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                    [post_content] => 
The BI Disconnect: Why Your ERP and Power BI Aren't Truly Connected

You've invested heavily in a powerful ERP (Enterprise Resource Planning) system and the market-leading Power BI platform. Your teams are eager to harness data-driven insights to transform how your organization operates. Yet despite these investments, your analysts are still drowning in manual data exports, endless spreadsheet reconciliations, and heated debates over which department's numbers are actually correct. 

Sound familiar? 

The problem isn't your technology, it's the invisible language barrier between them. Every major ERP system, whether it's JD Edwards, Viewpoint Vista, or NetSuite, speaks its own unique dialect. These systems store critical business information in cryptic transactional data structures, non-standard formats, and application-specific logic that generic BI connectors simply can't interpret. A standard connector can move data from point A to point B, but it can't translate what that data actually means. 

The result? Raw, unusable data floods into Power BI, defeating the entire purpose of your analytics investment. Your finance team sees numbers that don't reconcile. Your operations managers can't trust the inventory figures. Your IT department is stuck building custom solutions that take years to complete and cost hundreds of thousands of dollars…or more. 

There's a better way. Application Intelligence serves as the expert translation layer that solved the BI paradox: transforming your ERP's cryptic language into analysis-ready insights and unlocking the true potential of your Power BI investment. 

 

Defining Application Intelligence: It's Expertise, Not Just a Connector 

 

Application Intelligence is fundamentally different from a basic data connector. It's the capability to decode and enrich data from core enterprise applications by embedding decades of domain-specific expertise directly into your analytics model. Think of it as the difference between receiving a document in a foreign language versus receiving that same document professionally translated with cultural context and business nuance intact. 

While a generic connector provides a pipe to move data, Application Intelligence for analytics provides the intelligence engine that transforms, standardizes, and applies sophisticated business logic—work that would otherwise consume months or years of expensive custom development. The alternative is hiring technology consultants who don't understand your ERP's underlying structure which can lead to ongoing costly projects with inconsistent results. 

Steve Schmidt, Business Intelligence Architect at Washington Companies, learned this lesson the hard way. After two failed attempts with premier Microsoft partners over a year and a half, he discovered the core problem: "The partners were tech experts but lacked deep domain knowledge of the source application (JD Edwards ERP)." Without that embedded application expertise, even the most skilled consultants struggle to deliver reliable results. 

To illustrate the depth of expertise required, consider the QuickLaunch Application Pack for JD Edwards. It contains over 3,000 pre-defined measures and 2,400+ business-friendly dimensions out of the box. This isn't just a collection of reports, it's the accumulated knowledge of decades of ERP expertise, encoded into an intelligent analytics foundation. This is the scale of intelligence required to truly master an enterprise system and unlock its value for business users. 

 

From Raw ERP Data to Rich Power BI Insights: A Look Under the Hood 

 

To understand how Application Intelligence transforms your analytics capabilities, let's examine the specific challenges that make ERP data so difficult to analyze and how an intelligence-first approach solves them. We'll use our Application Packs as a concrete example to demonstrate these solutions in action. 

 

1. Decoding & Transformation: Making Data Usable 

In Plain English: Your enterprise systems speak a language only IT specialists understand. Application Intelligence automatically translates cryptic database codes, proprietary date formats, and technical jargon into business terms your teams can actually use without requiring any manual interpretation. 

The first challenge with any ERP system is simply making the data comprehensible. ERPs are designed for transactional efficiency, not analytical clarity. This creates three fundamental obstacles: 

 

Translating Cryptic Schemas 

Many ERPs uses technical nomenclature that's meaningless to business users. In JD Edwards, critical business information is stored in tables with names like F0901 and fields labeled GBMCU. Without a translation layer, your finance team would need to memorize that F0901 is the Account Ledger table and GBMCU represents the Business Unit, hardly an intuitive reporting experience. 

Application Intelligence automatically translates these cryptic technical names into intuitive business terms. When your CFO opens a Power BI report, they see "Account Ledger" and "Business Unit", not database codes that require an IT degree to decipher. 

 

Handling System-Specific Data Formats 

ERPs often store data in proprietary formats that standard BI tools can't interpret correctly. JD Edwards, for example, stores dates as Julian date integers rather than standard calendar dates. Numerical values use a unique decimal placement code system that, if misinterpreted, can make million-dollar figures appear as pennies or vice versa. 

