Data analysis

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Map view:

Zoom: 100%

More settings

Connection length 100% Label size 100% Node size 100% Line width 100% Label width 100%

Export map as:

Data analysis topic overview

The analysis highlights Applications, Science and Products as prominent areas in the source structure around Data analysis.

Related topics: 109
Source areas: 8
Connected nodes: 123
Extracted relationships: 45
Related term clusters: 42
Bridge connections: 123

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Overview · 37 topics

Data analysis process · 24 topics

Analyzing quantitative data in finance · 13 topics

Free software for data analysis · 13 topics

Barriers to effective analysis · 8 topics

Quantitative messages · 6 topics

Data analysis contests · 5 topics

Other applications · 3 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Start with your topic. Discover where to go next.

Explore different angles and find fresh ideas to shape your next piece of content.

Data analysis

6Data cleansing · Data transformation · Data modeling

5Dataset · Data custodian · Information systems technician

9Data mining · Business intelligence · Descriptive statistics

6Mathematical formula · Mathematical model · Algorithms

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Quantitative messages

Analyzing quantitative data in finance

Barriers to effective analysis

Other applications

Free software for data analysis

Data analysis contests

Bibliography

For the semantics nerds

You can skip this section if you’re here for content ideas and keyword inspiration.

Advanced semantic analysis

How Data analysis connects Entity context

The extracted context around Data analysis shows recurring relationship patterns in the source. For example, Data analysis → CERN, Data, DevInfo, ELKI, FORTRAN/C, Free, Java, Julia, KNIME, Orange, Pandas, PAW, Python, ROOT, SciPy, The Konstanz Information Miner, United Nations Development Group Another extracted example is Data analysis → ASCE, Different, FHWA, Google, Kaggle, LTPP. Use these groups to spot repeated connection types before inspecting the individual relationships.

Top relations

related to Free software for data analysis · 17

Data analysis → CERN, Data, DevInfo, ELKI, FORTRAN/C, Free, Java, Julia, KNIME, Orange, Pandas, PAW, Python, ROOT, SciPy, The Konstanz Information Miner, United Nations Development Group

related to Data analysis contests · 6

Data analysis → ASCE, Different, FHWA, Google, Kaggle, LTPP

related to Barriers to effective analysis · 2

Data analysis → Barriers, Distinguishing

related to Data analysis process · 2

Data analysis → Data, Statistician John Tukey

related to Data processing · 2

Data analysis → Data, Excel

related to Exploratory data analysis · 2

Data analysis → Data, Descriptive

related to Reproducible analysis · 2

Data analysis → Additionally, Often

is a · 1

Data analysis → process of inspecting

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

data analysis may used information one also business exploratory variables techniques statistical analytics main isbn quality initial statistics results analysts

Data analysis relationships Subject–Predicate–Object triples

TTTA extracted 45 structured relationships around Data analysis. Examples in this analysis include Data analysis → is a → process of inspecting and business analytics → instance of → It is widely used in fields. The table shows each extracted connection, where it came from and its confidence.

Subject	Predicate	Object	Confidence	Src
Data analysis	is a	process of inspecting	0.90	text
business analytics	instance of	It is widely used in fields	0.80	text
healthcare	instance of	It is widely used in fields	0.80	text
and artificial intelligence to extract meaningful insights from data.Data mining is a particular data analysis technique that focuses on statistical modeling	instance of	It is widely used in fields	0.80	text
knowledge discovery for predictive rather than purely descriptive purposes	instance of	It is widely used in fields	0.80	text
while business intelligence covers data analysis that relies heavily on aggregation	instance of	It is widely used in fields	0.80	text
focusing mainly on business information	instance of	It is widely used in fields	0.80	text
Flink	instance of	decision-making and implementation.Frameworks	0.80	text
Spark	instance of	decision-making and implementation.Frameworks	0.80	text
Apache Hadoop	instance of	decision-making and implementation.Frameworks	0.80	text
RapidMiner	instance of	decision-making and implementation.Frameworks	0.80	text
and Storm can be helpful for data analysis	instance of	decision-making and implementation.Frameworks	0.80	text

Related concept clusters Related term clusters

The concept neighborhoods around Data analysis bring nearby vocabulary together. In this analysis, examples include Data, May and Used. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

Data analysis
- Data
- May
- Used
- Initial
- Confirmatory
- Also
- Analytics
- Business
- Quality
- Information
- Techniques
- Important
data analysis
- Data
- Exploratory
- May
- Initial
- Used
- Phase
- Main
- Confirmatory
- Quality
- Also
- Analytics
- Business
data
- May
- Used
- Initial
- Also
- Analytics
- Business
- Quality
- Information
- Techniques
- Main
- Process
- Phase
business analytics
- Intelligence
- Analytics
- Business
- Models
- Quantitative
- Research
- Used
- Initial
- Statistical
- Exploratory
- Information
- Data
data mining
- May
- Used
- Initial
- Also
- Analytics
- Business
- Quality
- Information
- Techniques
- Main
- Process
- Phase
exploratory data analysis
- Data
- Confirmatory
- Initial
- Exploratory
- May
- Used
- Phase
- Intelligence
- Process
- Main
- Research
- Results
confirmatory data analysis
- Data
- Exploratory
- May
- Initial
- Used
- Phase
- Results
- Main
- Also
- Confirmatory
- Quality
- Analytics
unstructured data
- May
- Used
- Initial
- Also
- Analytics
- Business
- Quality
- Information
- Techniques
- Main
- Process
- Phase

Connections between topic areas Semantic bridges

For Data analysis, one of the stronger structural bridges in this analysis connects Data analysis with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3

Data analysis — Overview · splits 86 ⟂ 38

Data analysis — Data analysis process · splits 99 ⟂ 25

Data analysis — Analyzing quantitative data in finance · splits 110 ⟂ 14

Data analysis — Free software for data analysis · splits 110 ⟂ 14

Data analysis — Barriers to effective analysis · splits 115 ⟂ 9

Data analysis — Quantitative messages · splits 117 ⟂ 7

Data analysis — Data analysis contests · splits 118 ⟂ 6

Data analysis — Bibliography · splits 118 ⟂ 6

Data analysis — Other applications · splits 120 ⟂ 4

Map overview Semantic statistics

Data analysis

Nodes124

Edges123

Triples45

Avg. degree1.98

Density0.016129

Components1

Source & methodology

TTTA analyzes the structure around Data analysis to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Applications, Science & Products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Data analysis · EN edition · Analysis: TopicsToTalkAbout

Data analysis: Applications, Science & Products

Data analysis topic overview

What this topic covers Research coverage

Key facts & relationships

Start with your topic. Discover where to go next.

Questions to explore

Explore all related topics Closing gaps

Overview

Data analysis process

Quantitative messages

Analyzing quantitative data in finance

Barriers to effective analysis

Other applications

Free software for data analysis

Data analysis contests

Bibliography

For the semantics nerds

Advanced semantic analysis

How Data analysis connects Entity context

Data analysis

Top relations

Important terminology

Important terminology

Data analysis relationships Subject–Predicate–Object triples

Related concept clusters Related term clusters

Connections between topic areas Semantic bridges

Map overview Semantic statistics

Data analysis

Source & methodology