Analytical Data Platform for the Energy Sector —KazEnergy

Analytical Data Platform (ADP) Development that would automate data collection from multiple structured and unstructured sources.

Python 3.x

TensorFlow

Microsoft Power BI

Introduction

The KazEnergy Association, a key institution coordinating Kazakhstan’s energy sector, faced major challenges in monitoring, analyzing, and forecasting industry dynamics across oil, gas, and renewable energy segments. Existing data sources were fragmented — spread across government agencies, industry reports, media, and company filings — making decision-making slow and inconsistent. KazEnergy sought to create an Analytical Data Platform (ADP) that would automate data collection from multiple structured and unstructured sources, consolidate it into a unified Data Warehouse (DWH), and provide real-time analytics and interactive dashboards for energy industry monitoring, forecasting, and reporting.

Business Challenges

1

2

3

Fragmented and heterogeneous data ecosystem

Lack of automated analytics and visualization tools

Limited ability to process unstructured information

The solution implemented a modular analytical platform based on a multi-layer architecture:

• Data Collection Subsystem — automatic ingestion from APIs, file uploads, and direct DB connections; supports structured, semi-structured, and unstructured data.
• Data Warehouse (DWH) — unified storage combining relational, non-relational, and graph databases for efficient cross-domain analysis.
• Analytics & Visualization Layer — dynamic dashboards, reports, and visual widgets (built in Microsoft Power BI) showing KPIs such as production, exports, and prices.
• Unstructured Data Analysis Module (NLP) — uses AI to summarize documents, extract entities, detect topics, and build knowledge graphs.
• Administration Subsystem — full control over users, roles, access rights, and audit logs.

Approach

Phase 1 – Research & Design
o Collected data structure and requirements from KazEnergy departments and government partners.
o Designed system architecture, database schema, and UX mock-ups for dashboards.
o Delivered a Conceptual Project with role matrix, security model, and scalability plan.

Phase 2 – System Development
o Implemented DWH with hybrid storage (PostgreSQL + Neo4j + MongoDB).
o Developed ETL pipelines for ingestion from state and corporate data sources. o Created analytics dashboards and widgets visualizing key indicators: production, reserves, exports, investments, taxes, and pricing.
o Integrated NLP module (Python + TensorFlow/PyTorch) for automatic summarization, topic modeling, and trend detection.

Phase 3 – Deployment & Operation
o User training and system testing with real datasets.
o Launch into pilot mode followed by full production deployment.
o Established warranty support and 24/7 monitoring procedures.

1) Dashboards: oil & gas production, refinery processing, foreign investment, national fund contributions, energy consumption, and fuel price dynamics.

2) Unstructured analytics: automatic generation of summaries and insights from industry news, reports, and scientific articles.

3) Knowledge Graph: linking entities such as companies, fields, and projects for contextual exploration.

Results

>50 % reduction

In manual report preparation time.

Enhanced decision-making speed

With real-time KPIs and predictive modeling

End-to-end
digitalization

Data aggregation and analytics for Kazakhstan’s energy sector.

Improved transparency and communication

With government agencies and industry stakeholders

Other Cases

Increasing revenue with AI implementation: Dodo Pizza

Through in-depth research and analysis, we identify opportunities for growth, target audience insights, and the most

Increasing revenue with AI implementation: Dodo Pizza

Through in-depth research and analysis, we identify opportunities for growth, target audience insights, and the most

22 months

7 specialists

22 months

7 specialists

Would you like to discuss your project?

We will help you grow your business by creating and implementing a technology strategy tailored to your needs.