99.98%Uptime
4.7xDeploys/wk
-38%Cost
Deploy pipelinegreen
Security scansgreen
SLO burn ratehealthy
Yansh Systems
We design modern data platforms on Snowflake, BigQuery and Databricks — with governed pipelines, dbt-modelled semantics and self-serve BI that survives contact with actual business users.
Data programs fail when engineering ships pipelines nobody trusts and analytics ships dashboards nobody opens. We treat platform, semantics and enablement as one product — owned end-to-end.
Whether you're picking your first warehouse or untangling a decade-old lake, we meet you at your current maturity and take you to the next stage without a rewrite.
Use-case shortlisting, target architecture and a costed roadmap your CFO can defend.
Snowflake, BigQuery or Redshift builds with tenancy, security and cost controls baked in.
Databricks and Iceberg patterns for scale, ML workloads and open-format portability.
Airbyte, Fivetran and custom connectors feeding dbt models with CI, tests and lineage.
Looker, Power BI and Tableau rollouts with a real semantic layer and certified content.
Collibra, Alation and Unity Catalog implementations with stewardship models people follow.
Customer, product and location MDM with match/merge, survivorship and downstream syndication.
Kafka, Kinesis and Flink pipelines for event-driven analytics and operational use cases.
Great Expectations, Monte Carlo and Elementary to catch broken data before your CEO does.
Workshop on business questions, source-system audit and a prioritized data-product backlog.
Conformed dimensions, dbt project structure, metric definitions and access-tier design.
Pipelines, models and dashboards shipped in two-week increments with stakeholder demos.
Analyst training, governance handover and a runbook for adding the next data product yourselves.
A 400-store retailer was reconciling four conflicting versions of daily sales every Monday morning. In eighteen weeks we consolidated onto Snowflake, rebuilt sales and inventory models in dbt, and shipped a single certified dashboard the exec team now opens before their coffee.
Depends on workload profile, existing cloud, ML ambitions and team skills. We'll recommend after a short discovery, not a sales call.
Yes. Most engagements are on incumbent stacks; we optimize before recommending anything is replaced.
Classification, masking, row-level security and access reviews are part of every platform build, not a later phase.
Enablement is a formal workstream — pair sessions, dbt training and office hours until analysts self-serve confidently.
Book a 30-minute call with a data principal. We'll come with two or three concrete plays sized to your team and stack.