iDACC employs experienced Big Data Engineers, Data Scientists, and Business Analysts offering the following consulting and implementation services:

  • Big Data Systems Engineering
  • Data Engineering & DataOps
  • Data Science
  • Data Visualization
  • Project Management for Data Science
  • Security and GDPR Compliance
  • Data Driven Executive Decision-Making Consulting

Netcompany-Intrasoft employs its own DataOps approach to successfully implement any analytics solution.  Our approach is based on four methodological & engineering pillars:

  1. Continuous data analytics methodology that bridges stakeholder expectations with data driven results
  2. Data SLAs ensuring availability, quality and security standards
  3. State of the art data instrumentation for streamlining and automating data pipelines
  4. Use of collaborative data engineering development environments for improved re-usability and technological choices

Continuous data analytics

Continuous data analytics is an iterative 5-step process making sure that all requirements set by the customer are consistently evaluated against the work done by Netcompany-Intrasoft’s data engineers and data scientists. This process ensures that the outcome will be a cognitive data application that matches the customer’s expectations with the maximum possible accuracy.

Data SLAs for availability, quality and security standards

Based on customer needs and requirements Netcompany-Intrasoft engineers will design a solution to meet the SLAs belonging to the following categories:

  1. Data Availability & Retention – How fast data must be ingested, processed & queried and how long data remain online.  
  2. Data Quality – Metrics about the quality and fidelity of the ingested data. 
  3. Security – Compliance to regulatory and internal requirements.

Data instrumentation for streamlining and automating data pipelines

Netcompany-Intrasoft’s data engineers design & implement logic that checks every stage of the implemented data pipelines for compliance to the data availability and quality SLAs defined together with the customer.  If any SLA is broken the appropriate personnel will be notified.

Collaborative Data Engineering Environment

For any data analytics project to succeed, the data engineers and data scientists involved need to have at their disposal their favorite toolset. Their work needs not only to be shareable with their colleagues but also, any code deployed into the production system must seamlessly work without errors about missing libraries or access rights. Netcompany-Intrasoft’s engineers can design and deliver fully collaborative and re-usable data engineering development environments, utilizing pure open source or commercial platforms.