Data Warehousing & Engineering
Data Architecture

INTRODUCTION
Data Architecture Strategies bring your data ambitions to life
Calligo’s team of experts designs and builds tailored data solutions that enable efficient data management and utilization. By leveraging our expertise, we help businesses maximize the value of their data assets, whether that involves creating a data lake, designing a data warehouse, or building a robust data governance framework.
Our data architecture services are designed to meet the unique needs of each business. We work closely with clients to understand their data landscape, identify areas for improvement, and develop a customized solution that fits their specific requirements. By providing a comprehensive range of data architecture services, we help businesses enhance their data operations and gain a competitive edge in today’s data-driven business landscape.
How to build Data Architecture Strategy with Calligo
Based on your objectives, resources, culture and compliance obligations, we will use our creativity and expertise to craft a data infrastructure blueprint that will serve and support your every strategic ambition.
On top of the blueprint will lie a granular investigation of your data sources and assets – their location, quality and demands, and the platforms (cloud or on-premise), pipelines and technologies that they will need to perform their role in your strategic objectives.
Turning vision to reality. Our Data Engineers will create the pipelines, data models and environment that will transform your organization’s decision-making.
Why choose Calligo for your Data Architecture Strategy?
USE CASES
How Calligo has helped businesses
Calligo provides data-driven solutions to optimize manufacturing operations. Services include demand forecasting, inventory and logistics optimization, predictive maintenance, and supplier degradation analysis. Calligo integrates macro-economic shock models with company-specific data to help manufacturers make better decisions during unexpected economic shocks.
Calligo uses predictive models and time-series analysis to forecast demand and reduce inventory costs. The company also employs predictive models and survival analysis to help manufacturers reduce the risk of unplanned downtime by predicting when and how their machines will fail.
Retailers use demand forecasting with region-specific features to optimize product selection, increase sales, and reduce inventory losses. Calligo’s solutions use safe-harbor data anonymization methods to extract maximal value from customer data while maintaining privacy and avoiding legal risks.
Customer segmentation helps retailers market more effectively, improve product selection, lower risks, and understand expansion opportunities. Calligo’s machine learning solutions use customer data, external data, and domain expertise to create valuable customer groupings that inform various business areas.
Calligo provides data solutions to optimize various aspects of healthcare operations. Its services include improving the STAR rating of healthcare providers through prescriptive solutions, using predictive models and time-series analysis to prepare for a health crisis, optimizing staff scheduling to reduce labor costs while meeting patient needs, and minimizing inpatient surgical costs while maximizing revenue. Calligo also offers solutions to improve supply chain logistics to reduce the risk of inadequate supplies and reduce patient wait time through predictive models and optimization.
Moreover, Calligo offers solutions to reduce readmission rates and improve ER admittance, which can increase revenue in shared-cost models and improve the STAR rating. These services rely on predictive models, Monte-Carlo simulations, and machine learning models to analyze data and provide actionable insights to healthcare providers. With Calligo’s advanced data solutions, healthcare providers can make informed decisions to improve patient care, reduce costs, and optimize their operations for better outcomes.
Calligo provides transportation and logistics solutions that use predictive models, time-series analysis, Monte-Carlo simulations, and optimization to solve complex problems such as price optimization, cost predictions, and mileage optimization. These solutions help businesses maximize profit margin and reduce costs related to fuel, labor, and maintenance.
By utilizing machine learning algorithms, Calligo provides data-driven decisions that consider fuel costs, labor costs, shipping demand, and the availability of other opportunities. Predictive models and optimization are also used to minimize mileage driven and maximize profitability per truckload through mileage optimization and opportunistic loading.
Calligo provides data-driven solutions to optimize different aspects of telecom operations such as call center staff scheduling, market penetration analysis, store location optimization, service interruption detection, and customer segmentation. The use of predictive models and optimization leads to reduced costs, increased revenue, and higher customer satisfaction.
By leveraging machine learning solutions, Calligo can efficiently meet customer needs and optimize labor as call center needs change. Understanding market penetration using predictive models and time-series analysis helps identify high-potential markets that yield the best return on investment.
Calligo is a data science company that helps non-profit organizations improve their decision-making process. They use predictive models, time-series analysis, and economic modeling to forecast the value of investments and marketing impact. Their machine learning solutions use data from new markets, employee and resource data, to predict outcomes, helping organizations choose the most advantageous new markets to pursue.
Calligo also uses predictive modeling to determine the best targets for fundraising efforts, to allocate labor efficiently, and to find the most efficient routes and methods for product shipping. Finally, they use optimization, predictive models, anomaly detection, and collaborative filtering to match service providers with service recipients, reducing risk, and increasing the number of services rendered.
Calligo provides machine learning solutions for the financial industry, including fraud detection, automated data extraction, customer segmentation, risk assessment, and product recommendations. Fraud detection uses clustering, anomaly detection, and time-series analysis, while OCR algorithms facilitate automated data entry. Customer segmentation uses clustering and collaborative filtering.
Risk assessment and underwriting involve predictive models and time-series analysis, while Calligo helps capture the best return on marketing investments using predictive models, A/B testing, and customer segmentation. Predictive models, collaborative filtering, and time-series analysis are also used to generate additional revenue through product recommendations and execute targeted marketing for reduced costs and increased revenue.
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