Unlock AS400 Data With Data Warehousing and Business Intelligence Visualization

Unlock AS400 Data With Data Warehousing and Business Intelligence Visualization


Your AS400 Can Still Power Monster Business Growth. It Just Needs A Friend.

AS400 systems, once at the forefront of retail technology, are still critical for many mid-size retailers, but their outdated interfaces, limited integration capabilities, and the shrinking pool of IBM i specialists present significant operational challenges and make it hard to keep up in today’s fast-paced environment. Modernizing AS400 data through data warehousing and business intelligence (BI) tools can solve these issues, enabling real-time insights, better decision-making, and smoother operations.

Key Takeaways:

  • AS400 Challenges: Outdated interfaces, integration difficulties, and a shrinking pool of IBM i specialists.
  • Data Warehousing Benefits: Centralized data, improved reporting, historical analysis, and reduced system strain.
  • BI Tools Advantages: Self-service analytics, interactive dashboards, and automated reporting.
  • Integration Steps: Use ETL tools, map data structures, and prioritize security.

Quick Overview:

Solution Benefit
AS400 Backbone system for operational software like ERPs and PIMs
Data Warehousing Centralized reporting, deeper analysis
BI Visualization Actionable insights and real-time dashboards
Integration Approach Phased implementation and strong security

By combining AS400 data with modern tools, retailers can improve inventory management, customer insights, and operational efficiency – all while extending the life of their legacy systems.

Expert Interview: About Dean Wynkoop

For this article, we interviewed Dean Wynkoop, Co-Founder of Retlia, a leader in retail intelligence. He has been deeply involved in maintaining AS400 systems for some of the world’s most prominent companies, including a top national financial services firm. Dean was also instrumental in the implementation of one of the pioneering retail data warehouses at outdoor retailer Cabela’s, who also made use of AS400 systems. His extensive background in both legacy and modern data solutions gives him a unique perspective on integrating these systems to achieve operational excellence.

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About The i-Series AS400

What Is the AS400?

The AS400 (now known as IBM i) is a legacy transactional system still heavily used in retail and manufacturing. While it might appear outdated, it operates similarly to other modern databases and offers some unique architectural benefits.

Just Another Source System

At its core, the AS400 is a transactional system—just like Microsoft Dynamics, Salesforce, or JDA. It stores operational data, integrates with other systems, and acts as a standard source system in a data environment.

"It’s no different than any other database. It’s a transactional system." – Dean

There’s nothing particularly unusual or complex about its table structure when compared to SQL Server or Oracle. If you know how to work with relational data, the AS400 won’t feel foreign.

SQL-Friendly File Architecture

One standout feature of the AS400 is how it handles files and tables. On this platform, there’s no meaningful distinction between a flat file and a database table—they’re all queryable via SQL.

"There’s nothing special or complex about the table structure in an AS400 as opposed to SQL Server or anything else." – Dean

This simplifies data extraction and allows for more flexible querying, especially when integrating older systems into modern data pipelines.

Object-Oriented From the Start

The AS400 was ahead of its time in adopting an object-based operating system. Everything in the system is treated as an object, including tables, which are just subtypes of objects. This architectural choice makes the platform more consistent and modular under the hood.

Easy to Connect, Even Today

Thanks to its built-in ODBC and JDBC connectors, tools like Matillion can connect to the AS400 out of the box—no special treatment required. It integrates with modern systems just like SQL Server, MySQL, or Oracle, making it much easier to bring legacy data into cloud analytics platforms.

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Quirks and Challenges Accessing AS400 Data for Reporting and Analytics

For many mid-market retailers and wholesalers, the AS400 is still the backbone of daily operations—but its design, naming conventions, and programming culture can make modern data usage difficult. These challenges don’t necessarily come from the hardware itself, but from decades of backward-compatible programming practices. If you’re trying to centralize your data, automate reporting, or introduce self-service analytics, these quirks can stall or derail your efforts unless you have expert support.

