This series has explored Freedman Analytical Engine (FAE)’s purpose and process. More specifically, we have looked at the problems that FAE solves, the need for standardized data in order to complete analysis, and the involvement of programmers and analysts in completing this ETL process. We have described ways in which file structures are identified and...Read more

In the last post, we discussed the five file formats encountered by Freedman Analytical Engine (FAE) as it processes Centers for Medicare and Medicaid Services (CMS) quality data. They require FAE to standardize these files to create one merged CSV. This merged file will most closely resemble a Vertical ID file. This post will focus...Read more

In the last blog post we discussed augmenting the ETL process for CMS quality data. Freedman Analytical Engine (FAE) starts with this quality data, which does not have a consistent structure, and normalizes the column headers and measure identifiers, merging it into one CSV for analysis. To normalize these varying formats, the different file structures...Read more

When something occurs automatically, the computer completes a task from start to finish. In an augmented task, the computer helps the person to complete the task, but needs some form of interaction or input from the user. Previously, we explained how Freedman Analytical Engine (FAE) uses metadata dictionaries to convert column headers and measure identifiers...Read more

In the previous blog post, I explained the general ETL process for CMS quality data. Analysis of quality data from the Centers for Medicare and Medicaid Services (CMS), just like all payer claims data, population health management data, and other data sources, requires the data to be extracted, transformed, and loaded. The majority of this...Read more

New Blog Series: Inconsistent Data Sets How do you deal with inconsistent data? Every experienced analyst knows that about 90% of the job is getting your data in shape for analysis. This 90% is not only time-consuming, but also more drudgery than enlightenment. This is especially true if you need to merge multiple data sets...Read more