Banks rely on numerous data sources, including internal systems, digital banking, CRM systems, external data, and web services. Banking Insight starts with these existing data sources and integrates them into the data lake.
Azure Data Lake Storage is a secure cloud platform that provides cost-effective and scalable storage for high-performance analytics workloads. This platform handles the most demanding analytics workloads allowing you to run large-scale analytics queries at a consistently high-performance level.
Azure SQL Database is an always-up-to-date, fully managed relational database service built for the cloud. Utilizing this database eliminates the complexity of configuring and managing high availability, tuning, backups, and other database tasks with a fully managed SQL database.
Power BI allows users to create and share interactive data visualizations through a unified, scalable platform for self-service and enterprise business intelligence (BI). The end result is an amazing data experience that makes it easy to visualize your personalized data.
Secure, cloud-based platform means no hardware to support and maintain
Access to Analytics Experts built into the monthly service fee
Free, online Analytics Assessment tool to evaluate current state; plan next steps
Take better control of data through defined standards, procedures and regulation
Lumio Insight is a proud Microsoft Partner, incorporating trusted Microsoft solutions into our Banking Insight Architecture. Our modular component solutions are supported by Microsoft’s unmatched technology portfolio to help your bank get the data it needs to uncover valuable insight.
We are passionate about helping community banks unlock their insight strategy.
Collecting data is easy. Squeezing insights out of data requires special skills and effort…but it’s worth the effort since actionable insights can be a fundamental enabler of business performance.
Managing data effectively requires having a data strategy and reliable methods to access, integrate, cleanse, govern, store and prepare data for analytics.
Not all data is valuable or even useful. Data quality is a difference maker. Data must be accurate, complete, reliable, relevant, and timely to be considered high quality and fit for purpose.
Data silos are bad for business. Effectively managed metadata and master data shared enterprise-widecan be both operationally and strategically leveraged throughout business processes.