  • Antique Field Naming Conventions limit discovery and understanding
    Field names are often cryptic (e.g., P1PONUM for purchase order number) due to early 6–10 character limits. Longer SQL aliases exist but are rarely configured or documented.
  • Legacy monolithic design makes logic hard to trace
    AS400 programs often combine business logic, data access, and UI in one file. There’s no clean separation of layers like in modern architecture.
  • Native coding uses non-SQL access methods
    Many programs use RPG’s native CHAIN and READ instead of SQL, relying on developer-managed indexes and data paths. This adds friction when extracting structured data.
  • Data types and encoding cause mismatches
    AS400 uses EBCDIC encoding by default, not ASCII, which introduces complications when transferring or transforming data.

    “One story I like to tell is I used an integer for a numeric value and the developer was furious I used ‘strange data types’—even though it was the most common data type in the world.”
    —Dean Wynkoop

  • Low availability of skilled resources
    Few people understand both AS400 and modern cloud/data tools, making it hard to staff for integration or migration work.

    “The number of people that understand AS400 and newer technology—you can count on your fingers and toes.”
    —Dean Wynkoop

  • Backwards compatibility leads to tech debt
    IBM ensured AS400 remained compatible with even punch-card-era systems, so teams often maintain decades-old conventions.

    “AS400 was designed to be backward compatible all the way back to card-based systems. That’s why so much of the code is still antique.”
    —Dean Wynkoop

  • Limited adoption of modern tools
    While AS400 supports modern languages like Python or C++, most development still uses RPG. The system isn’t technically limited—but culturally, it’s stuck.
  • Non-standard performance tuning
    AS400’s performance can be excellent, but optimizing it often requires deep RPG knowledge and manual index management.
  • Hardware is robust—but the talent and tooling gap remains
    The AS400 itself is technically powerful—sometimes even ahead of its time—but its surrounding ecosystem limits its usefulness for today’s analytics and BI needs.

    “If I was an executive that had to pick AS400 versus SQL Server—if I discounted the resource thing—I think AS400 beats SQL Server hands down.”
    —Dean Wynkoop

Bottom line for execs:

  • Your data isn’t stuck because AS400 is old—it’s stuck because it wasn’t designed to be shared.
  • With the right approach and expertise, you can extract and modernize this data, but it takes strategy and planning.
  • While it supports many great, modern ways for getting the data out—you’ll likely need specialized people to navigate the AS400 quirks and bridge the AS400-to-modern gap.
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Connecting AS400 to Data Warehouses

Data warehousing creates a centralized hub for AS400 data, addressing the operational limitations of older transactional systems. This setup also prepares the data for advanced BI visualization, which is vital for turning raw data into actionable business insights.

Why Use a Data Warehouse?

While AS400 systems excel at handling day-to-day transactional processes, they are limited when it comes to complex analytics and large-scale reporting. Data warehouses make it easier to combine AS400 data with other retail systems, allowing for deeper analysis that legacy systems just can’t handle. Modern data warehouses, however, offer solutions to these challenges by processing in environments designed for high performance in analytics and reporting. One major perk? Analytical processing is kept separate from daily operations, so critical business functions aren’t slowed down by complex queries or reporting processes.

Here’s what a data warehouse can do:

Feature Business Impact
Consolidated Reporting A unified source of truth across systems
Historical Analysis Helps identify long-term trends
Performance Boost Reduces strain on production systems
Data Integration Offers a combined view of business activity

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Using BI Tools with AS400 Data

Retail BI Tools Overview

Modern BI tools help transform AS400 data into practical insights through user-friendly self-service analytics and interactive dashboards. These platforms are designed to assist mid-size retailers in making informed decisions without needing advanced technical skills.

Feature Business Value
Self-Service Analytics Lets teams create reports without relying on IT support
Custom Dashboards Offers real-time insights into key retail metrics
Report Automation Saves time by automating scheduled data updates
Data Integration Combines data from various sources into one view

These features form the foundation for clear and effective data visualization.