Application Intelligence automatically handles these conversions. Julian dates are instantly transformed into standard calendar dates. Decimal placement codes are correctly interpreted to ensure every financial value displays with absolute precision. These transformations happen seamlessly in the background, so your users simply see accurate, ready-to-analyze data. 

 

Interpreting Special Codes 

Business context is frequently hidden behind cryptic system codes. Some ERPs extensively use User-Defined Codes (UDCs) which are internal reference codes that represent everything from payment terms to inventory categories. Without the proper mapping, a report showing payment term code "03" means nothing to your accounts receivable team. 

Application Intelligence automatically joins these code tables and replaces technical codes with meaningful business descriptions. Instead of seeing "03," your AR team sees "Net 30 Days", information they can immediately understand and act upon. 

 

Transforming Complex Structures 

Some systems require sophisticated restructuring to become analysis-ready. NetSuite stores all transactions including sales orders, purchase orders, invoices, and payments in one massive, multi-purpose transaction table. This design is efficient for the ERP system but creates a performance nightmare for analytics. 

Application Intelligence re-engineers these large, multi-purpose tables into structures optimized for high-performance analytics in Power BI. The result is faster query performance and more intuitive data exploration for your users. 

 


2. Enrichment & Business Logic: Making Data Intelligent 

In Plain English: Raw data from your systems doesn't include the calculations and business rules your teams actually need to make decisions. Application Intelligence provides pre-built, validated formulas for all your critical metrics like Gross Profit or Inventory Turnover so your teams can trust the numbers without requiring custom development or constant validation. 

Transformation alone isn't enough. True intelligence requires enriching your data with the business rules and consistent calculations that drive decision-making. 

 

Standardizing Key Calculations 

Raw transactional data from your ERP lacks the key performance indicators your business depends on. Calculating metrics like Gross Profit, Sales Backlog, or Inventory Turnover from scratch requires deep knowledge of which tables to join, what exclusions to apply, and how to handle edge cases correctly. 

Application Intelligence provides pre-built, battle-tested calculations for all critical business metrics. These aren't simple formulas—they're sophisticated measures that account for the nuances and exceptions that exist in real-world operations. Your teams can trust the numbers because the business logic has been validated across hundreds of implementations. 

 

Enabling Multi-Calendar Functionality 

Many organizations need to view data through multiple lenses simultaneously: fiscal calendars, standard calendars, 4-4-5 retail calendars, or custom planning periods. Supporting this flexibility in standard reporting tools requires complex Power BI DAX calculations and careful data modeling. 

Application Intelligence provides robust support for analyzing data across different fiscal and standard calendars simultaneously. Your finance team can compare performance against the fiscal year while operations track standard calendar metrics, all from the same trusted data source. 

 

Supporting Multi-Currency Conversion 

Global enterprises face currency complexity in every transaction. Analytics users operating internationally need dynamic currency conversion to support both local currency reporting for regional managers and consolidated group currency reporting for executives...all from the same data source. 

Application Intelligence features automatic multi-currency conversion, ensuring your reports reflect accurate financial reality whether you're analyzing a single country or comparing performance across a global footprint. 

 

Handling Unit of Measure Conversions 

Manufacturing and distribution organizations constantly deal with products measured in different units across the supply chain. In your ERP, the same product might be purchased by the pallet, stocked by the case, sold by the unit, and reported in equivalent weights or volumes. Calculating true inventory values, cost of goods sold, or shipment volumes requires converting between these different units of measure and doing it incorrectly can make your numbers completely unreliable. 

Application Intelligence features dynamic UOM conversion that automatically translates between transaction units, primary units, and equivalent units. Your purchasing team can analyze costs per pallet while your sales team reviews revenue per unit and your warehouse managers track inventory by case; all from the same trusted data with mathematically accurate conversions applied automatically. 

 

Merging Multiple Data Sources 

Most companies need information from multiple fact tables to get a complete picture of the business.  In the case of construction, to truly understand the cash flow on a project, managers need to see the job cost details alongside the open accounts payable and accounts receivable.  Application intelligence provides for this broad reporting capability.  Furthermore, data from other enterprise systems can be merged to create a single source of truth.  For instance, understanding profitability by customer for construction projects should include job costing from the ERP and also the cost of bidding and acquiring the work, which commonly would come from a Customer Relationship Manager (CRM) system. 

Maybe we can add a Vista specific example regarding blending multiple fact tables to achieve a common report.  The Job Cost perspective uses over 9 fact table sources to create standard Job Costs analytics including Work in Progress (WIP), Actual to Projected, Backlog, Cost & Billings in Excess, etc.  This could go into the Partitioning Large Fact tables section too.  But the application intelligence needs to know how & where the data is stored. 

