Data Engineering
Enterprise
Scale Data Architecture. Control Cost. Design for Long-Term Efficiency.
What's Included
- Enterprise-wide data architecture and pipeline analysis
- Evaluation of ingestion, routing, and retention strategies
- Identification of cost drivers and inefficiencies at scale
- Standardization and optimization recommendations
- Future-state data architecture design
- Executive readout with strategic guidance
Why Data Complexity Becomes a Systemic Risk
At enterprise scale, data complexity doesn't just create inefficiency. It creates systemic risk that compounds across teams, environments, and business units.
Data growth outpaces infrastructure and cost controls, with no enterprise-wide strategy for managing ingestion, retention, or pipeline spend.
Ingestion strategies vary across teams and business units, creating fragmented pipelines with no standardization and limited reuse.
Limited visibility into enterprise-wide data usage, value, and cost makes it impossible to prioritize optimization or justify investment decisions.
Data architecture decisions are made in isolation, without alignment to long-term business needs, creating technical debt at every layer.
What This Engagement Delivers
An enterprise-scale data architecture engagement that evaluates, aligns, and designs your data strategy for performance, cost efficiency, and long-term growth.
- Enterprise Architecture Evaluation End-to-end evaluation of data ingestion patterns, pipeline architecture, and data flow across environments and business units.
- Cost & Efficiency Analysis Analysis of data growth patterns, retention strategies, licensing cost drivers, and redundant or low-value data flows at scale.
- Pipeline Standardization Recommendations for standardizing data onboarding, routing, and transformation practices across teams and environments.
- Systemic Inefficiency Identification Identification of cross-team redundancies, fragmented pipelines, and architectural patterns that limit scalability or drive unnecessary cost.
- Future-State Architecture Design Design of a scalable, cost-efficient target architecture aligned to enterprise priorities, data volumes, and long-term business needs.
- Strategic Roadmap A prioritized optimization and scaling roadmap with executive recommendations for investment, sequencing, and governance.
How We Work Together
Remote, fixed-scope, and consultant-led: every engagement has defined outcomes and a clear path to value.
Fixed-Duration Engagement
A defined engagement with structured days of work. Focused scope, no open-ended commitments.
Fixed Scope
Defined outcomes and deliverables from day one. No scope creep. Predictable delivery every time.
Remote Delivery
Delivered remotely by a certified Splunk consultant. Full engagement from day one, no travel overhead.
Active Participation Required
This is a collaborative engagement. Your team's involvement ensures outcomes map to your environment and priorities.
VAR Delivery Model
Delivered in partnership with your VAR. nth degree provides the execution capacity. Your reseller manages the relationship.
Executive Readout
Every engagement closes with a structured executive readout covering findings, recommendations, and next steps.
What You Walk Away With
Enterprise Architecture Assessment
Cost & Scalability Roadmap
Future-State Architecture Design
Standardization Recommendations
Executive Readout & Strategic Guidance
🎯 When to Use This Service
- Large-scale or multi-team Splunk environments experiencing data complexity
- Organizations experiencing rapid data growth with rising costs and no clear strategy
- Environments with fragmented data onboarding practices across teams
- Teams planning for significant long-term scaling, migration, or platform optimization
🏆 What Success Looks Like
- Enterprise-wide visibility into data usage, pipeline efficiency, and cost drivers
- Standardized, scalable data architecture across teams and environments
- Reduced cost through optimized ingestion strategies and retention policies
- Clear, executive-aligned roadmap toward sustainable data growth and governance
Find the Right Engagement Level
Each tier builds on the previous, scaling scope and depth to match your environment.
Foundation
- Data onboarding & pipeline review
- Parsing & field extraction validation
- Data quality & structure assessment
- Optimization recommendations
Strategic
- Pipeline & ingestion strategy analysis
- Cost driver identification & reduction
- Parsing & transformation optimization
- Prioritized optimization roadmap
Enterprise
- Enterprise architecture & pipeline analysis
- Data growth, indexing & retention strategy
- Systemic inefficiency identification
- Future-state architecture design
- Executive readout & strategic guidance
mesh™ Add-On
Optional Enhancement
mesh™This engagement can be enhanced through a mesh™ subscription for ongoing governance, continuous improvement, and sustained alignment beyond the engagement window.
With mesh™, your investment doesn’t end at delivery. It becomes part of an ongoing program:
- Ongoing prioritization of data onboarding and optimization
- Governance across enterprise data strategy and cost management
- Continuous refinement of pipelines, parsing, and architecture
- Sustained alignment between data quality, cost, and business outcomes
At Scale, Data Must Be Designed, Not Just Managed
This engagement ensures your enterprise data architecture supports long-term performance, cost control, and alignment between data strategy and business outcomes.