BI Data Visualization Impact

Interactive, visual dashboards simplify complex AS400 data, making it easier to interpret and act on insights. Some key visualization features you should seek to gain as you connect your AS400 to a data warehouse and BI tools include:

  • Drill-down analysis to explore sales trends
  • Interactive filters for detailed inventory, product, and customer insights
  • Customizable report formats like charts, graphs, tables, and AI chats
  • Embedded analytics directly within business applications

"Everyone has data, but not many people have information. To me, that’s a transformation of taking data that is widespread in disparate systems a lot of times in companies and bringing it all together to do analytics." – Aaron Ambur, Nexus Outdoors

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Implementation Guide for Mid-Size Retail

Data Evaluation Steps

Start by analyzing your AS400 system to gather critical retail metrics like sales, inventory, and customer data. Focus on these three key areas during your evaluation:

  • Data Quality Assessment: Look for duplicate records, missing entries, and outdated information that need cleaning before integration.
  • Business Requirements Analysis: Map out each department’s reporting needs to ensure all essential data is covered.
  • Technical Infrastructure Review: Check your system’s capacity and identify any technical limitations that could affect integration.

Once you’ve assessed your data, choose tools that simplify both integration and reporting.

Choosing the Right Tools

Retlia is purpose-built to help mid-size retailers finally unlock the full value of their data—especially when legacy systems like AS400 are holding them back. While AS400 remains reliable for transactions, it lacks the transparency, speed, and flexibility needed for today’s analytics. Retlia fills that gap with a modern data stack—Matillion for scalable data extraction and transformation, Snowflake for fast, cloud-native warehousing, and Tableau for intuitive dashboards and visual analytics. Layered on top is Retlia’s own retail-specific schema, executive dashboards, and drilldown tools designed for merchandisers, operators, and finance leaders. Together, these components turn siloed AS400 data into clean, usable insight that supports faster decisions, self-service exploration, and unified performance tracking across teams.

Component Purpose How It Overcomes AS400 Limitations
Matillion Cloud ETL for extracting and transforming AS400 and other source data Native connector easily accesses AS400 data structures
Snowflake Cloud data warehouse with fast query performance and flexible scaling Replaces AS400’s rigid storage with searchable, high-performance joined data
Tableau Front-end BI and dashboards with self-serve drilldown and trend analysis Adds visualization and self-service not possible in AS400
Retlia Retail Schema Midsize retail-specific data model for sales, inventory, margins, and more Simplifies messy AS400 fields into clear business metrics for reporting performance
Retlia Executive Dashboards KPIs tailored for finance, merchandising, sales/marketing, and ops leadership Gives top-line visibility that AS400 screens can’t deliver
Retlia Drilldown Tools Self-serve filters, breakdowns, and ad hoc question support Empowers teams without needing RPG or SQL skills

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How to Integrate AS400 Data

Smooth integration of AS400 data requires careful planning. Industry expert Laura Hamway notes, "Most of the frustration that I’ve been hearing over the past 20 years is that the reporting in the packaged ERP systems is not sufficient". According to Dean, “The most significant challenge is not the integration itself, but the cultural shift needed. Teams need to understand how to handle and use data in new ways, without relying solely on the AS400’s operational processing."

Here are the key steps:

  1. ETL Process Setup
    Use modern ETL tools designed for IBM i systems to simplify data transfers. For instance, IBM Db2 Web Query for i includes built-in ETL features that handle data cleaning and consolidation while maintaining security. And Matillion has a out-of-the-box connector to AS400I series.
  2. Security Measures
    Leverage IBM i’s native security features, like user authentication, access controls, and audit trails, to safeguard data during the integration process.
  3. Data Mapping
    Align AS400 data structures with the warehouse schema to ensure the information is accurate and usable, to ensure accurate data mapping, and to avoid discrepancies.

Best Practices for Integration

A phased approach works best when integrating data, ensuring the process aligns with your team’s capacity.

Project Management Tips:

  • Break the project into smaller, manageable phases.
  • Prioritize business-critical data first. Getting key data sources for an Executive KPI dashboard is a great place to start.
  • Set up clear validation steps to verify data accuracy, and accurate discovery of data.
  • Document every integration point for future reference.

Technical Tips:

  • Keep IBM i systems updated to maintain performance.
  • Use automated error checks and quality monitoring tools.
  • Establish recovery protocols to handle any issues.

This structured approach connects legacy AS400 data with modern BI tools, paving the way for actionable insights that can drive retail success. By following these steps, your data becomes a powerful resource for making informed decisions.

