Managed Data Services

Reliable Data. Ready for Reporting.

We take the recurring data work behind your reports—extracting, cleaning, reconciling, and maintaining data from your ERP and operational systems—so your team gets trusted, reporting-ready information without building an internal data engineering team.

  • Flat-rate managed service

  • No hourly consulting meter

  • No large platform transformation required

  • Start with the data that matters most

Your systems already have the data. Getting it ready is the hard part.

Many organizations have invested in ERP and operational systems, yet management reporting still depends on exports, spreadsheets, manual cleanup and one person who knows how the numbers fit together.

Recurring reports require manual ERP exports and spreadsheet cleanup.

  • Different reports produce different answers for the same business question.

  • Inventory, sales, finance or operational data must be reconciled before anyone trusts it.

  • Reporting projects stall because the underlying source data is inconsistent or incomplete.

  • The organization needs better data but cannot justify hiring a full internal data team.

Managed service economics. Enterprise-grade ETL thinking.

Scalar Solutions' managed data service is built on long-standing experience designing and operating ETL, data integration, reporting and modern data-platform solutions.

Our background spans traditional database and ETL environments through cloud-based data engineering and analytics platforms. That experience matters because reliable managed data is not simply about moving records from one system to another — it requires understanding source behavior, transformations, reconciliation, failure handling and downstream reporting dependencies.

20+ years of data movement and integration

Experience across SQL-based integration, ETL/ELT, enterprise reporting, data warehousing, cloud data engineering and modern analytics architectures.

Operational reliability over tool complexity

We use the architecture appropriate for the client. The goal is not to sell a large platform; it is to produce dependable data that the business can actually use.

Senior technical oversight

Managed services are grounded in hands-on data engineering and platform experience rather than generic outsourced support.

A straightforward way to take recurring data work off your team.

01 CONNECT

Extract

Connect securely to ERP, databases, APIs, operational applications or scheduled files.

02 PREPARE

Clean

Standardize formats, normalize values, remove duplicate conditions and apply agreed business rules.

03 VERIFY

Validate

Check completeness, reconcile key measures and identify unexpected data conditions.

04 OPERATE

Monitor

Run and monitor scheduled processing so the data remains usable as source systems change.

05 CONSUME

Deliver

Provide reporting-ready data for Excel, Power BI, dashboards, automation or other downstream uses.

Different systems. Familiar data problems.

We focus on operational environments where valuable business data exists, but obtaining a consistent reporting view still requires too much manual work.

Manufacturing

When production, inventory, purchasing and finance live in the ERP, leadership still shouldn't have to wait for someone to rebuild the numbers in Excel.

Inventory does not reconcile cleanly.
Operations sees one quantity while accounting or another ERP report shows something different.

Sales and backlog visibility is delayed.
Open orders, shipped orders and revenue are spread across reports and require recurring spreadsheet work.

Production reporting is assembled manually.
Work orders, output, scrap, downtime or material usage have to be exported and reshaped before managers can use them.

Purchasing decisions rely on imperfect data.
POs, receipts, inventory and supplier information do not come together in a consistent management view.

Managed outcome: clean, validated sales, inventory, purchasing and production data that stays ready for recurring reporting and analysis.

Wholesale & Distribution

A distributor can have an ERP, WMS and accounting system and still struggle to answer basic questions about inventory, margin and order performance without manual reconciliation.

Inventory availability is difficult to trust.
Warehouse balances, committed stock, receipts and ERP quantities do not line up cleanly.

Customer and SKU reporting is inconsistent.
Different exports use different product, customer or location structures.

Margin reporting takes manual work.
Sales, product cost, freight, discounts and returns have to be combined before true margin can be analyzed.

Purchasing is driven by disconnected reports.
Demand, available inventory, open POs and supplier history are difficult to consume together.

Managed outcome: dependable order, inventory, product, supplier and margin data that is ready for management reporting.

Healthcare Services

Healthcare operators often have the information they need — but it is fragmented across scheduling, billing, practice-management, financial and administrative systems.

Utilization reports require multiple exports.
Provider, location, appointment and scheduling data need to be combined before operations can see capacity and utilization.

