Escape the data maze: Your SAP data journey from source to insight

Behind every smart decision lies accurate, up-to-date data that’s correctly formatted and available at the right time. If your organization uses SAP, the stakes are high: Business-critical operations rely on synchronized data flows across ERP systems, analytics platforms and cloud infrastructure.

SAP environments are more powerful than ever, but they’re also more flexible and open to work with the latest technologies. This inherently adds complexity. Many organizations are operating hybrid landscapes with SAP S/4HANA on-premises or in the cloud, SAP Business Technology Platform (BTP) connected to non-SAP apps and tools, external data lakes or warehouses, third-party analytics platforms and a growing number of integration points and APIs. 

Yet, many enterprises are discovering the hard way that it’s not the limitations of integration holding them back; it’s a lack of true orchestration.

Managing data movement across this ecosystem is no longer a task for isolated scripts or point-to-point integrations. It requires an automation fabric that ensures your data flows securely and reliably.

Luckily, much of what you need to achieve this already exists — within your environment, your tech stack and your team. But it needs to come together to run autonomously across all your applications, processes and data. That’s where a purpose-built orchestration layer adds transformative value to SAP data ecosystems.

Where data pipelines break down

Modern SAP landscapes are hybrid by design. You might be running S/4HANA on-prem with SAP BTP extensions in the cloud. You might be feeding into Snowflake for advanced analytics or using Microsoft Power BI for dashboards. You may even leverage tools like Azure Synapse, Databricks or Informatica Cloud. This sprawl creates complexity, and complexity creates friction.

Let’s walk through some common data-related challenges you could be experiencing.

Fragmented scheduling leads to inconsistent data

Without centralized orchestration, teams use whatever’s available: cron jobs, external schedulers, hand-written scripts, etc. This leads to mismatched timing and unreliable dependencies. For example, your sales numbers in Power BI don’t align with your inventory figures in SAP S/4HANA because the data pipelines refresh on different cadences — or worse, silently fail.

Disparate systems often mean data stays siloed, which causes reporting to be inconsistent. That’s a consequence of not having a single pane of glass from which to manage and monitor your data flows. Without a centralized scheduler that acts as an orchestration engine, systems can’t depend on one another effectively, leading to gaps and overlaps. 

Manual processes contribute to high error rates

Manual data entry and transfers are still too common, especially when you’re bridging SAP with non-SAP systems like partner portals, pricing tools or local data repositories. Each touchpoint adds risk. 

If a pricing update comes in from an external vendor and someone delays or incorrectly inputs it manually into files that update SAP Business Warehouse (BW), your customers might see the wrong price and your support lines could light up.

Lack of timely visibility forces reactivity

Outdated data is almost worse than no data. If dashboards and reports pull from systems that haven’t been synced properly, your leadership team will make calls based on stale information. 

Let’s say SAP Analytics Cloud shows margin erosion in one product line, but you don’t have up-to-date access to supply chain or POS data. The root cause will remain unclear, delaying response and ballooning the impact of negative outcomes. 

Difficulty tracking data lineage

When something goes wrong, how fast can you trace it back to the source? In many cases, it takes hours or days of manual investigation across teams and tools. 

When a financial report in SAP Analytics Cloud flags missing revenue, but the issue started in a data ingestion workflow running through Azure Synapse or SAP Datasphere, you’re stuck chasing ghosts if you have no orchestration layer.

Missing automation, missed opportunities

This is perhaps the most widespread and costly issue: systems and teams doing the right things but in isolation. It causes pipelines to stall and dependencies to be overlooked. In other words, you get stuck in a reactive loop.

Your data may be moving on rigid schedules instead of when it’s actually available. Critical workloads like Databricks clusters or EC2 instances might stay running long after they need to. Or, your Power BI might be refreshing every hour instead of being triggered by actual data loads. All of these have the potential to create both lag and waste.

A real picture of end-to-end orchestration across your data ecosystem

What does a centralized, intelligent workload automation (WLA) platform that unifies and orchestrates data movement across SAP and non-SAP systems look like?

• Fluid integration with everything from SAP S/4HANA to cloud-native tools like Snowflake, Databricks, Azure and Google Cloud
• Automated data flow — no more relying on email alerts or batch jobs
• Real-time alerting and proactive error handling to prevent pipeline issues before they impact the business
• Centralized observability so you can see and track data lineage and process status across the entire landscape

With these capabilities, you’re not just fixing technical issues. You’re enabling business agility. You’re giving your teams trustworthy data to act on and reducing the cost and risk of digital operations. Essentially, you’re building a future-ready enterprise.

This automation fabric is powered by a secure, cloud-native job scheduling solution that runs completely outside your SAP environment but is deeply integrated with it. That means no additional load on SAP systems, no lost visibility and no vendor lock-in.

Why this matters for you now as an SAP user

Whether you’re deep into a RISE with SAP transformation or just beginning to connect SAP to cloud analytics and data platforms, orchestrating your data movement must be a strategic priority. SAP Business Data Cloud (BDC) offers incredible promise for unifying enterprise data and applying AI and analytics at scale.  But like any system, BDC is only as good as the data pipelines feeding into it.

And for most enterprises, those pipelines touch systems far beyond SAP: Snowflake, Databricks, Power BI, Azure Data Factory, ServiceNow, Kubernetes, even legacy platforms. And this isn’t just an IT issue. Your Finance team needs timely close processes and readily available data that supports compliance. Your Operations team has to keep processes flowing without waste. Your Customer Support team needs a 360-degree customer view to ensure service and satisfaction.

Even your future initiatives, like training and implementing AI models, depend on clean, accurate and complete data that’s reliable and doesn’t cause hallucinations.

What’s at stake? Cost, trust and transformation

End-to-end data pipeline automation is more than just convenient. RunMyJobs by Redwood customers know firsthand how critical advanced WLA via an SAP-partnered solution can be. It helps them handle the real-world complexities of data operations that arise daily for fast-moving enterprises. 

RunMyJobs’ event-driven workflows, conditional logic, alerting, retries, visual no-code design, AI/ML predictive analysis and alerting and other automation fabric-focused features enable:

• Cost savings: Customers have reduced cloud spend by auto-scaling Databricks clusters or shutting down idle EC2 instances via RunMyJobs.
• Faster reporting: Orchestrating SAP-to-Snowflake-to-Power BI flows, for example, keeps you meeting tight SLAs for daily or hourly dashboards without running refreshes that burn compute unnecessarily.
• Better governance: With audit trails, centralized logs and controlled access (e.g., via ServiceNow), RunMyJobs customers meet compliance requirements more easily.
• Reliability for AI: As AI becomes more crucial to drive productivity and efficiency, you need to know that the data it uses is accurate. RunMyJobs uses best-in-class automation practices to secure the data feeding your AI models, orchestrating continuous data flows so their outputs are reliable, unbiased and meet quality standards.

If your data flows matter, then orchestration matters. With RunMyJobs, you can unify your SAP and non-SAP systems into one intelligent, automated, business-aware fabric. You can reduce risk, lower costs and dramatically improve the accuracy and timeliness of your reporting.

Stop thinking in terms of single integrations and start thinking in terms of coordination. Learn how to develop resilient value-chain, data-driven SAP processes and get the most from your SAP solutions with end-to-end automation.