Data Analytics Journey Roadmap for Banks & Credit Unions
Become a data-driven organization to make better decisions and relentlessly measure, monitor in a continuous and automated manner
- Generate & automate reports from data that are in different silo systems.
- Enable business analysts and other stakeholders find the needed data, perform necessary data scrubbing and create reports with minimal IT involvement.
- Create 360° view of member & loan portfolio with master data management.
- Gain insights into data by correlating with external data sources and find patterns.
- Improve key business metrics – loan growth, member satisfaction, profitability, acquisition, and retention.
- Enhance existing marketing program capabilities with advanced member segmentation to better match members with next best products.
- Develop an analytics roadmap with agile methodologies to quickly see the benefits and provide feedback.
- Member & loan data in multiple silos.
- Broad requirements to satisfy different CxO needs such as loan growth, better reporting process, member satisfaction, engineer’s productivity, and improved marketing program capabilities.
- Restricted access to data sources and formats due to vendor compliance policy and regulations.
- Proposed roadmap should coexist with past investments in IT applications and technologies.
- Educate key stakeholders on the data analytics journey roadmap and provide cost benefit analysis on infrastructure and resources.
- Treselle Engineering team created roadmap for data analytics journey that included Infrastructure, Analytics Foundation, Descriptive Analytics, Diagnostic Analytics, and Predictive Analytics.
- Emphasized the data analytics maturity that the client will achieve over time by following the roadmap.
- Identified high level capabilities that can be accomplished during each phase of the analytics journey using agile methodologies.
- Created logical and physical data lake architecture to visually represent the data pipeline process.
- Identified necessary tools and technologies based on Hadoop & Spark ecosystem.
- Applied necessary industry standards such as CUFX, HMDA codes, masking PII (Personally Identified Information), etc.
- Prepared the cost structure for both infrastructure and human resources needed to accomplish client’s goals in each of the analytic phases.
- Created list of business benefits that client will accomplish so business executives understand the value.
- Ensured that this new data analytics roadmap complements client’s investment in existing applications such as Tableau, Informatica, and MSSQL.
THE SOLUTION DIAGRAM: