BIMachine - Analytics and IA Platform
BIMachine

Integrated Data Lake

Centralized storage and governance of corporate data

Data Lake BIMachine

Corporate Data Lake that stores years of history, processes billions of records, and delivers analysis in seconds. Unlimited storage, optimized performance, predictable cost.

Totvs
Salesforce
Vtex
SAP
Oracle
Excel

Unified Data Lake

100B+ rows | 500 TB

Why you can't
analyze complete business history

Databases die with volume

Relational databases weren't meant for analyzing billions of rows.

YEAR 1

2 seconds

500 thousand orders

YEAR 2

15 seconds

2.5 million orders

YEAR 3

90 seconds

8 million orders - Crashes!

Traditional solution: "Let's archive old data. Delete orders > 3 years."

You sacrifice history for performance. Decisions are short-sighted.

Each system has its database

Data in different places, different formats, they don't talk.

Totvs

SQL Server

Salesforce

Cloud

Vtex

Cloud

Budget

Excel

Supplier

CSV

Real cost: Complex analyses take days/weeks. Most give up. Decisions are made without deep analysis.

History is expensive to maintain

Companies cut history to save storage.

SQL SERVER ON-PREMISE (10 TB)

Hardware$ 20k/year
Licenses$ 30k/year
Backup$ 10k/year
Total$ 60k/year

BIMACHINE DATA LAKE (10 TB)

Cloud Storage$ 8k/year
Processing$ 4k/year
BackupIncluded
Total$ 12k/year
SAVINGS: $ 48K/YEAR (80% LESS)

Unlimited Storage + Analytical Performance
+ Optimized Cost

Columnar Storage

Data in Apache Parquet format. To sum revenue, it reads only the "value" column, ignores the rest.

90s → 3s (30x faster)

Automatic Consolidation

All data from all systems automatically consolidated when it arrives via connectors.

JOIN between systems automatically

Unlimited History

Data Lake scales horizontally. Smart partitioning by date.

10 years with no performance impact

Optimized Cost

Cloud storage with up to 80% lower cost than traditional infrastructure.

Linear scale, predictable cost

Smart Compression

Data compressed automatically. Text 10:1, Numbers 5:1, Dates 8:1.

50 GB → 8 GB (6x smaller)

Smart Cache

Frequent results cached. Monthly revenue: 1h cache. Pipeline: 15min cache.

<500ms even with billions of rows

How it works under the hood

1

Ingestion

Connectors extract data from source systems

  • •Structured (SQL, APIs)
  • •Semi-structured (JSON, XML)
  • •Unstructured (CSV, logs)
2

Storage

S3-compatible Object Storage, Parquet format

/company_id/
/orders/
/year=2024/
data.parquet
3

Engine

Apache Spark-like Query Engine

  • •Predicate pushdown
  • •Column pruning
  • •Parallel processing
4

Cache

Frequent results in memory

  • •Revenue: 1h cache
  • •Pipeline: 15min cache
  • •History: 1 day cache

Real world use cases

Deep History Analysis

CFO wants to compare 2024 vs 2019 performance (5 years ago)

WITHOUT DATA LAKE:

2019 data was archived/deleted. Analysis impossible.

WITH DATA LAKE:

2019 data is there. Query returns in 3 seconds.

INSIGHT:

2024 margin (18%) equal to 2019. But in 2020-2023 reached 22%. Why did it drop?

Cohort Analysis (Clients)

Manager wants to analyze retention by first purchase cohort

WITHOUT DATA LAKE:

Analysis limited to last 2-3 years. Old cohorts deleted.

WITH DATA LAKE:

Complete history since 2018. Full cohort analysis.

INSIGHT:

2018-2019 clients have 40% higher retention than 2023-2024. Why?

Multi-Year Seasonality

Director wants to plan inventory for December/2025

WITHOUT DATA LAKE:

Only 2022-2024 data (3 years). Small sample.

WITH DATA LAKE:

5 years of history. Identifies +47% pattern in December.

INSIGHT:

Data-driven decision: Increase inventory 50% for Dec/2025.

Behavior Change

CEO wants to know: Why did margin drop from 22% to 18%?

WITHOUT DATA LAKE:

Superficial analysis: Costs rose, prices didn't keep up.

WITH DATA LAKE:

Deep drill-down: Margin by product, region, client 2021 vs 2024.

INSIGHT:

Product A: margin dropped from 28% to 19%. Supplier X increased 45%.

Data organized, auditable, secure

Data Catalog

Automatic inventory. Smart search by any field or metric.

Data Lineage

Source to destination tracking. Know exactly where each number came from.

Granular Control

Automatic filters per user. Region, period, access profile.

Auditing

Complete log for GDPR, SOX, ISO 27001. Who accessed, when, which query.

From traditional database to
Data Lake in 1 week

1

ASSESSMENT

1 DAY

System survey, data volume, priority tables, requirements

2

HISTORICAL LOAD

2-4 DAYS

Full migration, transformation, integrity validation

3

VALIDATION

1 DAY

Row counting, aggregated totals, performance testing

4

GO-LIVE

1 DAY

Dashboard transition, production connectors, rollback available

Keep full historywithout sacrificing performance or cost

Corporate Data Lake ready for billions of rows

Strategic AI Diagnosis

  • checkMapping of current analytical maturity
  • checkIdentification of concrete opportunities for AI use in your area
  • checkPrioritization of initiatives based on impact and feasibility
  • checkGuidance on structure, tools and necessary integrations

Free Trial 14 Days

  • checkFull platform + active Ada.IA
  • checkIntegration with your data sources
  • checkBIMStore Templates
  • checkDedicated technical support in English
  • checkNo card, no commitment

Speak with one of our specialists

  • checkQuick 30-minute schedule
  • checkOverview and identification of opportunities
  • checkClear your doubts about the platform
BIMachine

Complete Business Intelligence and Artificial Intelligence platform to transform data into strategic decisions.

contato@bimachine.com.br
+55 (51) 3709-2950
Brazil

Solutions

  • Business Intelligence
  • Ada.IA (Generative AI)
  • IA Store (Marketplace)
  • IAMachine
  • BIM Store

Platform

  • Resources
  • Advanced Analytics
  • Integrations
  • Dashboards
  • Automation

Company

  • About us
  • Success Cases
  • Careers
  • Blog
  • Contact

Support

  • Knowledge Base
  • Help Center
  • Status
  • Training
© 2026 BIMachine. All rights reserved.
PrivacyTermsCookies