Process

 

Process - Data Sources

Process - Data Warehouse

Process - Business Intelligence

Data Sources
Data sources can be any digital database or computer file located inside your firewall or externally at a vendor site. JOHO consultants will work with your team to identify and prioritize when and how to incorporate your source data into the JOHO OneSource™ data model.
Extract, transform, and load (ETL) refers the process of extracting data from digital sources, transforming the data into useful business needs, and loading it into the end target location. JOHO developers design these procedures using SQL Server Integration Services (SSIS) to move the data on a daily basis during off-peak hours from the source production systems into an Operation Data Store and/or Staging Area in order to prevent unnecessary strain on your daily operations.
JOHO ODS
The JOHO Operations Data Store (ODS) is a collection of select tables from the disparate data sources. It’s highly unlikely that all tables from each data source needs to be loaded, so this information often consists of only the important Member, Customer, Employee, Date/Time, Branch, Product, and other Transactional data that will appear in your BI reports.
JOHO STAGING AREA
The JOHO Staging Area is used a temporary landing location to “stage” the data prior to loading the ODS and/or data marts.
JOHO ETL DATA INTEGRATION
During the JOHO ETL Data Integration process, JOHO developers apply proprietary logic and rules prior to loading the actual data mart tables that allows the data from different sources to “talk”. Data joins, aggregations, lookups, and pivots, as well as data cleansing, custom data elements, and consistent formatting are often completed during this process. This is where the multi-source data integration “magic” occurs.
JOHO DATA MARTS
JOHO Data Marts represent small slices of the entire data warehouse and are oriented to specific lines of business (Loans, CDs, Checking, Savings, Mortgage, etc.) and/or departments (Sales, Operations, Human Resources, IT, etc.). The data is often denormalized into dimension (attributes) and fact (metrics) tables in order to simplify business user understanding of the data and to significantly increase report performance.
SECURE USER ACCESS
The data abstraction layer is the communication between the JOHO Data Marts and end-user reports, dashboards, mobile apps, scorecards, and analytics. The information displayed is business-user friendly, requires proper security rights to view, and is often delivered via a secure web site. The JOHO OneSource™ data model is vendor neutral, allowing any of the numerous business intelligence vendors to connect.
JOHO OneSource™ comes with several reports, dashboards, and scorecards out-of-the-box. However, not all businesses have the same requirements or strategic initiatives, so custom modifications can be delivered upon request.
  • Dashboards – Monitor business performance summaries, trends, comparisons, and exceptions across your organization relevant to specific objectives or business processes such as sales, finance, member growth, new loan/deposit production, and actual vs. goal variances.
  • Reports – Design interactive, professional-looking, on-demand displays of virtually any data scenario within your organization and deliver them to business users via a secure web interface or scheduled emails.
  • Analytics – Describe, predict, and improve business performance by understanding customer demographics, portfolio analysis, and financial statement ratios to help drive revenue, reduce risk, and improve operational efficiency.
  • Mobile Apps – Deliver business information to on-the-go employees via mobile devices or provide integrated source data to your own custom or third party mobile application.
  • Scorecards – At-a-glance groupings of specific Key Performance Indicators (KPIs). A branch scorecard may highlight accounts, transactions, deposits, loans, employee productivity, and customer survey scores with green, yellow, and red indicators to indicate if that location is on target.
  • Data Mining – Discover your customers’ banking habits and patterns using statistical analysis to help validate or disprove your “gut” feelings and develop marketing plans to target potential future behavior.