Data Science
Overwhelmed by vast amounts of complex data? At Resource Data, our Data Sciences experts help you harness this data using advanced predictive modeling, machine learning, and Natural Language Processing (NLP). Your information is turned into actionable insights that drive innovation and improve decision-making.
Expertise
Make smarter decisions, faster.
Data science transforms raw information into strategic advantage—and we know how to make it work for you. At Resource Data, we blend practical business insight with powerful techniques like statistical modeling, machine learning, and advanced text analysis to deliver measurable results. Whether you’re optimizing resource use, forecasting trends, or uncovering hidden patterns, our solutions help you confidently anticipate change and drive better outcomes.
Predictive Modeling
You’re not alone if you’re feeling uncertain about future market shifts and decision-making. Using statistical techniques, Resource Data develops sophisticated predictive models to analyze historical trends and forecast future outcomes. These models are custom built specifically to your needs, so your strategic decisions are data driven. Gain the clarity, confidence, and operational efficiency needed to proactively manage risks and opportunities.
Machine Learning
Rigid systems can limit your agility in adapting quickly to evolving data. Machine learning (ML) addresses this by enabling computers to learn and improve from data, without explicit programming. We develop algorithms and deploy machine learning solutions able to use large amounts of data with limited human intervention. Our solutions continuously refine their accuracy and perform tasks autonomously, so your team can streamline operations, optimize resources, and remain agile even in rapidly changing environments.
NLP and Text Analytics
Large volumes of unstructured text data often present challenges in extracting meaningful insights. Natural Language Processing (NLP) equips computers with the ability to understand, interpret, and generate human language. Resource Data leverages NLP and text analytics expertise to swiftly convert textual information—such as regulatory filings, operational reports, maintenance logs, and public inquiries—into actionable insights. With these insights, you can automate routine tasks, enhance decision-making, and significantly improve organizational effectiveness.
Data Mining
Overwhelming datasets often conceal valuable, untapped opportunities. Data mining involves systematically exploring and analyzing large datasets to uncover meaningful patterns, correlations, and trends. At Resource Data, our advanced data mining techniques help reveal hidden insights, enabling you to drive strategic decision-making, discover opportunities for innovation, and sustain a competitive advantage.
Our Clients
Hundreds of clients. Thousands of data projects.
“With every sprint, we are doing something that is changing the industry in education. We want to blaze the trail for what’s coming up and what’s new and possible in education, and we couldn’t really do that without Resource Data. I trust the Resource Data team wholeheartedly with all of the visions that we have and things we want to do in the future. I know that they will find a way to make it work.”
~ Gretchen Clarkson, Business Analyst, Epic Charter Schools
Alyeska Pipeline Service Company
Industry-Leading Data Analytics Tool Saves Pipeline Operator Millions
Engineers for Alyeska Pipeline Service Company (Alyeska) needed an automated data analytics tool to identify temperature loss locations along the Trans-Alaska Pipeline System (TAPS).
Scraper Pigs containing a Pipeline Data Logger (PDL) frequently traverse and clean the 800-mile pipeline. They collect large volumes of records of data on time, temperature, pressure, and acceleration during each trip. Given the sheer volume of data points, the PDL manufacturer and the engineers could not manually identify the Pigs’ geographic location at the time the data was collected.
Resource Data created an automated algorithm and interactive application which allows engineers to match data within a 60-foot location along the pipeline. Accurately identifying temperature loss locations helps engineers to perform heat loss mitigation activities. Visualizing the data graphically enables engineers to see new relationships between datasets and make recommendations to operators. The industry-leading geolocating tool helps Alyeska maintain crude oil flow, minimize wax buildup, and prevent compromised pigs.
Major Oil and Gas Company
Seeing Beneath the Ice: AI and GIS Unlock Hidden Terrain Changes
An oil and gas client needed a safer, more efficient way to analyze thermokarst—irregular terrain caused by thawing ice-rich permafrost—to monitor degradation and identify areas suitable for development. Traditional methods were costly, limited in scale, and required risky fieldwork, including lengthy helicopter flights and wildlife hazards. With climate change accelerating terrain changes, the client sought to proactively detect hazards like pingo collapses through remote monitoring and modeling.
Resource Data implemented a GIS and deep learning solution using high-resolution satellite imagery and a custom convolutional neural network (CNN). We manually digitized more than 1,000 features to train a model that achieved over 90% accuracy in detecting polygonal ground. Our team then enhanced the model to identify features like pingos, thermokarst lakes, and troughs, while supplementary analyses provided insights into surface hydrology, subsidence, and gas-emission craters.
With advanced environmental-monitoring methods, our client can drastically reduce analysis time and effort. This project also inspired interest in automated feature detection across the client’s remote sensing teams and showed AI’s potential to support sustainable development and future environmental studies.
Allpoints Surveying
AI-Driven Automation Simplifies Order Processing
As Allpoints Surveying expanded into new markets, processing customer orders from emails, PDFs, and spreadsheets became a challenge. The industry’s inconsistent terminology, Allpoints’ multi-region operations, and errors in customer emails made manual categorization by coordinators time-consuming and error prone. AllPoints needed an adaptive solution to handle these complexities.