 

3. Governance and Scalability: Preparing to Evolve with Your Business 

In Plain English: Your analytics platform needs to grow with your business and keep your data secure. Application Intelligence automatically handles user permissions, adapts when you upgrade your enterprise systems, and efficiently manages large data volumes so your analytics environment stays reliable and secure as you scale. 

The final dimension of building Application Intelligence in your enterprise analytics platform addresses the long-term health and security of your analytics environment. 

 

Applying Row-Level Security 

In any enterprise, different users need access to different data. Sales managers should see their territories, but not their competitors'. Regional CFOs may need visibility into their division's financials, but not the entire corporations. 

Application Intelligence deploys security policies that ensure users only see data they're authorized to access, with rules that automatically respect your source system's governance model. These security policies are baked into the data model itself, providing governance that scales with your user base without requiring manual intervention.  Application Intelligence supports custom security policies outside of the source ERP, where the security policies vary from the ERP or outside users need expanded secured access the analytics platform. 

 

Supporting Source System Version Updates 

ERPs evolve. Vendors release new versions with enhanced functionality and changed data structures. Without an intelligent layer that accounts for these variations, every system upgrade risks breaking your reports. 

Application Intelligence ensures compatibility with all modern versions of your enterprise application. When your ERP is upgraded, your analytics environment continues to function seamlessly, eliminating the costly cycle of rebuilding reports with every system change. 

 

Partitioning Large Data Tables 

As your business grows, so does your data. Refreshing millions of transactional records every day can strain both your source systems and your reporting infrastructure, leading to failed refreshes and outdated dashboards. 

Application Intelligence implements incremental refresh policies by intelligently partitioning large fact tables. This ensures faster data updates while reducing the load on your source systems. Only the changed data is refreshed, not the entire historical archive—keeping your reports current without compromising performance. 

 

The Payoff: Accelerated Value for Every Business Leader 

 

These deep technical capabilities translate directly into tangible business outcomes that matter to every executive stakeholder. 

 

For IT Leaders: Dramatically Accelerate Time-to-Value 

Your mission is to deliver technology solutions that enable the business while managing cost and risk. Traditional custom BI projects are the antithesis of this goal as they typically consume massive resources, extend over years, and often fail to deliver value. 

The Washington Companies experienced this firsthand. After a failed two-year DIY project with multiple platinum-level Microsoft partners, they turned to QuickLaunch. The transformation was dramatic: "What had been a failed, two year-long DIY project was completed in just 12 weeks with QuickLaunch." 

(link to recent webinar recording with Steve in this section) 

This acceleration isn't just about speed, it's about redirecting your valuable IT resources from platform building to strategic initiatives that drive competitive advantage. With Application Intelligence handling the heavy lifting of ERP translation and transformation, your team can focus on innovation and generating insights.  

 

For Finance Leaders: Gain Audit-Ready, Trusted Numbers 

Your teams spend countless hours reconciling numbers, investigating discrepancies, and defending the accuracy of reports. Every minute spent on data preparation is a minute not spent on strategic analysis and planning. 

IGI Wax, a leader in the wax manufacturing industry, reduced their AR credit dispute resolution time from 2-4 hours down to just 5 minutes using QuickLaunch-enabled analytics. This 23x productivity improvement freed their finance team to focus on strategic initiatives rather than data firefighting. 

When your finance teams trust the numbers in their reports, because those numbers are generated from validated data and standardized, governed calculations built on Application Intelligence, they can accelerate month-end close processes, respond faster to board inquiries, and spend more time on analysis that drives profitability. 

 

For Operational Leaders: Convert Complexity into Action 

Your supply chain, manufacturing, and project management teams operate in the details. They need visibility into inventory positions, production efficiency, project costs, and resource utilization information that's trapped in the transactional depths of your ERP. 

Application Intelligence converts complex operational data into actionable insights. Pre-built, standardized calculations for metrics like Inventory Turnover give your operations managers the KPIs they need to optimize processes and improve performance. When an operations manager can instantly see which products are moving slowly or which projects are trending over budget, they can intervene before small issues become major problems. 

One manufacturing client implemented QuickLaunch and within 10 weeks identified $1.2M in inventory optimization opportunities, opportunities that were invisible when their data was locked in cryptic ERP tables. 

