Sometimes, the hardest part of analytics is getting data to analyze in the first place. Consilink can help you quickly identify and extract source system data for use in your analyses. We have the tools and experience to efficiently establish and maintain both standard and custom data feeds, including from both internal and external source systems. Also, our team can manage, monitor, and proactively resolve any issues in the feeds to keep your data flowing worry-free.
It’s well-known among data analysts that “garbage in equals garbage out”. Consilink “takes out the trash” from your data. We work with your team to identify, clean, and validate source data to ensure your organization doesn’t waste valuable analyst and IT resources investigating avoidable irregularities in your source data. Also, by adopting our repeatable, transparent processes and results, your team will learn how to systematically avoid data errors at the outset.
Deep analytic insights often appear at the intersection of disparate data sets, but blending data can be tricky. Consilink can help you develop the data models and architecture to properly integrate disparate datasets. We work with your teams to understand the nuances of each source, and then apply our experience to develop an extensible solution to correctly blend multiple data sets. Also, we maintain and operate a proprietary healthcare data warehouse built to blend many of the common datasets used in managing healthcare organizations (e.g., eligibility, claims).
Simply possessing data or analytic insights in your organization does not automatically improve decision-making. You need the right information at the right time to the right person in the right format. Consilink transforms your data and makes a difference in your business. We package and deliver information to improve decision-making. This includes moving raw data between systems, developing targeted datasets to support analysts, developing custom analyses to support business users. We provide the expertise and infrastructure to bridge the gap between having data and producing results.