Pickl AI

OCTOBER 14, 2024

Summary: This article explores different types of Data Analysis, including descriptive, exploratory, inferential, predictive, diagnostic, and prescriptive analysis. Introduction Data Analysis transforms raw data into valuable insights that drive informed decisions. What is Data Analysis?

Data Analysis 52

Data Analysis Data Analysis EDA Data Mining 52

Pickl AI

NOVEMBER 4, 2024

This article will guide you through effective strategies to learn Python for Data Science, covering essential resources, libraries, and practical applications to kickstart your journey in this thriving field. Key Takeaways Python’s simplicity makes it ideal for Data Analysis. in 2022, according to the PYPL Index.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Dataconomy

APRIL 27, 2023

What is an online transaction processing database: Indexed data sets are used for rapid querying in OLTP systems Regular & incremental backups for data safety Frequent backups are necessary to ensure that data is protected in the event of a system failure or other issue.

Database 159

Database Data Scientist Data Mining Data Mining 159

Smart Data Collective

MARCH 23, 2020

Online shopping, gaming, web surfing – all of this data can be collected, and more importantly, analyzed. Most businesses prefer to rely on the insights gained from the big data analysis. Active game users generate hundreds of terabytes of data every day.

Big Data 131

Big Data Big Data Data Mining Data Mining 131

Smart Data Collective

JUNE 4, 2021

Here are the chronological steps for the data science journey. First of all, it is important to understand what data science is and is not. Data science should not be used synonymously with data mining. Mathematics, statistics, and programming are pillars of data science. Exploratory Data Analysis.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

Cambridge Intelligence

JANUARY 30, 2024

While it has always been a data-intensive process, enterprise fraud management today is more complex and more important than ever. This blog post explores the evolving role of enterprise fraud management, examines the impact of AI and showcases the importance of visual data analysis. What is enterprise fraud management?

Data Visualization 105

Data Visualization AI AI Analytics 105

Dataconomy

MARCH 24, 2023

BI involves using data mining, reporting, and querying techniques to identify key business metrics and KPIs that can help companies make informed decisions. A career path in BI can be a lucrative and rewarding choice for those with interest in data analysis and problem-solving. What is business intelligence?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Dataconomy

MARCH 24, 2023

BI involves using data mining, reporting, and querying techniques to identify key business metrics and KPIs that can help companies make informed decisions. A career path in BI can be a lucrative and rewarding choice for those with interest in data analysis and problem-solving. What is business intelligence?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

ODSC - Open Data Science

FEBRUARY 10, 2023

How to Use Data Mining in Cybersecurity Since every organization must prioritize cybersecurity, data mining is applicable across all industries. But what role does data mining play in cybersecurity? Jordan of UC Berkeley about learning-aware mechanism design and machine learning. Here’s a quick recap.

Azure 52

Azure ML ML Data Mining 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Towards AI

MARCH 17, 2023

Random variable: Statistics and data mining are concerned with data. How do we link sample spaces and events to data? That choice will be random [Even though there are methods to choose k sample but still this is random]. and those chosen people will be sampled from all student's sample space.

Hypothesis Testing 98

Hypothesis Testing Data Mining Data Mining Data Mining 98

Pickl AI

JUNE 25, 2023

The latter is the practice of using statistical techniques, data mining, predictive modelling, and Machine Learning algorithms to analyze past and present data. Descriptive Analytics Descriptive analytics focuses on summarizing historical data to gain a better understanding of past events and trends.

Analytics 52

Analytics Analytics Predictive Analytics Machine Learning 52

Pickl AI

OCTOBER 3, 2024

Predictive analytics refers to the use of statistical algorithms and Machine Learning techniques to analyse historical data and predict future events or outcomes. It involves various processes, including data mining, predictive modelling, and statistical analysis. How Does Analytics Benefit Businesses?