At IGI Wax, once JD Edwards Application Intelligence was built into their unified analytics platform which connected ERP and manufacturing systems, they applied machine learning and AI to identify optimal settings that reduced manufacturing waste from 8% to 4%, directly increasing profit by $8-10 million per year. This breakthrough was only possible because Application Intelligence had created the clean, unified data foundation required for advanced analytics. 

 

Beyond Translation: Application Intelligence as Part of Your Future-Ready Foundation 

 

Application Intelligence isn't just a translation tool, it's the cornerstone of a complete enterprise analytics platform that unifies your data ecosystem and future-proofs your investment. 

 

The Integrated Platform Approach 

Application Intelligence works as part of QuickLaunch's comprehensive platform to deliver unified enterprise analytics: 

    
 	
  • Application Intelligence decodes complex ERP, CRM, and operational system structures into business-ready insights 
    • 



    
 	
  • Centralized Data Lakehouse Foundation unifies information across your entire technology ecosystem into a single source of truth 
    • 



    
 	
  • Pre-built Application Packs deliver thousands of pre-configured measures and business-friendly dimensions 
    • 



    
 	
  • Enterprise-grade methodologies ensure governance, security, and scalability are built in from day one 
    • 


Together, these capabilities eliminate the fragmented, departmental approach that creates new data silos. Instead, you establish a unified foundation where every system speaks the same language and every department works from the same trusted data. 

 

Built for Tomorrow's Innovations 

The intelligent data foundation you build today becomes your platform for advanced analytics tomorrow. 

AI and Machine Learning Ready: When your data is already decoded and standardized, you can deploy predictive models, optimization algorithms, and automated insights without extensive preparation. 

Adapts as Technology Evolves: Application Intelligence ensures compatibility across modern system versions, so upgrades don't break your reports. When you acquire companies or integrate new systems, the same intelligent approach maintains consistency while expanding your data foundation. 

Scales Without Rebuilding: As business needs change, your platform grows with you from basic reporting to predictive analytics to AI-powered automation, all built on the same trusted foundation. 

Organizations that move faster than their competition don't have better tools, they have better foundations. Application Intelligence, as part of a complete analytics platform, provides the strategic infrastructure that enables continuous innovation and compounds in value over time. 

 

Stop Translating Your Data. Start Using It. 

The path to becoming a data-driven organization isn't paved with data connections, it's built on data intelligence. A simple pipe between your enterprise systems and Power BI leaves you with the same cryptic, unusable data you started with, just in a different location. True value requires the expert translation layer that Application Intelligence provides as part of a complete platform that unifies your entire enterprise. 

The most successful organizations aren't the ones with the most data, they're the ones who can turn data into insight, and insight into action, faster than their competition. Application Intelligence, combined with QuickLaunch's unified analytics platform, helps them do it in weeks instead of years. 

The path to becoming a data-driven organization isn't about wrestling with your systems; it's about making them speak the same language. 

 

Ready to Unlock the True Potential of Your Enterprise Data? 

 

Whether you're struggling with JD Edwards, Viewpoint Vista, NetSuite, or managing data across multiple systems, Application Intelligence is your bridge from complexity to clarity. 

 

Next Steps: 











Discover how Application Intelligence transforms analytics for your specific systems








 










Watch how QuickLaunch can transform your cryptic data into clear insights








 









Ready for the Complete Picture?


Download our comprehensive guide: Connect. Centralize. Conquer: A Blueprint for Achieving a Unified Enterprise Analytics Platform to understand the full journey from fragmented systems to unified enterprise intelligence.

 		





 

 
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                    [post_content] => You've invested millions in implementing JD Edwards. Your team can process invoices, manage purchase orders, and track inventory like clockwork. But when your CFO asks for last quarter's profit margins by business unit, or a project manager needs real-time cost analysis, everything grinds to a halt. Sound familiar? You're not alone. JD Edwards excels at what it was designed for—capturing transactions with precision. But when it comes to getting meaningful intelligence back out, the system often becomes the biggest roadblock. The problem isn't your team or your budget. The issue is fundamental: JD Edwards reporting was never built for modern, self-service analytics. Let's explore why this happens, what it’s costing your business, and most importantly, how to build a scalable, future-ready analytics solution on top of your JDE investment without ripping and replacing your ERP.

