Data for Ops : Giving meaning to your data

We help IT, SRE, operations, production, and security teams turn data into a driver of efficiency to improve IT operations management.

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Data for Ops: turning data into a driver of operational growth

Data is everywhere, but is it really being used? Whether for strategic decisions or critical operations, Synapsys helps you turn your data into meaningful action.

IT teams face an explosion of data from both business activities (marketing, finance, HR, sales) and IT operations (logs, alerts, metrics, performance, cybersecurity). Despite this wealth of information, data often remains underutilized — missing the opportunity to create value, optimize operations, or anticipate issues.

Synapsys offers Data for Ops support to turn this data into a powerful driver of growth and performance for technical, SRE, operations, production, and security teams.

How we successfully drive your Data for Ops initiatives

Our experience in data and IT operations management enables us to successfully guide your Data for Ops journey, ensuring the integration of the right data management methodologies and tools.

Advanced visualization and monitoring

We develop customized monitoring and analytics tools to track incidents, system performance, and cybersecurity operations using platforms such as Grafana, Kibana, Power BI, and Metabase.

Intelligent analytics and AI

We rapidly deploy Data & AI use cases to automate anomaly detection and perform predictive analyses of failures, saturation, or user behavior.

Data-driven cybersecurity

We help you develop use cases to enhance real-time security log monitoring, build dashboards for SOC/SIEM, and strengthen compliance support for GDPR, NIS2, and ISO 27001.

Continuous improvement

We support you end-to-end, from defining KPIs for Ops teams, integrating them into DevOps routines (run, incident review, etc.), to building a data-driven culture within your teams.

Key Data for Ops use cases

Automatic detection of anomalies in system metrics (CPU, RAM, network latency, application errors, etc.) using predictive models.

Automated KPIs on ITIL processes (incident, change, problem, release) through ticket analysis and lifecycle tracking.

Modeling resource consumption trends (servers, storage, network) to forecast future capacity needs.

Analysis of logs and user behavior (IAM, access, hours, applications) to detect suspicious patterns or deviations from internal policies.

Analysis of incident history (ITSM) to identify the most frequent root causes, recurring bottlenecks, and the most frequently engaged teams.

Cross-analysis of cloud and on-premise consumption data with associated costs to detect drifts, underused resources, or unused instances left running.

Our Data for Ops support

Our Data, DevOps, and AI teams support you throughout your projects to identify and develop Data for Ops use cases that create real value.

Quick audit of existing data and needs

Training and data culture enablement for internal teams

Use case scoping and KPI identification

Delivery of dashboards and analytical models

Deployment of a proof of concept on a critical scope

Implementation of production-ready ETL / ELT pipelines

Centralization and cleansing of data sources (logs, metrics, traces, alerts, etc.)

Accelerate your Data for Ops transformation

Our experts support you in automating your operations and enhancing your performance.

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Frequently Asked Questions

What is Data for Ops and why is it useful for IT teams?

Data for Ops refers to the use of operational data from IT environments (logs, alerts, metrics, traces) to improve monitoring, security, performance, and the ability to anticipate incidents. This approach enables technical teams (RUN, SRE, production, security) to act faster and more proactively, and to optimize critical operations through relevant indicators and real-time visibility.

What types of data are used in a Data for Ops approach?

Data for Ops leverages a wide range of technical data: system logs, performance metrics, monitoring alerts, application traces, security logs, resource usage indicators, etc. This data is centralized, cleaned, and then integrated into ETL/ELT pipelines to feed dashboards or predictive analytics models.

What concrete benefits does Data for Ops bring to IT operations and production teams?

Thanks to Data for Ops, IT teams can:

Reduce MTTR by visualizing incidents faster
Anticipating breakdowns or saturations through predictive models
Automating certain operational decisions
Improve security through real-time log analysis
Monitor regulatory compliance (GDPR, ISO 27001, NIS2)

What technologies are used in a Data for Ops approach?

Implementing a Data for Ops solution relies on monitoring tools (Grafana, Kibana, Metabase, Power BI), data processing pipelines (ETL/ELT), AI/ML analytics platforms for anomaly detection, and custom dashboards for IT teams. These technologies enable advanced monitoring, improved data governance, and faster decision-making.

How does Synapsys support you in implementing a Data for Ops strategy?

Synapsys offers a comprehensive approach to structuring and leveraging operational data: a rapid audit of existing data, definition of priority use cases, implementation of a proof of concept (POC), creation of dashboards tailored to operational roles, integration of critical data, and team training. The goal is to transform raw data into high-impact, sustainable, and controlled operational decisions.