Michael Friedhoff Email & Phone Number

Addison, Tx

Concentra – January 2015 to CurrentData Engineer(healthcare)Goal: • Strategic/Key account reporting automation. • Marketo, CRM (MS Dynamics), and Revenue automation and integration. • Creation of Sales center contribution analytics.Steps: • Created detailed sales performance analysis for sales initiatives and strategies. • Supported reporting of acquired customers to determine which customers were lost in the process. • Coached a junior ETL developer on methods to build workflow for Marketo REST api data acquisition. • Developed the workflow to extract daily the Marketo data from the REST api. • Built data structures to ensure that all sales channels could be analyzed via MicroStrategy. • Enabled direct drill through from MicroStrategy dashboards directly to CRM – MS Dynamics. • Designed and built the trailing 12 months and following 12 months revenue comparison process.Result: • Star Award sponsored by the sales department. • Sales now fixes data quality issues in the source system instead of the final reporting/analytics. • Confirmed that not 1 single employer constitutes more than 3% of Concentra's gross revenue. • $80k yearly savings after converting commission start date to admit date from transaction date. • Ensured growth for existing accounts by changing the way baseline is calculated for commission payout. • Sales' dashboards are now updated and calculated daily instead of monthly or even quarterly.Future: • Implement visit based cost analysis (Sales, Marketing) - Return on Investment. • Facilitate marketing's self-sufficiency in regards to reporting. • Forecasting/projections. • Account/customer retention insight.

Dallas, Texas

Goal:• Source data from the EDW, Wizard, Trax, Swift, and the Tibco bus to create a new dedicated data mart for the maintenance department.• Build an analytical model in real-time while sourcing the data from multiple distinct continuous streams to track aircraft maintenance events.Steps:• Listened to the internal Customer, aircraft maintenance, in order to obtain the needed business context and insight.• Drove agreement between three different entities, dispatch, maintenance, and corporate modeling, so that the data and metrics told the proper story.• Created requirement documents and source to target documents for use by the developers.• Instituted defensive coding algorithms to address data quality issues in the OTS data being derived from the Routing GUI.• Managed all ETL developers through the entire define, design, and build phases.• Ensured that the target model and ETL graphs were thoroughly tested before being deployed into production.Result:• New ability to determine the length of an aircraft maintenance event.• Enterprise wide belief in the quality and accuracy of the aircraft maintenance event data.• Almost real-time access to data.

Dallas/Fort Worth Area

Goals:• Throughput analysis for six emergency departments in the Baylor Healthcare System.• Populate warehouse daily (dimensional model/star) from six independent emergency department information systems.Steps:• Built the source to target documentation that was used by the ETL developers.• Analyzed source data from MedHost and Eclipsys.• Defined conformed dimensions such as arrival methods and disposition locations.• Implemented a comprehensive regression testing environment.• Resolved warehouse issues that ranged from primary key violations to inconsistent data values resulting from source system data inconsistencies.• Assured quality data by scouring the data sources to determine if ETL process flows would account for all data forms (nulls, zeroes, etc).Result:• Created the ability for the executive management team to compare the performance of all of the emergency departments within the enterprise.

Dallas/Fort Worth Area

Goal:• Determine why multiple source systems differed in results regarding the U-verse products sold (Data Quality).Steps:• Designed custom one-off SQL queries to pull data directly from several different source systems, warehouses, and a dimensional database.• Utilized Kettle (Pentaho Data Integration) to automatically generate custom Excel spreadsheets that combined data from the dimensional reporting database with the source transactional data in the warehouses.• Discovered data structures and meaning of data in the warehouses with minimal assistance and documentation.• Deciphered the path and systems by which orders traverse once they left the point of sale system on their way to final provisioning.• Reconciled differences in results between reports generated in 3 different reporting systems.• Generated queries against database tables that contained several hundred billion rows.Results:• Determined that modifying one single upstream business process negated the need to make code changes in at least seven different downstream systems.