Organizations of all sizes are simply overwhelmed with data that is inconsistent with their business outcomes. That is where self-service Business Intelligence comes into play. While user categories might have varying needs, there are some commonalities.
Provide a roadmap for data governance & establishment of Information Governance Metadata Management practices
Technical & data leadership with a special focus on providing guidance to internal Enterprise Information Management, Enterprise Architecture & Application Development teams
Creation of a new information lifecycle for data platform initiatives.
Model transformations between RDB & MongoDB data models
Assistance in the design of the data microservice layer for the new data platform
Business Outcomes
Established Data Governance & built self-sustaining processes to ensure future compliance across multiple business lines
Introduced & adopted new agile practices within the Data Governance process, shortening project lifecycles, increasing collaboration & adding visibility to their programs
Required a consulting partner with expertise in the healthcare & pharmacy domain that could innovate & test solutions driven by analytics
Partnered with cross-functional teams & vendors to deliver impactful initiatives to patients
Drive day-to-day execution of these new initiatives & provide critical insights to guide decisions on future enhancements & net new functionality to accelerate growth
Analytics, testing & scaling of new products & development & run targeting logic/queries
Carefully track results to determine the value (contact vs. control) & initiative success
Business Outcomes
Ongoing effort & collaboration with the client as they continue to invest in this initiative because of the double-digit ROI outcomes
Accelerated growth with Swoon Consulting leading to day-to-day execution of new initiatives & providing critical insights that guided decisions on future enhancements & net new functionality
Required a strategic partner with ability to quickly supplement the existing team with outside expertise to support vaccine distribution efforts by utilizing data to take a hypothesis-driven approach to identify, forecast & solve for business opportunities
Provided a consulting team that consisted of a Product Owner, Data Scientist & Data Analysts to supplement full-time staff & delivered advanced modeling capabilities
Developed actionable insights around the workforce & improved processes for reporting
Researched data sources to better understand how data can be utilized to improve pharmacy operations
Business Outcomes
Developed a Tableau dashboard to deliver labor insights to business & field partners
The pilot had been rolled out & the client team was at 2.5% of the total completion of the initiative & didn’t have the people & expertise to accomplish their timeline goals
Collaborated with the business & led a team of advanced Data Engineers to design, build, test, productionalize & support the Front Store Personalization Engine
Designed a highly scalable & extensible Big Data platform that enabled industrializing collection, storage, modeling & analysis of massive data sets from heterogeneous channels
Business Outcomes
Caught up to the initial lagging project timeline by quickly building out applications & pipelines & establishing modern DevOps & release processes to speed up development cycles
Resulted in increased revenue & an improved curated & personalized customer experience
Created an enterprise staging environment by enabling interfaces to new medical device software
Architected & developed a data pipeline to move data from raw zone into conformed catalog entities
Created user reporting environment to enable access to the newly created Data Lake
Managed & forecasted storage & hardware requirements to make a recommendation for the smooth transition into daily operations
Created continuous integration, delivery & deployment (CICD) process to the integrated data pipeline changes based on modifications to the medical devices
Business Outcomes
Creation of Data Lake to host enterprise data enabled the client to study the behavior of its medical equipment & make necessary changes to improve their functionality
Improvement in devices reflected in an increase in device revenue by over 15%
Redesign & resolution of the product hierarchy discrepancies by working with the business & user base to confirm items within the category & sub-category challenged areas
Design & architect the data staging environment for incoming artificial intelligence (AI) & existing data in the ePBCS application
Marrying AI & user data to get the data sets to a common granularity
Integrate ePBCS Cloud application by designing & creating data pipelines
Validate the current ePBCS KPIs with predicted model KPIs
Business Outcomes
User predictions became aligned & AI budget predictions were over 80% accurate
Fully functional & reliable AI prediction models with user prediction accuracy improved by learning the prediction techniques
Collaboration with client teams to understand the current state & project requirements from product management groups, assess the optimal data solution, produce artifacts & articulate project vision to other teams
Develop conceptual & logical solutions for data acquisition, data models & pipelines
Provide technical guidance to client teams – data designers, engineers, & developers
Business Outcomes
Successfully performed a large data warehouse (Snowflake) implementation, addressed gaps in their existing technology stack, brought in new data sets & provided new data solutions for product development teams