Develop a Data Ingestion and Storage Strategy
To ensure your data is reliable and accurate, we provide it with the best possible environment: a data ingestion and storage strategy designed for performance, security, and traceability. Behind every decision lies data that deserves to be protected and fully leveraged.
1
Data Reliability
Unreliable data has no value. Our teams ensure your data sources are properly ingested, assess data quality, and govern loading processes so that every decision is based on solid, traceable information.
- Data source analysis: Inventory, data flow and dependency mapping, connectivity validation, and risk assessment
- Data quality assessment: Measurements of completeness, accuracy, consistency, uniqueness, and freshness, with defined thresholds and alerts
- Data management process review: Roles and responsibilities (data owners/stewards), access policies, data lifecycle management, and remediation processes
2
Strategic roadmap
We build a clear, actionable roadmap that prioritizes the steps required to achieve your analytics objectives and maximize the ROI of your data. It includes concrete actions to strengthen data quality, security, and governance, with realistic milestones, timelines, and estimates for resources and budget.
- Strategic priority setting: Use‑case mapping, value/effort matrix, KPI definitions
- Milestones & timelines: Iterative delivery (MVP → scaling), delivery cadence, risk management
- Resources & budget: Capacity by role (data, BI, AI, security), skills development, cost estimation
3
Data Centralization
Designing a data integration and harmonization plan is complex. Our teams bring the experience and expertise needed to efficiently connect your systems and consolidate all your data sources (databases, ERP, CRM, APIs, flat files, SaaS, etc.) into a centralized, structured, and reliable environment—ready for analytics and AI.
- Collect: Centralize multi-sources data
- Harmonize: Organize and strandardize data to ensure consistency, quality and traceability
- Implementation of quality and compliance processes
4
Data Security
Because data security is critical, our teams design architectures and models that protect your customers’ information, including sensitive data. From access controls to encryption, we embed best practices to secure your analytics and AI use cases—without compromising performance.
- Protect: Encryption, masking, and access controls for sensitive data
- Govern: Data classification, access policies, and audit logs
- Monitor: Alerts and traceability to detect and prevent incidents
“Thanks to Neos’ data audit, we were able to optimize our processes and strengthen the security of our analytical infrastructure.”
Philippe Giroux, VP Digital Transformation
Groupe Amiel
Ready to define your data strategy?
Don’t let your data go unused. We put our data strategy expertise to work for your growth, delivering practical, industry‑focused solutions that move quickly from strategy to execution. Tell us about your objectives: together, we’ll build a concrete path that turns your data into a lasting driver of growth.