Resource Data implemented an AI solution powered by OpenAI’s GPT-4 for a proof of concept (POC). The AI parsed sample emails, extracting key details like builder names, lot addresses, and task requests. Advanced data-validation techniques matched this information to AllPoints’ MasterJob and Customer tables, producing structured outputs. The system also identified surveying task requests, linked them to a list of standardized task names, and assigned task IDs.
The POC achieved 94% accuracy in identifying builders and 68% accuracy in standardizing tasks. These results showed how AI could enhance efficiency and help AllPoints achieve future system integrations and operational improvements.
Major Oil and Gas Company
Machine Learning and GIS Advance Lake-Volume Estimation
For an oil and gas client in northern Alaska, estimating lake volumes is essential to meet permitting requirements for water withdrawals while preserving fish habitats and water resources. Traditional field surveys, covering only 10 percent of the region’s lakes over 30 years, are time-intensive and costly. Our client needed a more efficient way to get necessary data.
Resource Data explored innovative solutions using GIS and machine learning to accelerate this process while complying with regulations. We tested random forest regression models using ArcGIS Pro toolboxes to estimate lake volumes based on geospatial data that’s specific to northern Alaska. By refining this model and integrating it with advanced GIS methods like topobathymetric LiDAR, we continue to enhance its efficiency and precision.
This approach provides a faster, scalable solution to support permitting processes for our client while protecting vital fish habitats across Alaska’s lake-rich regions.
Oil and Gas Company
AI Optimization Increases Plant Efficiency
At an oil and gas client’s electrical power generation and hydrocarbon recovery facility, operators were hampered by the facility’s inefficient, ’70s-era design. Facing rising fuel costs and limited energy recovery from hydrocarbon vapor, they managed the plant reactively to meet safety requirements, resulting in efficiency and quality losses. Plus, complex systems and vast historical data complicated identifying key performance variables to improve operations.
Resource Data employed expertise in statistics and simulation with machine learning (ML) to help our client collect critical data and understand how to make improvements. Advanced ML tools included an extra tree random forest regressor (RFR) and classification tasks with neural networks to analyze millions of records spanning 10 years and hundreds of derived features. These models distilled data into 12 critical variables, helping engineers simulate what-if scenarios and test system configurations for better performance.
The client can now conduct more accurate simulations, revealing key interactions and the impacts of equipment upgrades, operational adjustments, and redesigns. This data supports engineering work focused on implementing sustainable operational improvements to achieve annual fuel cost savings.
Real-World Solutions
Data science in action.Smart. Scalable. And already working.
At Resource Data, our data science solutions are built to deliver meaningful results—no hype, just practical impact. We’ve helped clients across government, education, energy, and manufacturing harness data to solve real-world problems and seize new opportunities. Whether it’s automating inspections, improving student support, or delivering targeted customer experiences, data science is already reshaping how organizations operate. Below are examples of how these technologies are making a difference across industries—and how Resource Data can help you apply them.
Speech Recognition
Speech recognition is the ability of software to identify and process human speech into a machine-readable format. These systems enable hands-free interactions and automated documentation. In healthcare, they streamline provider note-taking and patient record updates. In transportation, voice-activated controls improve safety and operational efficiency.
Chatbots and Virtual Agents
AI-driven chatbots and virtual agents simulate human conversation to handle routine customer interactions. These tools enhance responsiveness and satisfaction by offering quick, automated assistance. For instance, education institutions use them to answer admissions and financial aid questions, while financial services firms deploy them to support 24/7 account management.
Computer Vision
Computer vision gives machines the ability to interpret and process visual information of the physical world such as images or video. It automates tasks like equipment and quality control inspections in manufacturing, remote monitoring of environmental conditions in natural resource management, and infrastructure analysis for urban planning. Computer vision’s ability to find patterns, identify anomalies, and detect hazards improves accuracy, reduces costs, and advances safety across sectors.
Spatial Analytics
Spatial analytics involves analyzing data that includes geographical or spatial information to derive patterns, relationships, or trends. In public health, it supports tracking disease outbreaks and resource distribution. In education, spatial data is used to assess student access to resources and optimize school zoning. Utilities employ spatial analytics for asset management and outage prediction, and energy companies leverage it for environmental impact studies and site assessments.
Recommendation Engines
Recommendation engines are algorithms designed to analyze user behavior and suggest content, products, or actions tailored to individual preferences. E-commerce platforms use them to drive sales through personalized product suggestions, while utilities offer personalized energy-saving programs. Government agencies use them to connect citizens with relevant public services and in higher education, these engines guide students toward courses and resources based on performance and interests.
Rick Busch
Service Area Lead, Data Engineering
With a dynamic blend of technical and leadership experience honed over 20 years in IT, Rick has solidified himself as a seasoned project manager, data engineer, and architect. His comprehensive technical knowledge in software engineering, database development, and data warehousing underpins his ability to steer complex projects.
Rick is instrumental in guiding clients through the nuanced landscape of cloud-based data warehousing. He specializes in devising and executing strategies to transition traditional on-premises data warehouses to leading cloud platforms, including Snowflake, Microsoft Azure, and Amazon Web Services.
Talk to Rick Busch
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