Data Analytics
We use data analytics to discover, interpret, and communicate meaningful patterns and trends in data. Through the application of analytics techniques, we are able to deliver objective insight and data-driven strategic recommendations.
We work with existing data sets, and can build simple to complex data sets containing data from multiple sources. We have expertise collecting, scrubbing, transforming, and modeling data. We can produce descriptive, diagnostic, predictive, and prescriptive analytics.
Our past projects include a wide variety of areas ranging from consumer market segmentation to international trade analysis to analysis of the effects of introducing a new domestic economic policy.
Over the years, we have developed expertise in the following areas:
Data mining, Data visualization, Big data, Text analysis, Machine learning, and Spatial analysis.
Data Mining
We employ data mining to extract information and discover patterns and correlations in large data sets. We segment the data by identifying natural groupings. We transform information into a comprehensible structure for further analysis. And we use machine learning and statistical models to uncover hidden patterns in large data sets. We perform clustering, classification, and regression with the information found in the data sets. Insight and actionable information is then derived from the data and provided to decision-makers.
Data Visualization
Our objective is to communicate information clearly and effectively. Our data visualization methodologies allow us to present complex information through statistical graphics, plots, information graphics and other charts. We incorporate various data visualization techniques to make data and information more accessible, understandable, and usable. Through several forms of data visualization, we are able to present comparisons, causality, associations, patterns, and trends involving different variables. Our dashboards, infographics, charts, plots, and graphs provide intuitive and consumable information.
Big Data
We use big data analytics with large, diverse data sets that include structured, semi-structured, and unstructured data. Using large volumes of data from several sources, we are able to employ text analytics, predictive analytics, data visualization, AI, machine learning, statistics, and natural language processing. Through these analyses we are able to uncover trends, patterns, and correlations in large amounts of data which can help decision-makers.
Text Analysis
Our text analysis techniques allow us to extract information from unstructured text, including trends and patterns. We have experience performing text classification (e.g. topic analysis, sentiment analysis), and text extraction. And we are able to provide insights from these analyses. While text analysis is able to provide qualitative insight, we also use text analytics to transform insight into quantitative data, which is then represented through data visualization.
Machine Learning
We leverage machine learning to explore data and identify patterns. Using both supervised and unsupervised learning, we are able to provide recommendations about ways to improve internal processes and reduce workloads and inefficiencies. Machine learning allows us to detect what the human eye may not, including complex patterns that otherwise would have been overlooked during human analysis. The use of algorithms allows us to examine much larger sets of data and understand patterns quickly and effectively. For instance, we use K-means clustering to identify patterns or groups within a data set of interest. We have used clustering in several projects ranging from market segmentation to international trade analysis.
Spatial Analysis
Our expertise in spatial analysis allows us to apply statistical analysis and other techniques to data which has a geographical or spatial aspect. We combine GIS-based network analysis and Geovisualization (e.g. images, maps, diagrams, charts, 3D views) and produce studies that analyze patterns and trends in data. We have used spatial analysis in projects involving economic development, trade, political economy, labor economics, and socio-economic issues.