 

The Real Problem: When Great ERP Meets Terrible Reporting

 

Most JD Edwards implementations follow a predictable pattern. The system works beautifully for daily operations—your warehouse staff can process shipments, accounting can handle invoices, and procurement can manage purchase orders. Everything runs smoothly until someone asks a seemingly simple question: "What were our gross margins by product line last month?" That’s when you discover the harsh reality. Your business analyst disappears for three hours, exports data to multiple spreadsheets, and returns with a report that nobody quite trusts because the numbers don't match what finance reported last week. This isn't a training problem or a user error. It's a structural limitation that stems from how JD Edwards organizes and stores information.

 

The 5,000-Table Nightmare

JD Edwards contains approximately 5,000 tables with cryptic names that make sense to the system but are indecipherable to humans. Your business unit master table isn't called "Business_Units"—it's labeled F0006. The object account field isn't named something logical like "GL_Account"—it's called GBOBJ. Imagine trying to explain your company's financial performance using a language where every important term is replaced with seemingly random codes. That's exactly what your analysts face every day when working with raw JD Edwards data. The dates present another challenge. While the rest of the business world uses standard Gregorian dates, JD Edwards stores dates in Julian format. Your December 31st becomes 120365, creating an additional translation step for every time-based analysis. Even the numerical data needs cleanup. Amounts and units lack proper decimal precision, making financial calculations prone to rounding errors. User-defined codes that represent critical business segments—like your sales territories or product categories—appear as generic code values rather than meaningful descriptions.

 

The Hidden Costs of Broken JD Edwards Reporting

 

When reporting doesn't work smoothly, the costs compound quickly across multiple areas of your business. Here are some of the most common costs we see companies dealing with:

 

Productivity Drain

Your most skilled analysts spend an inordinate amount of their time on data preparation instead of actual analysis. These professionals, who should be uncovering insights and driving strategic decisions, become glorified data janitors. They manually extract information from multiple systems, massage it in spreadsheets, and hope everything aligns correctly. This represents a massive misallocation of talent. Instead of leveraging their expertise to identify growth opportunities or operational efficiencies, your team burns valuable hours fighting with data formats and reconciling conflicting numbers.

 

Decision-Making Delays

Speed matters in business. When your operations manager can't quickly assess supply chain performance across regions, minor disruptions cascade into major problems. When your CFO lacks real-time visibility into cash flow across business units, conservative decisions replace aggressive growth investments. The time between asking a business question and getting a reliable answer directly impacts your competitive position. While you're waiting for reports, competitors with better data infrastructure are already adapting to market changes.

 

Technology Sprawl

IT departments often respond to reporting frustrations by implementing multiple point solutions. Finance gets their preferred business intelligence tool, operations chooses something different, and marketing selects a third option. Soon you're managing a complex ecosystem of overlapping applications, each requiring separate licenses, maintenance, and support. This technological fragmentation creates additional integration challenges while inflating your software costs. Your IT team spends time maintaining multiple systems instead of focusing on strategic initiatives that drive business value.

 

Erosion of Trust

Perhaps most damaging is what happens when teams lose confidence in the numbers. When sales reports and finance reports tell different stories about the same quarter, skepticism spreads throughout the organization. Every dashboard gets questioned, every analysis gets challenged, and data-driven decision making becomes impossible. Teams revert to gut feelings and departmental spreadsheets because those feel more trustworthy than official reports. This destroys the foundation needed for effective business intelligence and strategic planning.

 

The Architecture of a Modern Solution: Transforming JDE Data

 

Fixing JDE reporting no longer requires building a clunky, traditional data warehouse. The solution is a modern, integrated analytics ecosystem that transforms your raw JDE data into a trusted, accessible, and AI-ready asset. This involves three key layers, delivered by QuickLaunch Analytics.

 

Connect: Automated Data Pipelines

The first step involves establishing reliable, automated connections between JD Edwards and your analytics infrastructure. Rather than manual exports and imports, the QuickLaunch Foundation Pack implements systems that continuously synchronize data with minimal intervention. These automated pipelines eliminate the manual bottlenecks that slow down reporting, ensuring your analytics environment stays current with operational changes. It also allows you to connect and integrate data from your other critical systems, like CRM and HR platforms, to break down silos.

 

Centralize: A Governed Data Lakehouse

Once you have reliable data flows, the information is centralized in a modern cloud platform like Databricks or Microsoft Fabric. This is the core of your new analytics ecosystem: a governed Data Lakehouse that serves as the single, scalable repository for all your enterprise data. Here, the raw, cryptic JDE data is transformed, cleaned, and organized. This foundational layer is not only optimized for today's analytics but is also designed to be the launching point for future AI and machine learning initiatives, turning your data into a true enterprise asset.

