Data Visualization and Interpretation
Expert-defined terms from the Professional Certificate in Occupational Health Data Analysis course at London School of Business and Administration. Free to read, free to share, paired with a globally recognised certification pathway.
Data Visualization and Interpretation #
Data Visualization and Interpretation
Data visualization and interpretation are crucial components of the Professional… #
This glossary provides a comprehensive list of terms related to this field to enhance understanding and application in occupational health data analysis.
1 #
Data Visualization
Data visualization refers to the graphical representation of data to communicate… #
It helps in identifying patterns, trends, and outliers in data that may not be apparent in raw text. Visualizing data can take various forms such as charts, graphs, maps, and dashboards.
Example #
A bar chart showing the number of occupational injuries by type over a period of time.
2 #
Interpretation
Interpretation involves making sense of data by analyzing patterns and trends to… #
It requires critical thinking and domain knowledge to draw accurate conclusions from data visualization.
Example #
Interpreting a line graph to understand the correlation between employee absenteeism and work shifts.
3 #
Exploratory Data Analysis (EDA)
Exploratory Data Analysis is an approach to analyze datasets to summarize their… #
It helps in understanding the distribution, outliers, and missing values in data before formal modeling.
Example #
Using histograms and scatter plots to explore the relationship between two variables in a dataset.
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Dashboard
A dashboard is a visual display of key metrics and performance indicators to mon… #
It provides a real-time snapshot of data through interactive charts and graphs.
Example #
An interactive dashboard showing the sales performance of different products by region.
5 #
Heatmap
A heatmap is a graphical representation of data where values are depicted as col… #
It is commonly used to visualize the intensity of relationships between variables in a dataset.
Example #
A heatmap showing the correlation between different risk factors for occupational diseases.
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Scatter Plot
A scatter plot is a type of mathematical diagram using Cartesian coordinates to… #
It helps in identifying relationships between variables and detecting outliers.
Example #
A scatter plot showing the relationship between employee age and years of experience in a company.
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Pie Chart
A pie chart is a circular statistical graphic divided into slices to illustrate… #
It is commonly used to show the distribution of a categorical variable in a dataset.
Example #
A pie chart representing the distribution of different job roles in an organization.
8 #
Line Chart
A line chart is a type of graph that displays information as a series of data po… #
It is useful for showing trends over time or comparing multiple variables.
Example #
A line chart showing the increase in workplace accidents over the past five years.
9 #
Bar Chart
A bar chart is a graphical representation of data using rectangular bars to show… #
It is effective in comparing values across different categories.
Example #
A bar chart illustrating the distribution of occupational hazards in different departments.
10 #
Data Mining
Data mining is the process of discovering patterns and relationships in large da… #
It helps in uncovering hidden insights for decision-making.
Example #
Using data mining to identify factors contributing to occupational injuries in a manufacturing plant.
11 #
Data Dashboard
A data dashboard is a visual tool that displays key performance indicators, metr… #
It provides a real-time overview of organizational data for monitoring and decision-making.
Example #
A data dashboard showing the daily production output and quality control metrics in a factory.
12 #
Data Analysis
Data analysis is the process of inspecting, cleansing, transforming, and modelin… #
It involves applying statistical and analytical methods to interpret data.
Example #
Conducting data analysis to determine the correlation between workplace ergonomics and employee productivity.
13 #
Data Integration
Data integration involves combining data from different sources to provide a uni… #
It helps in creating a comprehensive dataset for meaningful insights.
Example #
Integrating employee health records with occupational injury reports for a comprehensive analysis.
14 #
Data Visualization Tool
A data visualization tool is software that enables users to create graphical rep… #
It provides interactive features for exploring and presenting data visually.
Example #
Using Tableau or Power BI as data visualization tools to create interactive dashboards for occupational health data analysis.
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Data Quality
Data quality refers to the accuracy, completeness, consistency, and reliability… #
It is essential to ensure that data is free from errors and biases.
