From the outset, Lucky Strike Entertainment’s intent was to offer a magical place to let loose, have fun, and feel great! Over the years they have expanded throughout the country and have continued to add more things to do and an ever evolving menu of fun, food, and drinks.
Lucky Strike Entertainment utilizes several disparate systems to manage process and operations. Knowledge workers often need access to data assets across these systems to make decisions and gain insight. Data exports and mashups are used today and are time consuming and error prone. They wanted to unify these data assets into a single platform to support efficiencies, accuracy, and greater insight for their users.
IOLAP’s role in this project will be to design, develop, test, and deploy the solution on AWS. We created the necessary infrastructure and systems to support the business requirements. The conceptual design called for the following components: • Ingestion Engine: This asset is responsible for extracting data assets from MicrosPOS, Salesforce, Tripleseat, and Compeat. It manages the scheduling and orchestration of the extraction and handles publishing this data for further system consumption. • Data Lake: A foundational data lake will be created using several AWS services. The lake will leverage Amazon S3 to store raw flat files pulled from the source systems. • Transformation Engine: Responsible for transforming raw data into the data warehouse. This handles data cleansing, business rules, aggregations, etc. • Data Warehouse: This Amazon Redshift based solution will follow dimensional modeling techniques to store and deliver relational data to consumers (e.g. PowerBI or Tableau). IOLAP will create the cluster and all data models supporting the business need. • Analytics Tools & Packages: This is the infrastructure, business abstraction layer, reports, and dashboards that end users will consume. IOLAP assumes 2 key dashboards and multiple supporting detail reports.
Lucky Strike was able to transform its data into a modern data warehouse that integrated Sales & Labor data from MicrosPOS, event sales data from Salesforce and Tripleseat and relevant dimensional data from Compeat
AWS based infrastructure was key to take full advantage of that allowed their solution to go to market quickly and scale securely and cost effectively
TCO was reduced by 50 percent by migrating key on premises infrastructure to AWS cloud
75% increase in data transformation efficiency to deliver Sales & Labor reports to decision makers due to AWS cloud efficiencies to go to market quickly