Predictive Analytics 52

Predictive Analytics Analytics Analytics Machine Learning 52

ODSC - Open Data Science

APRIL 24, 2024

How can energy-saving opportunities reveal themselves without data curation, oversight, and management? Lack of Predictive Maintenance The predictive potential of data analytics leads to lean maintenance behaviors. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

Analytics 52

Analytics Analytics Data Scientist Data Science 52

ODSC - Open Data Science

MARCH 11, 2024

You will also get invaluable insights by networking and connecting with hundreds of data science attendees, world-renowned instructors, industry experts, and dozens of top companies seeking the next wave of talent. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

Data Science 52

Data Science Deep Learning Deep Learning Machine Learning 52

Pickl AI

MARCH 3, 2023

There are other types of Statistical Analysis as well which includes the following: Predictive Analysis: Significantly, it is the type of Analysis useful for forecasting future events based on present and past data. Moreover, it helps make informed decisions and encourages efficient decision-making processes.

Exploratory Data Analysis 40

Exploratory Data Analysis Hypothesis Testing Data Analyst Data Scientist 40

Pickl AI

OCTOBER 15, 2024

Diagnostic Analytics Diagnostic analytics goes a step further by explaining why certain events occurred. It uses data mining , correlations, and statistical analyses to investigate the causes behind past outcomes. It analyses patterns to predict trends, customer behaviours, and potential outcomes.

Analytics 52

Analytics Analytics Predictive Analytics Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Heartbeat

MARCH 8, 2023

R is a popular open-source programming language used for statistical computation and data analysis, as well as for text classification tasks such as basic spam detection, sentiment analysis, and topic labeling. Data mining, text classification, and information retrieval are just a few applications.

Machine Learning 52

Machine Learning Machine Learning Algorithm Data Mining 52

Pickl AI

AUGUST 21, 2024

Content Aggregation News websites or blogs may scrape content from multiple sources to provide a comprehensive overview of current events or topics. Scraping: Once the URLs are indexed, a web scraper extracts specific data fields from the relevant pages. This targeted extraction focuses on the information needed for analysis.

Apache Hadoop 52

Apache Hadoop Hadoop Database Data Quality 52

Pickl AI

MAY 10, 2023

Being an important component of Data Science, the use of statistical methods are crucial in training algorithms in order to make classification. Certainly, these predictions and classification help in uncovering valuable insights in data mining projects.

Clustering 52

Clustering Decision Trees Machine Learning Machine Learning 52

Data Science Dojo

JANUARY 13, 2023

Attendees also have the opportunity to meet with leading vendors and solutions providers in the data and analytics space, and network with peers in the industry. The Gartner Data and Analytics Summit is considered as a leading event for professionals in the data and analytics field. 4.

Data Science 226

Data Science Data Mining Data Mining Data Mining 226

Mlearning.ai

MAY 23, 2023

Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Data processing does the task of exploring the data, mining it, and analyzing it which can be finally used to generate the summary of the insights extracted from the data.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Dataconomy

SEPTEMBER 1, 2023

Heart disease stands as one of the foremost global causes of mortality today, presenting a critical challenge in clinical data analysis. Leveraging hybrid machine learning techniques, a field highly effective at processing vast healthcare data volumes is increasingly promising in effective heart disease prediction.

Decision Trees 195

Decision Trees Machine Learning Machine Learning Support Vector Machines 195

Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Process Mining offers process transparency, compliance insights, and process optimization. Each applications has its own data model.

Data Science 246

Data Science Azure Power BI Business Intelligence 246

Dataconomy

FEBRUARY 26, 2025

Data mining has emerged as a vital tool in todays data-driven environment, enabling organizations to extract valuable insights from vast amounts of information. As businesses generate and collect more data than ever before, understanding how to uncover patterns and trends becomes essential for making informed decisions.

Data Mining 91

Data Mining Data Mining Data Mining Data Preparation 91

Heartbeat

FEBRUARY 29, 2024

Photo by Nathan Dumlao on Unsplash Introduction Web scraping automates the extraction of data from websites using programming or specialized tools. Required for tasks such as market research, data analysis, content aggregation, and competitive intelligence.

Python 52

Python Deep Learning Deep Learning Data Quality 52