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AI & Data

Business Intelligence Services

A data platform people actually trust — reliable pipelines, governed metrics, and self-serve analytics that answer questions without a queue for the data team.

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DAWKI / BISample data

Built for your business

From Raw Data to Trusted Insights

From Snowflake and BigQuery to Looker, Power BI, and Tableau — we engineer the modern data stack and the dashboards leaders actually use.

  • Modern Data Stack

    Snowflake, BigQuery, Databricks, dbt, Fivetran and Airbyte — production-grade.

    • Warehouse and ingestion set up
    • dbt project scaffold
    • Cost and access controls
    Learn moreEach layer swappable, none of them bespoke

  • ELT Pipelines

    Reliable, observable, version-controlled pipelines built with dbt and orchestrators.

    • Orchestrated ELT jobs
    • Tests on every model
    • Failure alerts to Slack
    Learn moreVersion-controlled, tested, and it tells you when it fails

  • Self-Serve Analytics

    Semantic layers and governed metrics so business users get answers without SQL.

    • Semantic layer and metric docs
    • Self-serve explores
    • Training for business users
    Learn more

  • Embedded Analytics

    Dashboards and metrics embedded into your SaaS product or internal apps.

    • Embedded, row-level secured
    • Themed to your product
    • Usage tracked
    Learn moreYour customers see their numbers inside your product, with your look

  • Data Quality & Governance

    Tests, alerts, lineage, catalogs and access controls.

    • Data tests and freshness SLAs
    • Lineage and catalog
    • Access policies
    Learn more

  • Predictive Analytics

    Forecasts, churn, scoring and anomaly detection on a trusted data layer.

    • Forecast and churn models
    • Anomaly detection
    • Scores written back to CRM
    Learn more

What we deliver

Business Intelligence Services We Offer

Start with the capabilities you need today. We define the scope, integrations, and acceptance criteria together before delivery begins.

  • BI Strategy & Roadmap

    Data vision, target architecture, tooling decisions, and adoption plan.

    Enquire about this

  • Cloud Data Warehousing

    Snowflake, BigQuery, Redshift, Databricks lakehouse implementation and tuning.

    Enquire about this

  • Data Pipelines & ETL/ELT

    Pipelines with Fivetran, Airbyte, Stitch, and custom Python — orchestrated by Airflow/Prefect.

    Enquire about this

  • dbt Development

    Modular dbt models, tests, docs, and CI/CD for analytics engineering at scale.

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  • Semantic Layer & Metrics

    LookML, Cube, dbt Semantic Layer — governed metrics consumed across tools.

    Enquire about this

  • Dashboards & Reporting

    Looker, Power BI, Tableau, Metabase, Sigma — designed for executives and operators.

    Enquire about this

  • Embedded Analytics

    Embed dashboards and customer-facing analytics into your SaaS product.

    Enquire about this

  • Data Quality & Observability

    Monte Carlo, dbt tests, anomaly detection, freshness checks, and SLA alerting.

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  • Data Governance & Catalogs

    Atlan, DataHub, Collibra — lineage, glossaries, and access controls.

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  • Reverse ETL

    Activate warehouse data into Salesforce, HubSpot, Marketo via Hightouch or Census.

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  • Predictive & Advanced Analytics

    Forecasts, churn, LTV, and segmentation models built on your data warehouse.

    Enquire about this

  • Data Team Augmentation

    Embedded analytics engineers, BI developers, and data architects for your team.

    Enquire about this

From brief to delivery

A clear path from the first conversation.

A practical process with agreed milestones, regular reviews, and a handover your team can use.

  1. Step 01

    Audit & Strategy

    Audit data sources, gaps, and stakeholder needs; design target architecture.

  2. Step 02

    Build

    Stand up warehouse, ELT, semantic layer, and core dashboards.

  3. Step 03

    Activate

    Roll out self-serve analytics, training, and adoption playbooks.

  4. Step 04

    Operate & Improve

    Monitor pipeline health, evolve data models, and add predictive capabilities.

Tools of the trade

The right technology for the work.

We choose tools around your existing systems, requirements, and long-term maintenance needs. The final stack follows the project.

  • Snowflake
  • Google BigQuery
  • Databricks
  • PostgreSQL
  • Fivetran
  • Airbyte
  • Stitch
  • dbt
  • Apache Airflow
  • Tableau
  • Looker
  • Power BI
  • Metabase
  • Cube
  • Hightouch
  • Monte Carlo

Your next step

Request a free consultation

A few details help us understand your goals and come prepared. Fields marked * are required.

How we use your details. We collect only what you enter here — your name, mobile number and email, and your company, budget and message if you add them — to reply to this enquiry, prepare a proposal and follow up about it by phone, email or WhatsApp. We don’t sell your data or use it for anything else. You can withdraw consent, or ask to see, correct or erase your data, at any time by emailing info@dawkiinfotech.com; if we don’t resolve a concern, you can complain to the Data Protection Board of India. Full details in our Privacy Policy.

Before we begin

Your questions, answered.

What to know about business intelligence services, from project scope to ongoing support.

01What is business intelligence?

Business Intelligence is the practice of turning raw business data into trusted dashboards, metrics, and insights that drive better decisions across the organization.

02Which BI tools do you work with?

Looker, Power BI, Tableau, Metabase, Sigma, and Mode — chosen based on your data team, budget, and existing stack.

03Which data warehouses do you support?

Snowflake, BigQuery, Redshift, Databricks lakehouse, and Postgres-based warehouses — including migration between them.

04Do you build the pipelines too?

Yes. We design and build pipelines with Fivetran, Airbyte, Stitch, custom Python, and orchestrators like Airflow, Prefect, or Dagster.

05Can you embed analytics into our product?

Yes. We embed dashboards and build customer-facing analytics into SaaS products using Looker, Sigma, Cube, or custom builds.

06How do you handle data quality?

dbt tests, Monte Carlo or similar observability platforms, freshness alerts, anomaly detection, and clear data SLAs.

07How long does a BI implementation take?

A foundational warehouse + core dashboards typically launches in 8–14 weeks. Larger enterprise BI programs run 4–9 months in phases.

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A conversation is a good start

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