Example #
Implementing data quality checks to identify and correct inaccuracies in occupational health data.
16 #
Data Transformation
Data transformation involves converting, normalizing, and standardizing data to… #
It includes processes like data cleaning, aggregation, and feature engineering.
Example #
Transforming raw sensor data into meaningful variables for predicting workplace hazards.
17 #
Data Warehouse
A data warehouse is a central repository that stores integrated and structured d… #
It enables organizations to access and analyze data for decision-making.
Example #
Storing occupational health data from different departments in a centralized data warehouse for analysis.
18 #
Data Exploration
Data exploration involves analyzing and visualizing datasets to understand their… #
It helps in identifying important variables and preparing data for analysis.
Example #
Exploring employee health data to identify trends in absenteeism and illness patterns.
19 #
Data Science
Data science is an interdisciplinary field that uses scientific methods, algorit… #
It combines statistics, machine learning, and domain knowledge for data analysis.
Example #
Applying data science techniques to predict occupational health risks based on historical data.
20 #
Descriptive Statistics
Descriptive statistics are measures used to summarize and describe the main feat… #
They include measures of central tendency (mean, median, mode) and dispersion (range, variance, standard deviation).
Example #
Calculating the mean and standard deviation of employee absenteeism rates in a company.
21 #
Histogram
A histogram is a graphical representation of the distribution of numerical data… #
It helps in visualizing the shape and spread of data.
Example #
Creating a histogram to analyze the distribution of blood lead levels in a population.
22 #
Machine Learning
Machine learning is a branch of artificial intelligence that enables systems to… #
It involves developing algorithms that can identify patterns and make predictions from data.
Example #
Using machine learning algorithms to predict the likelihood of workplace accidents based on historical data.
23 #
Multivariate Analysis
Multivariate analysis is a statistical technique used to analyze datasets with m… #
It helps in understanding the relationships and interactions between variables.
Example #
Conducting multivariate analysis to identify the factors influencing employee satisfaction in the workplace.
24 #
Predictive Analytics
Predictive analytics is the use of statistical algorithms and machine learning t… #
It helps in forecasting trends, identifying risks, and making informed decisions.
Example #
Using predictive analytics to forecast the number of workplace injuries in the coming year.
25 #
Qualitative Data
Qualitative data refers to non #
numeric information that describes qualities, characteristics, and attributes. It provides insights into behaviors, attitudes, and perceptions that cannot be quantified.
Example #
Analyzing qualitative data from employee surveys to understand job satisfaction levels.
26 #
Quantitative Data
Quantitative data consists of numeric values that can be measured and analyzed s… #
It includes variables such as counts, measurements, and percentages that can be quantified.
Example #
Analyzing quantitative data on employee absenteeism rates to identify trends and patterns.
27 #
Regression Analysis
Regression analysis is a statistical technique used to model the relationship be… #
It helps in predicting the value of the dependent variable based on the values of the independent variables.
Example #
Performing regression analysis to predict the impact of workplace stress on employee performance.
28 #
Time Series Analysis
Time series analysis is a statistical technique used to analyze and interpret da… #
It helps in identifying trends, seasonality, and patterns in time-dependent data.
Example #
Using time series analysis to predict the seasonal variation in workplace accidents.
29 #
Visual Analytics
Visual analytics combines interactive data visualization with analytical reasoni… #
It integrates human judgment and computational algorithms for data exploration.
Example #
Using visual analytics tools to explore patterns in occupational health data and identify potential risks.
30 #
Data Interpretation
Data interpretation involves analyzing data to derive meaningful insights and dr… #
It requires critical thinking, domain knowledge, and statistical reasoning to make informed decisions based on data analysis.
Example #
Interpreting the results of a regression analysis to understand the impact of workplace safety programs on employee injury rates.
31 #
Data Validation
Data validation is the process of ensuring that data is accurate, consistent, an… #
It involves checking data for errors, duplicates, and missing values.
Example #
Validating employee health records to ensure that all fields are filled correctly and consistently.