Location reporting lacks consistency.
Multi-site organizations spend time standardizing providers, locations, services or administrative categories.

Revenue and operational activity are disconnected.
Finance and operations work from different reports that must be reconciled manually..

Recurring executive reporting is labor-intensive.
Staff rebuild the same operational workbook every week or month.

Managed outcome: structured, consistently refreshed operational and business datasets for reporting, analysis and management decision-making.

Construction & Specialty Contractors

Job profitability can change quickly, yet project, accounting, labor and purchasing data frequently sit in different systems and reach management too late.

Job-cost reports lag the work.
Committed cost, actual cost, labor and billing information must be reconciled before the project picture is accurate.

Labor data takes too long to consolidate.
Time, crew, project and payroll information require repetitive cleanup before useful reporting.

Project and accounting systems disagree.
Operations and finance use different versions of project status and financial performance.

Predictable cost without hiring a data engineering team.

Managed Data Services are structured around a defined scope and flat recurring service fee rather than open-ended hourly consulting.

We start with the business data domains that matter most and expand only when there is a clear operational need. This keeps the service practical for organizations that need reliable data but do not need a large enterprise data program.

Pricing is based on the overall data process being managed—including source-system access, integration complexity, refresh requirements and the agreed business outputs. We do not price by individual file, feed or pipeline. Specific pricing is provided after a short review of the environment.

WIP reporting is spreadsheet-dependent.
Controllers spend significant time extracting and manipulating data for monthly review.

Managed outcome: cleaner project, job-cost, labor, purchasing and financial data for recurring operational and financial reporting.

Flat-rate managed service

Designed to be competitive with the true cost of recurring manual reporting, ad hoc consulting, or building an internal data function.

  • Defined data domains and deliverables

  • Scheduled extraction and processing

  • Data cleanup and transformation

  • Validation and reconciliation

  • Monitoring and maintenance

  • Reporting-ready output

Common questions

  • Scalar takes responsibility for a recurring business-data process—from extraction and transformation through validation, monitoring and delivery—so your team receives dependable reporting-ready data without operating the underlying engineering process.

  • In many cases, yes. Access may be through read-only database connectivity, APIs, scheduled files, SFTP or other approved extraction methods.

  • Not necessarily. The service is designed to use the minimum architecture required for the outcome. Existing systems remain in place unless there is a specific reason to change them.

  • Yes. Outputs can be structured for Excel, Power BI, dashboards, analytics, automation or other agreed downstream uses.

  • Yes. Real operational data rarely comes from one perfectly structured source. A single reporting process may depend on SQL tables, CSV files, Excel workbooks, SFTP feeds or APIs. Scalar can combine those inputs into a standardized, validated output rather than requiring the business to manage each integration independently

  • Yes. A managed process may involve data from ERP databases, APIs, SFTP locations, scheduled files, spreadsheets and other operational sources. Scalar can manage the extraction, transformation, business rules, reconciliation, delivery and ongoing monitoring as one coordinated data process. We scope the overall environment rather than pricing every individual file, feed or technical pipeline separately.

  • For many small and mid-sized organizations, it can be. If the primary need is maintaining recurring integrations, preparing reporting data, reconciling business information and keeping existing pipelines operating reliably, building an internal data engineering position may be more capacity than the organization needs. Managed Data Services provides access to experienced data engineering capability without creating another full-time technical role.

  • Not necessarily. Scalar starts with the business requirement and the systems you already have. Where practical, we use existing database, integration and cloud capabilities rather than introducing another platform simply to deliver the service. If additional technology is genuinely required, we review the options and associated cost before implementation.

  • The service is designed for organizations that need dependable data engineering but may not need a dedicated engineering team. Instead of separately funding a data engineer, ETL tooling, monitoring infrastructure and ongoing support, Scalar manages the agreed process under a predictable service model. This can be particularly effective when the workload is important and recurring but not large enough to justify a full internal team.

Review My Data Process

Show us one recurring ERP export, reporting process or dataset your team is manually preparing today. We’ll review the current process and determine whether it is a good fit for a managed approach.