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What is Big Data Analytics
1.
It is a process to analyze
big data
to uncover hidden, valid, and useful patterns and insights.
Learn more in: Education in the Era of Industry 4.0: Qualifications, Challenges, and Opportunities
2.
The process, techniques, and tools used to gain insights from
Big Data
so that the decision making process could be optimized.
Learn more in: Big Data Analytics for Business
3.
Big data analytics
is the process of extracting useful patterns and correlations from huge
data
coming from various sources and in various formats.
Learn more in: Insight Into Big Data Analytics: Challenges, Recent Trends, and Future Prospects
4.
The application of methods and algorithms in sets of
big data
in order to gain insights.
Learn more in: Using Big Data in Healthcare
5.
Big data analytics
is the use of advanced analytic techniques against these huge
data
sets.
Big data analytics
enables to uncover hidden patterns, correlations and other insights from huge
data
sets.
Learn more in: Big Data in Business: Digital Transformation for Enhanced Decision-making and Superior Customer Experience
6.
It is the process of inspecting huge amount of varied
data
to uncover hidden patterns, unknown correlations and to extract valuable information using advanced analytic techniques and business intelligence tools.
Learn more in: Big Data Computing and the Reference Architecture
7.
Big Data Analytics
is the process of inspecting, cleaning, transforming, and modeling
Big Data
to discover and communicate useful information and patterns, suggest conclusions and support decision making ( Cao, M. et al., 2015 ).
Learn more in: Big Data Analytics and Visualization of Performance of Stock Exchange Companies Based on Balanced Scorecard Indicators
8.
Big data analytics
is the difficult process of analyzing large amounts of
data
in order to reveal information such as hidden patterns, correlations, market trends, and customer preferences which can help businesses make more informed decisions.
Learn more in: Big Data Analytics for Search Engine Optimization in Intelligent Business
9.
A process of extracting useful information and pattern from
big data
.
Learn more in: AI-Driven Big Healthcare Analytics: Contributions and Challenges
10.
Big data analytics
is the use of advanced techniques to analyze, process and examine
big data
to uncover hidden patterns, trends and relations in order to assist management decision making.
Learn more in: Enhancing Online Repurchase Intention via Application of Big Data Analytics in E-Commerce
11.
Analytics
is the discovery, interpretation, and visualization of meaningful patterns in
big data
. In order to do this,
analytics
use
data
classification and clustering mechanisms.
Learn more in: A Big Data Framework for Decision Making in Supply Chain
12.
The process of examining large volume of
data
of a variety of types to discover useful information.
Learn more in: Big Data Analytics: Trends and Case Studies
13.
Use of advanced analytic techniques against very voluminous, high velocity and diverse
data
sets that include structured, semi-structured and unstructured
data
, from different sources, and with varied sizes.
Learn more in: Study of E-Commerce Customer Review Capturing Process in the Indian Context
14.
It is the process of analyzing
big data
to uncover the hidden patterns and facts for competitive advantage using
Data
Mining and Business Intelligence tools and techniques.
Learn more in: Taxonomy Outline of Big Data Analytics Literature
15.
The mathematical and software techniques for examining large and varied
data
sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.
Learn more in: Avatar-Based Management Techniques for Breaking Down Language and Cultural Barriers in Modern Russian Corporations
16.
Big data
in
analytics
comprises of tools and techniques to get insight into the huge amount of
data
available for useful information.
Learn more in: Big Data and Analytics: Application to Healthcare Industry
17.
Process of examining large
data
sets containing a variety of
data
types for specific patterns, correlations, market trends, customer preferences and other relevant information.
Learn more in: Modeling Big Data Analytics with a Real-Time Executable Specification Language
18.
Analytics
is the discovery, interpretation, and visualization of meaningful patterns in
big data
. To do this,
analytics
use
data
classification and clustering mechanisms.
Learn more in: Quality Assurance Issues for Big Data Applications in Supply Chain Management
19.
Big data
/
analytics
is defined as the capability of processing extremely large
data
sets to identify patterns of relationships (correlation, causality) among
data
to be used in detecting market trends, consumer behaviour and preferences.
Learn more in: Role of Data Science and Data Analytics in Forensic Accounting and Fraud Detection
20.
Big data analytics
is the often composite process of examining large and wide-ranging
data
sets, or
big data
, to come across information—such as concealed patterns, indefinite correlations, market development and client preferences—that can help organizations create informed business decisions.
Learn more in: Big Data Analytics and IoT in Smart City Applications
21.
The mathematical and software techniques for examining large and varied
data
sets to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more-informed business decisions.
Learn more in: “Smart City”: The Concept of Resolving the Contradiction Between Production and Urban Life
22.
The platform to process and analyze scalable, fast-streaming, and multi-formatted
data
using MapReduce techniques and related technologies such as Hadoop and Spark and their associated eco systems.