32 #
Data Cleansing
Data cleansing, also known as data scrubbing, is the process of identifying and… #
It helps in improving data quality for analysis.
Example #
Cleaning occupational injury reports by removing duplicate entries and correcting spelling errors.
33 #
Data Governance
Data governance is a framework that defines the roles, responsibilities, policie… #
It helps in maintaining data integrity and security.
Example #
Establishing data governance policies to regulate the use and sharing of sensitive employee health data.
34 #
Data Privacy
Data privacy refers to the protection of personal and sensitive information from… #
It involves implementing security measures and policies to safeguard data.
Example #
Ensuring data privacy by encrypting employee health records and restricting access to authorized personnel only.
35 #
Data Security
Data security refers to the protection of data from unauthorized access, use, or… #
It involves implementing security measures such as encryption, access controls, and data backup.
Example #
Securing occupational health data by encrypting files and restricting access to secure servers.
36 #
Data Mining Techniques
Data mining techniques are algorithms and methods used to extract patterns, tren… #
They include clustering, classification, regression, and association rule mining.
Example #
Applying association rule mining to identify frequent patterns in occupational injury data.
37 #
Data Strategy
Data strategy is a plan that outlines how an organization will collect, store, m… #
It involves defining data governance, data architecture, and data management processes.
Example #
Developing a data strategy to streamline the collection and analysis of occupational health data.
38 #
Data Architecture
Data architecture refers to the design and structure of data systems, databases,… #
It defines how data is collected, stored, accessed, and managed.
Example #
Designing a data architecture that integrates occupational health data from multiple sources for analysis.
39 #
Data Model
A data model is a conceptual representation of data objects, their relationships… #
It helps in organizing and structuring data for analysis and retrieval.
Example #
Building a data model for occupational health data that includes tables for employees, incidents, and interventions.
40 #
Big Data
Big data refers to large volumes of structured and unstructured data that cannot… #
It involves storing, managing, and analyzing massive datasets to extract insights.
Example #
Analyzing big data from wearable devices to monitor employee health and safety in real-time.
41 #
Data Analytics
Data analytics is the process of analyzing and interpreting data to uncover insi… #
It involves applying statistical and computational techniques to extract meaningful information from data.
Example #
Using data analytics to identify factors contributing to workplace accidents and injuries.
42 #
Data Integration Tools
Data integration tools are software applications that enable organizations to co… #
They help in creating a comprehensive dataset for decision-making.
Example #
Using Informatica or Talend as data integration tools to merge occupational health data from different departments.
43 #
Data Visualization Techniques
Data visualization techniques are methods for representing data graphically to f… #
They include charts, graphs, maps, and dashboards for visualizing complex datasets.
Example #
Using heatmaps and treemaps to visualize the distribution of workplace hazards across different departments.
44 #
Data Mining Algorithms
Data mining algorithms are mathematical models and techniques used to extract pa… #
They include decision trees, neural networks, clustering algorithms, and association rules.
Example #
Applying the Apriori algorithm to discover frequent itemsets in occupational health data.
45 #
Data Warehouse Architecture
Data warehouse architecture refers to the design and structure of a data warehou… #
It includes data sources, ETL processes, storage, and access layers.
Example #
Designing a data warehouse architecture to store and analyze occupational health data for trend analysis.
46 #
Data Visualization Software
Data visualization software is a tool that enables users to create visual repres… #
It provides interactive features for exploring and presenting data visually.
Example #
Using Microsoft Power BI or Tableau as data visualization software to create interactive dashboards for occupational health data analysis.
47 #
Data Science Techniques
Data science techniques are methods and algorithms used to analyze, interpret, a… #
They include statistical analysis, machine learning, natural language processing, and social network analysis.
Example #
Applying data science techniques to analyze social media data for identifying trends in workplace safety concerns.
48 #
Data Exploration Tools
Data exploration tools are software applications that enable users to analyze an… #
They help in exploring data interactively for insights and