Solutions

BI and Business Analytics: From Data Source to Solution

We consolidate data from 1C, ERP, CRM and logs into one infrastructure: DWH and data marts, dashboards and management P&L, plus an AI layer on top. We select the BI engine for your data and security requirements, not the other way around.

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Our clients

Capital Group
FSK Group
SMLT
Tochno
Dogma
Sber City
FM Logistic
Danone
Relief Center
Pandora
BI and management analytics: from data to solutions
Saint-Gobain
Askona
FIX PRICE
Snezhnaia Koroleva
Muztorg
TVOE
Greenway
Polaris
Campari
Yandex
Lenta
International perfume and cosmetics brand
BI and management analytics: from data to solutions
RAEC
EKF
L'Etoile
Inventive Retail Group

How BI infrastructure works

BI and management analytics: from data to solutionsA horizontal flow of six nodes. On the left: 'Data exists, no solutions'. Next: 'Sources': 1C, ERP, CRM, logs. Then 'DWH / Data Lake', 'Data marts and ETL', 'BI dashboards' and on the right the result: 'Solutions from data, P&L'. Above the middle nodes—a band 'AI layer: anomalies, forecasts, explanations'.AI layer: anomalies · forecasts · explanationsData exists,no solutionsSourcesDWH /Data LakeData martsand ETLBI dashboards1C · ERP · CRM · logsSolutionsfrom data, P&L
From disparate sources to solutions: data from 1C, ERP, CRM and logs flows through DWH, data marts and dashboards, while the AI layer finds anomalies, builds forecasts and explains metrics.

How to choose a BI engine

No single engine covers all needs. We select based on your infrastructure, data requirements and budget—honestly, not tied to one vendor.

Yandex DataLens

Default cloud BI in RF: fast launch, sanction-free, native on ClickHouse, PostgreSQL and Metrics. → Learn more

Apache Superset

Open-source BI for on-premise and product embedding: data stays on your infrastructure, embedded SDK with JWT. → Learn more

ClickHouse

Real-time storage layer for big data and operational analytics. → Learn more

Qlik / Tableau

Support and development of existing BI infrastructure, including Power BI. → Learn more

What we do

DWH and Data Lake

We design data warehouse and data lake: sources, quality, layers and data marts on PostgreSQL, ClickHouse or Greenplum. → Learn more

Data marts and ETL

We build data marts and ETL pipelines: data from 1C, ERP and CRM brought to a unified analytics model.

BI dashboards

We build interactive dashboards and reports: real-time metrics, role-based access, self-service for business users.

Management P&L

We build management P&L you can trust for decisions: reproducible reporting instead of manual exports.

Data Governance and Data Quality

Enterprise data management: standardization, error elimination, unified master data and rules.

AI layer above analytics

AI on top of BI: data collection, anomaly detection, forecasts and natural language metric explanation. → Learn more

Assess where AI can deliver impact in your process

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Industry scenarios

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BI and management analytics case studies

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Related videos

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5:29 DWH implementation stages / Effective business data management 3:15 Implementing a DWH / Data Warehouse — the company's data store 4:55 The difference between DWH and a Data Lake, and where to start?