Swift’s data analytics team helps customers turn their data into insights, so leadership can make decisions with unprecedented insight and accuracy. Our team applies advanced analytics at scale for automation, visualization, and predictive modeling to find value, discover patterns, and develop capabilities across a variety of disciplines.
Data Modernization
We develop a modernization strategy to catalog and integrate legacy, file-based, and unstructured data systems into searchable, useable solutions that provide value.
Data Warehousing
Still a mainstay and central to many organizational strategies, we have expertise in building, managing, tuning, scaling, and integrating many types of data warehousing solutions.
Modeling and Reporting
Usage metrics provide facts to quantify the value of data. Knowing how, when, how often, and by whom data is used, leaders can show the value of their data investment.
Data Management
Swift brings extensive expertise in Extract, Transforming, and Loading (ETL) Data as well as data transport solutions.
Our solutions use predictive, analytical algorithms and emerging technology that will allow organizations to convert data into actionable intelligence and data-driven decision models. We provide the capabilities to manage and analyze both unstructured and semi-structured content, using data science techniques like predictive analytics and distributed processing frameworks like Hadoop, integrated with traditional structured data sources thereby providing new insights from the agency’s data.
We provide data governance, master data management, and data quality services to ensure that data is accurate, complete, and adheres to the privacy standards. Our team’s Business Intelligence (BI) tools efficiently present and share accurate, meaningful customer data from disparate sources and expose them using charts, pivot tables, reports, and visually appealing dashboards that can be saved, shared, modified, formatted, or embedded in the user’s personalized BI Intelligence Dashboards. This results in new levels of business user self-sufficiency. Our solutions ensure that big decisions are based on reliable data-driven models.
Our data scientists and engineers drive the convergence of multivariate modeling, statistics, and math in support of simulations and optimizations of all kinds. We analyze, build, and evaluate machine-learning (ML) models to increase business flexibility and support the organization’s data-driven objectives.
Our data scientists and analysts are experienced and certified in the following tools and techniques:
- R, SAS, Amazon SageMaker, Amazon Kinesis Data Streams
- Data Warehousing (Oracle, Informatica, SQL Server, Netezza, Apache Pig)
- Data Modeling (R, Erwin, Oracle SQL, MongoDB)
- Data Visualization (Tableau, Chart.js, Google Charts)
- Data Reporting (BI Publisher, SSRS, SAS, Crystal Reports, Excel)
- Provide platforms with multiple source and tool integrations that allow Organizations to act upon better data fusion