Mission: Make Data a Valuable product!

How? Making your data trustworthy.
Allowing business to focus on improving operations & finding efficiencies.

Why you need to start investing in data quality improvement?

Step to Implement Fluent

We start by answer these questions:

  • Who will use the platform?
  • What data quality problems do you want to solve?
  • What will be the single source of truth?
  • What are the challenges of data discovery and lineage?
  • What are your data governance requirements?

Building data pipeline monitoring

  • Using machine learning to understand the way data pipelines behave and send alerts when anomalies occur in that behavior.
  • Implement business rules for data validation

Operationalizing data pipeline with data observability

  • Define KPI to measure the success over time (downtime)
  • Coverage for freshness, volume, schema in place across entire data environment.
  • Optimize incident triage and resolution response, setting up clear lines of ownership.
  • Custom monitors centered around specific data SLAs (governance requirements)
  • Operationalizing preventive maintenance, preventing data incidents before pipeline breaks