WHAT DOES A DATA LAKEHOUSE DO?

Turns scattered data into a unified foundation for analytics, models, and operational automation
without endless integrations or inconsistent reports

OMNICHANNEL BIKY

OMNICHANNEL & OPERATIONAL INGESTION

Connects commercial and marketing sources: conversations, forms, web, CRM, DMS, ERP, Ads, and events.
Preserves data origin so every data point is trustworthy and traceable

traceability biky ads

END-TO-END LINEAGE & TRACEABILITY

Preserve data lineage: what arrived, when, from where, who used it, and what action it triggered.
Reduce risk, speed up audits, and strengthen governance

BIKY data lakehouse para automatizar ventas con IA

RAW, CURATED, AND CONSUMPTION ZONES

Store raw data, refine what matters, and publish what’s business-ready.
Your team can explore without breaking operations, and BI consumes without guesswork

BIKY Trust KYC para automatizar ventas con IA

GOVERNANCE, ACCESS & QUALITY

Role-based control, quality policies, and automated validations.
Fewer silent errors, more consistency for leadership, operations, and compliance

datos no estructurados biky

UNSTRUCTURED DATA FOR AI

Turns conversations, intent, sentiment, audio, documents, and signals into analytical assets.
This is key to running conversational sales with precision

ANALITICA EN TIEMPO REAL BIKY IA

ACTIVATION FOR BI & MODELS

Publish datasets and consumption layers for dashboards, cohorts, attribution, scoring, and model training.
Maintain a single source of truth for BI and ML

The Problem

Without a real Data Lakehouse, your company has data, but no truth

Each team builds its own “number” from different sources. Marketing tracks clicks, sales tracks deals, operations track timing, and no one can close the full loop. The result: inflated CAC, slow decisions, and models learning from polluted signals.

Consequences of operating without a Data Lakehouse:

  • Reports that don’t reconcile across teams
  • Costly integrations that never end
  • Unstructured data left out of analysis (chat, intent, objections, tone)
  • Incomplete attribution: money spent without proof of closure
  • Fragile compliance: slow audits with no lineage

The BIKY Thesis

A Data Lakehouse is not storage. It’s the infrastructure that turns data into execution

BIKY treats it as a data operating system: it unifies, governs, and publishes information ready to drive decisions and activate actions across the commercial operation. The advantage isn’t “having data,” but having data that’s reliable, alive, and usable for automation and continuous learning.

How we solve the problem:

  • Compliance by design: consent, traceability, and auditability
  • A single source of truth with lineage and versioning
  • Structured and unstructured data ready for analytics and models
  • A complete loop: campaign → conversation → opportunity → close → learning
  • Operational quality: rules, validations, and role-based access control.

HOW IT WORKS?

Three steps to turn scattered data into intelligence ready to operate


1.

CONNECT

Integrate your critical sources and standardize inputs: conversations, forms, web, CRM, Ads, and operations



2.

ORGANIZE

Structure data in layers: raw, curated, and consumption. Apply quality, identity, lineage, and governance to ensure consistency




3.

POWER

Publish datasets for Analytics, BI, and models; activate segments and signals so the rest of the suite runs with precision


DATA LAKEHOUSE IN ACTION

Unified data so AI stops guessing and operations become measurable

When truth is shared, conversion goes up and waste goes down

  • Faster decisions with consistent metrics
  • More accurate models powered by clean, complete signals
  • Real attribution: spend connected to closed revenue
  • Less friction between teams. Everyone operates on the same context
  • Scalability without relying on “heroes” or scattered spreadsheets

Use Cases

  • End-to-end attribution by cohort and channel
  • CLTV, CAC, and repurchase loops backed by evidence
  • Intent-based scoring using conversational signals
  • Forecasting based on real activity, not manual “updates”
  • Data observability and auditability for compliance and leadership
  • Feature layer for model training and evaluation

Data Lakehouse is the foundation. The other modules execute

  • CDP unifies identity and activates operational context
  • Analytics measures operations with full traceability
  • CRM runs the pipeline with live data and human oversight
  • Ads learn from real closures and optimize spend with evidence
  • Trust creates an auditable record and connects verification to decision-making

Privacy & Compliance Built into the Architecture

  • Consent enforced by channel and purpose (GDPR, ARCO, Law 1581)
  • Auditable record of changes and activations
  • Role-based access control
  • End-to-end traceability

FREQUENTLY ASKED QUESTIONS

A CDP unifies identity and customer context for commercial activation. A Data Lakehouse is the analytical storage and compute layer that consolidates the entire data reality, operations, marketing, conversations, and business, for BI and models. The CDP relies on the Lakehouse to scale with consistency.

Not necessarily. The Lakehouse can coexist with them and simplify when it makes sense. Its focus is to centralize, govern, and publish reliable datasets so BI tools and data teams can consume without friction.

Structured data (tables, events, transactions) and unstructured data (conversations, documents, signals, and context). This enables analytics and automation with a complete picture.

As a technical protocol: consent is recorded by channel and purpose, activation is controlled, and full traceability is maintained for audit and compliance.

A Single Source of Truth

Activate your Data Lakehouse to centralize, govern, and activate AI-ready data with full traceability and execution connected to your commercial operation

Activate your demo