Learn more in: Leveraging Applications of Data Mining in Healthcare Using Big Data Analytics: An Overview
23.
All the
data
processing and analysis techniques to examine large amounts of
data
in order to provide insights by uncovering hidden
data
structures (correlations, patterns) and to inform business decisions and public policies.
Learn more in: Food Loss and Waste: A Sustainable Supply Chain Perspective
24.
The process of examining very large and diverse of
data
which can be used of advanced analytic techniques in an effort to uncover hidden patterns, unknown correlations and other useful information.
Learn more in: The Effectiveness of Big Data in Social Networks
25.
Big data analytics
is a science and technology about organizing
big data
, analyzing and discovering knowledge, patterns, and intelligence from
big data
, visualizing and reporting the discovered knowledge for assisting decision making (Sun, Sun, & Strang, 2016). The main components of
big analytics
include
big data
descriptive
analytics
, predictive
analytics
, and prescriptive
analytics
(Sun, Sun, & Strang, 2018), which correspondingly address the three questions of
big data
: when and what occurred? what will occur? and what is the best answer or choice under uncertainty? All these questions are often encountered in almost every part of science, technology, business, management, organization, and industry.
Learn more in: Applying Intelligent Big Data Analytics in a Smart Airport Business: Value, Adoption, and Challenges
26.
Big data analytics
is the often-complex process of analyzing voluminous amount of structured, semi structured and unstructured
data
that has the potential to be mined for information.
Learn more in: Digital Transformation: Impact of 5G Technology in Supply Chain Industry
27.
This refers to analysis of
data
clusters to gain business intelligence and determine logic and trends that exist in the
data
.
Learn more in: Blockchain Technology in the Automotive Industry: Use Cases and Statistical Evaluation
28.
This refers to the capability to read and analyze volume of different
data
sets.
Learn more in: Business Intelligence: Strengths, Weaknesses, and Opportunities
29.
Is the mathematical and software techniques for examining large and varied
data
sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.
Learn more in: Avatar-Based and Automated Testing System for Quality Control of Student Training: Using Neuron Natural and Artificial Technology Platform Triple H
30.
The process, techniques, and tools used to gain insights from
Big Data
so that the decision making process could be optimized.
Learn more in: Integrated Data Architecture for Business
31.
Is the often complicated process of examining large and varied
data
sets, or
big data
, to uncover information—such as hidden patterns, unknown correlations, market trends, and customer preferences—that can help organizations make informed business decisions.
Learn more in: Integration of Data Mining and Business Intelligence in Big Data Analytics: A Research Agenda on Scholarly Publications
32.
Big data analytics
is the process of analyzing
big
, complex and variable
data
.
Learn more in: Management of Big Data Projects: PMI Approach for Success
33.
The process, techniques, and tools used to gain insights from
Big Data
so that the decision making process could be optimized.
Learn more in: Integrated Data Architecture for Business
34.
Techniques, technologies, systems, methodologies, tools, and applications used to analysis for decision making.
Learn more in: Big Data Adoption: A Comparative Study of the Indian Manufacturing and Services Sectors
35.
Extracting meaningful information from huge amount of
data
that is collected from various sources and types.
Learn more in: How Supply Chain Management Will Change in the Industry 4.0 Era?
36.
The process of examining
Big Data
to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.
Learn more in: Internet of Things and Big Data-Driven Data Analysis Services for Third Parties: Business Models, New Ventures, and Potential Horizons
37.
Big data analytics
describes the challenge of filtering out the relevant information from a huge deal of
data
with the right strategy.
Learn more in: Big Data Analytics and the Discovery of the Hidden Data Treasure From Savings Banks in Germany
38.
The process of examining
big data
to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.
Learn more in: Evaluation of Strategic Opportunities and Resulting Business Models for SMEs: Employing IoT in Their Data-Driven Ecosystems
39.
Examines large amounts of
data
to uncover hidden patterns, correlations and other insights.
Learn more in: Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0
40.
Is the mathematical and software techniques for examining large and varied
data
sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.
Learn more in: Avatar-Based Control and Development of Neuron Multi-Functional Platforms for Transformation Processes in the Digital Economy
41.
Can be defined basically using
analytics
techniques on
big data
to explore worthful information. The analyzing of
big data
is pretty important for both prediction of future and decision making in all working areas.
Learn more in: Intelligent Big Data Analytics in Health
42.
An approach to the analysis of large volumes of high velocity, complex and variable
data
from a multitude of sources that require advanced techniques and technologies.
Learn more in: Social Media Analytics: Opportunities and Challenges for Cultural Tourism Destinations
43.
Big Data Analytics
is the process of examining large amounts of
data
of a variety of types (
big data
) to uncover hidden patterns, unknown correlations and other useful information using advanced analytic techniques.
Learn more in: Big Data Analytics Demystified
Find more terms and definitions using our
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.
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