upon which Pandas was constructed.

Python 52

Python SQL Database Data Analysis 52

Mlearning.ai

JULY 9, 2023

Goal The objective of this post is to demonstrate how Polars performance is much better than other open-source libraries in a variety of data analysis tasks, such as data cleaning, data wrangling, and data visualization. ?

Data Analysis 52

Data Analysis Data Analysis Python Data Scientist 52

learn data science

DECEMBER 30, 2020

Text Data Wrangling UI When cleaning data, the text data is the most notorious. We introduced the Text Data Wrangling UI with v5.5 to make the following text data wrangling operations easier. text inside of brackets) First Word / Last Word Here is an example of extracting URLs from the tweet data.

Data Wrangling 52

Data Wrangling Hypothesis Testing Analytics Analytics 52