 

Conquer: Application Intelligence and Self-Service BI

This is where the cryptic data becomes business intelligence. The QuickLaunch JD Edwards Application Pack is a pre-built solution that sits on top of the Lakehouse, embedding decades of JDE-specific expertise into an enterprise-grade analytics model. It instantly translates the 5,000-table nightmare into an intuitive business structure. The Application Pack delivers a robust Power BI semantic model with over 3,000 pre-defined measures and 2,400 business-friendly dimensions, complete with standardized calculations and financial hierarchies. This semantic layer acts as the "one version of the truth," enabling true self-service analytics. Business users can finally explore data, create their own reports in Power BI, and get trusted answers to their questions without needing a technical translator.

Implementation: From Concept to Results in Weeks, Not Years

The journey from broken JD Edwards reporting to effective business intelligence doesn't require a massive, multi-year system overhaul. A modern, accelerator-based approach delivers value at a pace that legacy projects simply can't match. A typical QuickLaunch implementation deploys the Foundation Pack and the JDE Application Pack in a structured, phased approach that takes just 8-12 weeks. This modular strategy focuses on delivering a solid technical foundation first, then layering on the application-specific intelligence to provide immediate business value. Instead of building everything from scratch, you are leveraging a production-ready solution that encapsulates thousands of hours of development and domain expertise. This dramatically reduces implementation time, cost, and risk compared to a custom-built solution, which often takes 1-2 years.

 

Measuring Success: Beyond Better Reports

When JD Edwards reporting works properly, the benefits extend far beyond prettier dashboards and faster queries.

    
 	
  • Operational Efficiency: Analysts spend less time preparing data and more time generating insights. Managers get answers to business questions in minutes rather than hours or days. Decision-making processes accelerate because reliable information is readily available. A process that once took hours to resolve can now take minutes.
    • 
 	
  • Strategic Agility: With proper data infrastructure, organizations can respond quickly to market changes, identify emerging opportunities, and adjust strategies based on real-time performance data. The lag time between business events and management awareness shrinks dramatically.
    • 
 	
  • Innovation Enablement: Clean, accessible data in a Lakehouse creates the foundation for advanced analytics initiatives. Machine learning algorithms, predictive models, and artificial intelligence applications become feasible when they can access high-quality, well-structured information. Organizations that solve their data fragmentation problems position themselves to leverage emerging technologies while competitors struggle with basic reporting challenges.
    • 


 

Moving Forward: Your Next Steps

Fixing JD Edwards reporting isn't just a technical project—it's a strategic business initiative that touches every aspect of your operations. The cost of continuing with broken reporting processes compounds over time, while the benefits of a proper business intelligence infrastructure grow exponentially. Start by auditing your current situation. How much time do your analysts spend on data preparation versus analysis? How long does it take to get reliable answers to critical business questions? What opportunities might you be missing due to delayed or incomplete information? Consider the total cost of your current approach, including redundant software licenses, analyst productivity losses, and missed business opportunities. Compare this against the investment required to implement a modern, accelerated solution. Most importantly, think strategically about where your organization needs to be in the next 2-3 years. Competitors who solve their data challenges now will have significant advantages in leveraging AI and advanced analytics to drive business results.

 

Frequently Asked Questions

 

Can we fix JD Edwards reporting without disrupting our operational systems? Yes, absolutely. Modern approaches to JD Edwards reporting work by creating separate analytical environments that don't impact your production ERP system. The QuickLaunch solution operates alongside your existing systems without requiring modifications to the source applications. Our automated data synchronization is designed to keep your analytical systems current without affecting operational performance.

How long does it typically take to implement better JD Edwards reporting? With QuickLaunch, a full enterprise implementation is completed in just 8-12 weeks. This is significantly faster than a traditional, custom-built data warehouse project, which typically takes 1-2 years. Our approach uses pre-built components and proven methodologies to accelerate every phase, from data pipeline configuration to deploying business-ready reports.

How is this modern Lakehouse approach different from a traditional data warehouse for JD Edwards reporting? A traditional data warehouse is often rigid, expensive to build, and primarily designed for structured data from one system. A modern Data Lakehouse, which is the heart of the QuickLaunch Foundation Pack, is far more flexible and scalable. It's designed to unify all your enterprise data—from ERPs, CRMs, and other sources—in one place. This not only provides a comprehensive view of the business but also creates the necessary foundation for advanced analytics like predictive modeling and AI, which is a key limitation of older architectures.
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