Data platforms that operate themselves, not the team operating them
The average annual cost of poor data quality is $12.9M per organisation. Forty percent of data engineering teams spend more time on reactive incident response than on building new capability. BCS data platform management replaces reactive operations with Symphony automation and deKorvai continuous quality monitoring.
average annual cost of poor data quality per organisation
of data teams spend the majority of time on pipeline fixes rather than new capability
average cloud data platform spend wasted in ungoverned environments annually
Three things BCS does before every other consultancy starts building
Most delivery programmes begin at the solution layer. BCS begins at the evidence layer, measuring what exists before proposing what to build. That sequence is what separates recommendations with a measurable outcome from plans that look credible at presentation and fail in execution.
Measure before designing
deKorvai quality baseline established before any architecture decision is made. Every recommendation is grounded in measured evidence from the current data estate, not assumptions from stakeholder interviews.
Automate from the first sprint
Symphony automation scope identified and embedded in the delivery roadmap during the engagement itself, not proposed as a separate follow-on programme after delivery concludes.
Govern from day one
Anugal access governance and data classification policies are designed as part of the solution architecture and active from the first production dataset, not retrofitted after the platform is in use.
3 reasons enterprise data platform operations break down
Data platform operations failures follow patterns that are predictable and preventable. The common thread is reliance on human-driven responses to situations that should be automated from the first incident category.
Incident response depends on the most experienced engineer available
Platforms without automated incident response runbooks require a senior data engineer to diagnose and resolve every failure. Incident resolution time scales with team availability rather than incident severity. Night-time and weekend failures accumulate SLA debt that compounds when the first engineer available on Monday morning faces three simultaneous pipeline failures that cascaded from a single root cause.
Cost visibility arrives monthly with the cloud bill, not in real time
Data platform costs reviewed monthly rather than governed continuously produce budget overruns discovered after the fact. By the time a monthly cloud bill surfaces an overspend, the workloads driving the cost have run for 30 days. Retroactive optimisation recovers some future spend but cannot recover the cost already incurred, and the root cause is often a workload configuration catchable within the first hour of execution.
Data quality degrades without a monitoring layer that enforces standards
Data quality in production environments degrades continuously when there is no monitoring layer enforcing quality standards at every pipeline run. Source system schema changes, data volume spikes, and upstream process changes introduce quality failures that propagate through the pipeline estate undetected until a business user reports an incorrect report or a model produces an unexpected output.
What the data platform management engagement delivers
Incident categories resolved by Symphony runbooks, not engineers
Symphony automates classified failure patterns — pipeline restarts, quality escalations, and dependency recovery — so engineering teams receive resolution notifications rather than manual pages.
Data quality monitored continuously, not discovered from business complaints
deKorvai runs quality checks at every pipeline execution, surfacing failures within minutes so downstream consumers receive certified data rather than output that has not been validated since initial acceptance.
Cloud spend actively optimised, not reviewed retrospectively
Compute, storage, and query spend are monitored in real time against defined thresholds, with automated alerts and optimisation actions triggered before quarterly review cycles surface the waste.
Platform changes governed through versioned release processes
Configuration changes, pipeline updates, and schema modifications are versioned, staged, and promoted through the same Symphony release workflow used at build, eliminating drift from the first managed change.
Access continuously governed, not reviewed in annual cycles
Anugal flags policy drift as it occurs so role changes, contractor departures, and decommissioned service accounts are addressed on schedule rather than surfaced in the next annual review.
Internal engineering teams focused on new capability, not platform stability
BCS automation maintains the operational baseline, freeing data engineering teams to build new data products and analytics models instead of managing incidents and platform housekeeping.
How BCS manages a data platform from day one of the engagement
BCS platform management engagements begin with an operational baseline assessment and move through five phases to a fully automated managed service with defined SLAs and continuous quality reporting.
Operational Baseline
Assess the current platform state, document existing runbooks and quality configurations, establish deKorvai quality baseline measurements, and identify the operational risks requiring immediate attention.
Automation Gap Remediation
Convert manual operational procedures to Symphony runbooks. Incident categories that repeat are automated in the first 90 days. Routine operations move from engineer time to automated execution.
Quality Monitoring Deployment
Implement deKorvai continuous quality monitoring across all active pipelines. Quality gates, freshness monitoring, and anomaly detection are configured against defined business rules and SLA thresholds.
Cost Governance Activation
Deploy active cost monitoring against agreed budget thresholds. Workloads that breach cost limits trigger automated investigation and optimisation actions before month-end reporting.
Continuous Improvement Cadence
Establish monthly operational reporting, quarterly performance reviews, and a continuous improvement backlog that extends Symphony automation coverage and deKorvai quality coverage as the estate evolves.
What the managed service covers
BCS data platform management covers the full operational scope of an enterprise data platform, from pipeline health through to access governance and cost optimisation.
