Analytics Vidhya

MAY 29, 2023

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Both are associated with data usage but differ from each other.

Data mining 294

Data mining Data Collection Strategy Data Analytics 294

CIO Business Intelligence

OCTOBER 13, 2023

Data architect vs. data scientist According to Dataversity , the data architect and data scientist roles are related, but data architects focus on translating business requirements into technology requirements, defining data standards and principles, and building the model-development frameworks for data scientists to use.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

Unstructured Data 142

Unstructured Data Modeling Machine Learning Data mining 142

CIO Business Intelligence

APRIL 22, 2022

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Tableau: Now owned by Salesforce, Tableau is a data visualization tool.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

CIO Business Intelligence

JUNE 28, 2023

The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace. Working with non-typical data presents us with a reality where encountering challenges is part of our daily operations.”

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are responsible for developing, testing, and maintaining data pipelines and data architectures. Data scientists use data science to discover insights from massive amounts of structured and unstructured data to shape or meet specific business needs and goals.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131