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 81

Data Science Data Analytics Prescriptive Analytics Analytics 81

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 131

Data Architecture Data Warehouse Statistics Visualization 131

BizAcuity

OCTOBER 21, 2019

Text analytics helps to draw the insights from the unstructured data. . Text mining is also referred to as text analytics, is the process of deriving high -quality information from text. High-quality information is typically derived through the devising of patterns and trends through statistical pattern learning.

Analytics 73

Analytics Unstructured Data Data mining Structured Data 73

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 57

Machine Learning Data Science Statistics Deep Learning 57

BizAcuity

OCTOBER 21, 2019

Text analytics helps to draw the insights from the unstructured data. Text mining is also referred to as text analytics, is the process of deriving high -quality information from text. High-quality information is typically derived through the devising of patterns and trends through statistical pattern learning.

Analytics 40

Analytics Unstructured Data Data mining Structured Data 40

Rita Sallam

JULY 22, 2016

Summary of Differences Between Traditional and Modern Business Intelligence Platforms by Analytic Workflow Component. Q2: Would you consider Sisense better than others in handling big and unstructured data? Q4: Are we going to discuss Predictive types of Analytics in this discussion?

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Grooper

AUGUST 19, 2019

Master data management. Data governance. Structured, semi-structured, and unstructured data. Data pipelines. Business Analytics. Business analytics is a focus on practical requirements needed for understanding current performance and for predicting future outcomes. Data science skills.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54