Service · Data & Analytics

Big Data & Lake House

Unified lakehouse platforms that bring all your data together for analytics and AI — one governed source of truth, built to scale.

+0%Query performance
0%Storage cost saved
0%Data silos eliminated
Overview

What is Big Data & Lake House?

Big Data & Lake House at MindCraft Solution unifies your data estate into a single, governed platform that serves both business intelligence and machine learning. Instead of separate, costly silos — a warehouse here, a data lake there — we build a lakehouse that gives every team trusted data without copies and chaos.

We design for scale and cost from the start: open table formats, elastic compute separated from storage, and a clear medallion architecture (raw → cleaned → curated) so data is reliable and lineage is obvious.

The result is one place where analysts, data scientists and applications all work from the same trusted data — faster to query, cheaper to run, and ready for AI.

What's included

What Big Data & Lake House includes

Everything you need to take big Data & Lake House from idea to a dependable, owned capability.

Lakehouse architecture

A unified platform on Snowflake or Databricks serving BI and AI from one source.

Medallion data modelling

Raw, cleaned and curated layers with clear lineage and quality.

Ingestion at scale

Batch and streaming ingestion from all your sources.

Open table formats

Delta / Iceberg for reliability, time travel and no lock-in.

Performance & cost tuning

Partitioning, clustering and elastic compute to balance speed and spend.

Governance & access

Cataloguing, fine-grained access and quality controls built in.

The impact

Outcomes we target

Typical results from MindCraft data & Analytics engagements.

+0%Query performance
0%Storage cost saved
0%Data silos eliminated
0%Pipeline reliability
How we work

Our delivery model

A clear, low-risk path from first call to a running, optimized solution.

  1. 1

    Assess

    We map your sources, consumers and pain points, and design the target lakehouse.

  2. 2

    Build foundations

    We stand up storage, compute, ingestion and the medallion layers.

  3. 3

    Migrate & model

    We move data in and model curated, trusted datasets for each use.

  4. 4

    Optimise & govern

    We tune performance and cost and put governance and access controls in place.

Engagement models

Ways to work with us

Pick the model that fits your stage, budget and pace.

01

Fixed-scope project

A defined outcome, timeline and price. Best when the goal is clear and you want certainty.

02

Dedicated team

A senior squad that works as an extension of your team, iterating sprint by sprint.

03

Staff augmentation

Vetted specialists who plug into your existing team, tools and process.

Tools & technology

The stack we use

SnowflakeDatabricksDelta LakeApache IcebergApache SparkdbtAirflowAWS S3
Industries we serve

Built for your sector

We tailor big Data & Lake House to the realities, data and regulation of your industry.

Financial ServicesRetail & E-commerceHealthcareManufacturingTelecom
Deliverables

What you get

Concrete, owned artifacts — not just advice.

  • Lakehouse platform on your cloud
  • Medallion data model
  • Batch & streaming ingestion
  • Governance & access controls
  • Documentation & enablement
FAQ

Questions, answered

A warehouse is great for BI but limited for raw/ML data; a lake is flexible but hard to govern. A lakehouse combines both — warehouse reliability and governance over open, low-cost storage — so you don't maintain two systems.

No — we migrate incrementally by domain or use case, proving value early and avoiding a risky big-bang.

We use open table formats (Delta / Iceberg) so your data stays portable and you keep leverage over compute choices.

Yes — that's the point. The same governed data serves dashboards and machine-learning models, without duplicate copies.

Ready to talk about Big Data & Lake House?

Tell us where you are and what success looks like. We'll bring the right people, stack and plan — and reply within one business day.