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Data Security and Management

While ensuring data accessibility, prioritize strong security measures. A structured approach to data governance should include:

  • Access Control: Use role-based access permissions and maintain audit logs to track data access and changes.
  • Backup Procedures: Schedule regular backups to safeguard your data.
  • Compliance Documentation: Keep detailed records of security protocols and access policies.

Consider using the DataMigrator ETL Extension to automate data preparation tasks while maintaining high levels of accuracy. Snowflake also includes top of the line security features such as object level access controls.

To further enhance security, follow these steps:

  1. Data Classification: Sort data by sensitivity and importance to determine the right security measures for each category.
  2. Monitoring and Maintenance: Perform regular system checks and updates to maintain data integrity and system performance.
  3. Training and Documentation: Train your team on the new tools and security protocols to ensure smooth adoption.

Mid-Size Retail Solutions

Data warehousing solutions have proven to deliver clear benefits across several performance areas:

Performance Area Key Impacts
Promotional Analysis Better tracking of campaign ROI
Vendor Management Improved monitoring of supplier performance
Customer Analysis Greater insight into purchasing behaviors
Market Segmentation More precise targeting of customer groups

The move to real-time intelligence is reshaping retail operations by enabling:

  • Predictive Analytics: Identifying future demand trends and AI applications
  • Real-Time Decision Making: Providing instant access to critical data across all levels of the organization

Modern browser-based dashboards now offer customized views tailored to different roles, delivering enterprise-grade features without the usual complexity of implementation.

Research shows that retailers using data warehousing solutions outperform in areas like promotional effectiveness and customer analysis. These tools help organizations turn AS400 data into actionable insights, streamlining daily operations and decision-making processes.

These advancements position mid-size retailers for ongoing modernization and strategic growth.

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Conclusion: Modernizing AS400 Data with a Data Warehouse

Bringing AS400 data into modern data warehousing and BI tools can greatly improve efficiency for mid-size retailers. Fortegra‘s experience illustrates this shift perfectly. Eddie Urfer, Director of Data Analytics at Fortegra, highlights how modern tools have transformed their operations:

"We have to look at return on investment in everything we do. If we were using a toolset that required three programmers to do what one business user can do with a data warehouse, then that return would no longer be there."

This shift into modern data warehousing and BI delivers several operational improvements:

Area of Impact Operational Benefits
Data Access Easier querying and reporting for non-technical staff
Scalability Better handling of growing data demands
Security Reduced risk of user errors
Decision Making Faster access to actionable insights
Cost Efficiency Lower IT dependency and maintenance expenses

Retailers looking to modernize should focus on building detailed business plans that address both current and future needs. This ensures they retain the reliability and security of AS400 systems while gaining flexibility and reducing costs. By adopting modern data warehousing solutions, retailers can meet changing customer demands and market trends while safeguarding their existing investments. This approach strengthens their ability to scale, improves decision-making, and enhances operational security.

FAQs

What steps can mid-size retailers take to seamlessly integrate AS400 data into a modern data warehouse?

To ensure a smooth integration of AS400 data into a modern data warehouse, mid-size retailers should focus on a few key areas:

  • Streamlined Data Management: Use a robust data warehousing solution to consolidate, validate, and simplify your data. This reduces errors and ensures consistency.
  • Scalability and Growth: Choose a platform that can adapt to your growing data needs, ensuring long-term flexibility as your business expands.
  • Data Security: Safeguard your information by implementing a data warehouse with user access controls and aligning with IBM i security protocols.
  • Get Retlia: Its the modern data warehousing and BI solution tailored to mid-size retail, and quickly compatible with AS400.

By prioritizing these steps, retailers can unlock the full potential of their AS400 data, transforming it into actionable insights for better decision-making and operational efficiency.

How can business intelligence tools help mid-size retailers unlock the full potential of their AS400 data?

Business intelligence (BI) tools empower mid-size retailers to transform legacy AS400 data into meaningful insights that drive smarter decisions. By integrating AS400 data into modern BI platforms, retailers can create interactive reports, visualize trends, unlock teams across the business to create self-service reporting, and identify opportunities for growth and efficiency.

These tools simplify complex data, automate report generation, and deliver insights in user-friendly formats, reducing reliance on IT teams. This enables retail businesses to optimize marketing strategies, improve inventory management, and gain a competitive edge in a rapidly evolving market.

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