BH Technologies® Case Study
Amazon Web Services (AWS) Data Warehouse Solutions
Challenge
Our client, a provider of home loan, loan servicing, and refinance products to consumers and institutional partners in the United States (US), needed streamlined reporting and business processes to maintain accurate data.
Solution
To address our client’s needs, Beacon Hill Technologies deployed a high-functioning, cohesive team, including a program manager, senior program managers, a project coordinator, business analysts, quality assurance specialists, business intelligence (BI) data subject matter experts (SMEs), .NET developers, SQL developers, and Microsoft BI developers.
The Results
Our team successfully managed the implementation of a Microsoft data solution using Microsoft SQL 2014, SQL Server Integration Services (SSIS), SQL Service Analytic Service (SSAS), SQL Agent, and Master Data Services (MDS) / Data Quality Services (DQS). We also developed and presented comprehensive cost benefit analysis on AWS vs. onsite data storage; introduced project documentation standards for project timelines, decision, risk, and issue management, change control, testing, and migration; developed and managed first of its kind business intelligence intake tracking, prioritization, and initiation; designed and implemented resource model that allowed management to project and align resource needs across multiple projects; and managed BI reporting and analytics, Tool Proof of Concept for Microsoft Power BI, Qlik, and Business Objects.
Ultimately, our team was able to deliver three AWS-hosted data warehouse solutions. These implementations eliminated ten legacy data sources, automated regulatory and investor reporting, exposed business processes that were creating data quality issues, and allowed for easy and efficient ad-hoc reporting and analysis.
Ultimately, our team was able to deliver three AWS-hosted data warehouse solutions. These implementations eliminated ten legacy data sources, automated regulatory and investor reporting, exposed business processes that were creating data quality issues, and allowed for easy and efficient ad-hoc reporting and analysis.