Pipeline Health Monitoring
Continuous monitoring of pipeline execution status, data freshness, scheduling adherence, and dependency chain health. SLA-gated alerting for pipelines approaching or breaching agreed freshness thresholds.
deKorvai Quality Monitoring
Continuous automated quality checks at every pipeline execution. Completeness, accuracy, and business-rule conformance monitored against defined thresholds. Quality drift detected and escalated before downstream business impact.
Incident Response Automation
Symphony-orchestrated incident response for classified failure categories. Pipeline restart sequences, dependency recovery chains, and escalation workflows executed automatically. Mean time to recovery tracked against SLA for each incident category.
Cloud Cost Optimisation
Real-time spend monitoring against agreed budgets. Compute rightsizing recommendations, storage tier optimisation, and unused resource identification delivered monthly. Query performance tuning to reduce compute consumption on high-frequency analytical workloads.
Performance Tuning
Ongoing query performance analysis, partition strategy optimisation, index management, and caching configuration for the data platform and connected analytical tools. Performance degradation detected before it impacts business reporting SLAs.
Patch and Version Management
Platform component patching, runtime version upgrades, and dependency management executed through governed Symphony release workflows. Test environment validation before production promotion. Patch compliance reporting against platform vendor SLAs.
Access Governance
Anugal continuous monitoring of data platform access against defined access policies. Role drift detection, stale access identification, and contractor access revocation managed on schedule rather than discovered in annual reviews.
Capacity Planning
Monthly capacity utilisation review and growth trend analysis. Compute, storage, and network capacity recommendations aligned to the business data roadmap. Scale-up and scale-down planning before capacity constraints affect performance.
Operational Reporting
Monthly operational reports covering SLA performance, incident trends, quality metrics, cost governance, and capacity utilisation. Executive summaries and engineering-level detail delivered to agreed stakeholder audiences on schedule.
The platforms that keep the data platform operational without manual overhead
Platform Operations Automation
Symphony
Symphony automates routine data platform operations including patching, backup execution, scaling events, and incident response. Operations teams receive governed runbooks at handover rather than a list of manual procedures.
- Scheduled maintenance execution for patching, backup, and certificate rotation
- Incident response runbook automation triggered by platform monitoring alerts
- Scaling event orchestration with dependency-aware sequencing across platform layers
- Operations runbook library built and handed over as tested automation
Platform Health and Data State Monitoring
deKorvai
deKorvai monitors data platform health, pipeline throughput, and data state continuously, surfacing anomalies before they become incidents. Platform teams see the operational intelligence needed to act before SLA breaches occur.
- Continuous platform health monitoring across compute, storage, and pipeline layers
- Pipeline throughput anomaly detection surfaced before SLA breach thresholds
- Data freshness and completeness scoring for managed datasets
- Pre-maintenance state validation confirming platform readiness before procedures run
Platform Access and Privilege Governance
Anugal
Anugal governs privileged access to data platform infrastructure, replacing standing administrative permissions with just-in-time elevation scoped to the active maintenance task. Standing admin permissions are eliminated between maintenance windows.
- Just-in-time privileged access scoped to the active maintenance procedure
- Automated revocation on procedure completion without manual permission cleanup
- Standing admin permission elimination between scheduled maintenance windows
- Contractor access lifecycle controls matching internal operations standards
What makes BCS different from every other data platform managed service provider
BCS has managed SAP Datasphere, Azure, AWS, and GCP data platforms for enterprise clients across manufacturing, financial services, and healthcare. The operational baseline is delivered through Symphony automation and deKorvai continuous quality monitoring, not through a larger on-call team.
Symphony runbooks, not on-call engineers, as the primary incident response
Incident categories that repeat are converted to Symphony runbooks. Organisations stop paying engineer time to resolve incidents that have been resolved the same way 20 times before.
deKorvai catches quality failures before the business does
Continuous deKorvai monitoring runs at every pipeline execution. Quality failures are identified and escalated within minutes, not discovered when a finance director questions a report.
Cost governance is active, not retrospective
Cloud data platform spend is monitored in real time against agreed budgets. Workloads that breach cost thresholds trigger automated investigation before the month ends.
Access governance runs continuously, not annually
Anugal monitors data platform access against defined policies and flags drift at the point it occurs, not at the next scheduled access review.
SAP and cloud expertise in the same managed service team
Enterprises running SAP Datasphere or BW alongside Azure, AWS, or GCP receive managed operations from a single BCS team with no handoff at the platform boundary.
Managed service informed by the platform BCS built or assessed
Where BCS built the platform, the managed service team inherits the architecture context and Symphony runbook foundation. Where BCS takes over an existing platform, operations begin with a platform assessment that establishes the same baseline.
Ready to stop operating data platforms manually?
BCS data platform management replaces reactive incident response with Symphony automation and continuous deKorvai quality monitoring. Book an initial platform assessment to understand what a managed service engagement looks like for the current environment.