Smart Data Collective

NOVEMBER 18, 2020

You may not even know exactly which path you should pursue, since some seemingly similar fields in the data technology sector have surprising differences. We decided to cover some of the most important differences between Data Mining vs Data Science in order to finally understand which is which. What is Data Science?

Data Mining 358

Data Mining Big Data Artificial Intelligence Data Warehouse 358

Astera

MAY 30, 2024

Data analytics has several components: Data Aggregation : Collecting data from various sources. Data Mining : Sifting through data to find relevant information. Statistical Analysis : Using statistics to interpret data and identify trends. What are the 4 Types of Data Analytics?

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Smart Data Collective

JUNE 4, 2021

Since the field covers such a vast array of services, data scientists can find a ton of great opportunities in their field. Data scientists use algorithms for creating data models. These data models predict outcomes of new data. Data science is one of the highest-paid jobs of the 21st century.

E-Commerce 263

E-Commerce Cloud Computing Big Data Data Modelling 263

BizAcuity

MARCH 31, 2022

AI can be applies to all 3 major types of analytics: Descriptive Analytics: The entire journey of the descriptive and diagnostic analytics process includes data extraction, data aggregation and data mining; 3 applications where AI is widely used to reduce costs, and eliminate complex actions.

Artificial Intelligence 130

Artificial Intelligence Data Analytics Data Analytics Predictive Analytics 130

Data Pine

MARCH 31, 2022

To simplify things, you can think of back-end BI skills as more technical in nature and related to building BI platforms, like online data visualization tools. Front-end analytical and business intelligence skills are geared more towards presenting and communicating data to others. b) If You’re Already In The Workforce.

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95

Marutitech

JANUARY 21, 2022

Companies worldwide follow various approaches to deal with the process of data mining. . This method is generally known as the CRISP-DM, abbreviated as Cross-Industry Standard Process for Data Mining. . Data Understanding. Modeling data . The CRISP-DM methodology is as follows: Business Understanding.

Project Management 113

Project Management Data Mining Data Analytics Data Analytics 113

Data Pine

MARCH 25, 2022

Predictive analytics : This method uses advanced statistical techniques coming from data mining and machine learning technologies to analyze current and historical data and generate accurate predictions. BI dashboards , offer the possibility to filter the data all in one screen to extract deeper conclusions.

Business Intelligence 105

Business Intelligence Business Intelligence E-Commerce Predictive Analytics 105