“Onix helped us build the foundation for what will serve as a valuable cloud-native Asset Valuation Tool for our team.”
About the Customer
Catalyst Tech Ventures, Peachtree, GA was formed as a holding company — and a technology investment company — for select tech start-ups. The company’s assets involve mostly IT hardware and support services, especially for companies moving to the cloud — and that have an impact upon the skilled and experienced individuals required for this fast-paced environment. The company urgently needed to automate their process for determining market value from supplied lists in various formats
Catalyst knew they could save time by eliminating the manual process for obtaining information to establish costs for IT hardware. This time-consuming method of analyzing the data hindered their ability to move the business forward. The organization wanted a quick and innovative tool to handle the workload; a fully automated, event-driven data processing stack.
Onix developed a cloud-native Asset Valuation tool in Catalyst’s AWS Environment to read and reorganize data for visual insights delivered in an interactive dashboard. Using AWS services, Onix established a fully-automated, event-driven ETL pipeline to process data end-to-end using AWS Glue, Python and PySpark, registering the table technical metadata in AWS Glue DataCatalog. The ETL routine leveraged standard, raw, refined and curated data lake zones to process the data, convert it to parquet format — and store final results in a Redshift table for reporting purposes using QuickSight.
Additional AWS services included VPC (InternetGateway, EIP, NatGateway, Subnets, RouteTables, security groups, endpoints), the Onix Custom Data Lake foundation (S3 buckets, Lambda, IAM, SSM, LakeFormation, SecretsManger, Redshift) and Data ETL & Reporting (Lambda, Glue, Eventbridge, SNS, IAM, QuickSight). In just over one month, Onix delivered the asset valuation tool, giving Catalyst a quick, innovative way to identify costs with AWS Analytics products.
Impact and Results
Catalyst gained a fully automated data processing stack using AWS Serverless technologies (processing), AWS Redshift (data warehouse) — and AWS QuickSight for BI Reporting. CSV files are uploaded to an S3 bucket using Lambda and/or Glue. Technical metadata is registered in the AWS Glue DataCatalog. Ten form schemas have become just two. The QuickSight dashboard provides a consistent, filterable single-source output with a high-level raw data summary. Role-level data security provides centralized access management control to share with account managers, clients and their employees. Catalyst plans to further enhance the new dashboard as part of this project.