Qlik Talend Data Integration — Data Integration and Management in Azerbaijan
A modern platform for integrating, transforming, and preparing data for analytics and AI. Creates a unified and trusted data pipeline for businesses.
Supports deployment in the cloud, on-premises, and in hybrid environments. Implementation, licensing, and support in Azerbaijan.
- A unified data management platform Combines integration, data quality, management, and transformation into a single solution—without the need for disparate tools.
- Data Preparation for Analytics and AI Generates trusted, up-to-date, and ready-to-use data for BI, machine learning, and generative AI.
- Architectural Flexibility Support for cloud, hybrid, and multi-cloud environments with integration with AWS, Microsoft Azure, Google Cloud, Databricks, and Snowflake.
- Reliability and Compliance Built-in mechanisms for quality control, security, and regulatory compliance.
- From data to solutions and action. Accelerating the transition from analytics to action—from identifying signals to automation.
▪️Support for ETL, ELT, and CDC (Change Data Capture)
▪️Replication and automation of data processing pipelines
▪️Automated creation of Apache Iceberg data lakes with support for batch and streaming data, and performance optimization of Iceberg tables
▪️Automated creation of knowledge marts for RAG applications, using vector databases and LLM embeddings from OpenAI, Azure OpenAI, and Amazon Bedrock
▪️Integration of data from on-premises, cloud, and streaming sources
▪️Incremental data loading and processing optimization
▪️AI-assisted development and maintenance of data pipelines
▪️Connection to a wide range of sources via pre-built connectors
Enables rapid delivery of data to data stores, lakehouses, and analytics systems
▪️Visual, SQL, and AI-assisted transformation tools
▪️Building data pipelines tailored to specific business needs
▪️Support for architectures: Data Warehouse, Data Lake, Lakehouse (Medallion)
▪️Automation of data mart creation
Data becomes “fit-for-purpose”—ready to use without further processing
▪️Data profiling, cleansing, and enrichment
▪️Real-time data quality monitoring
▪️Configuration of quality rules and standards
▪️Metadata management and cataloging
▪️Data lineage analysis and impact analysis (impact analysis)
▪️Access control and security policies
▪️Support for high-quality data in the form of data products, data validation, and data correction (data stewardship)
Ensures data trust and control over its use in analytics and AI
▪️Deployment in the cloud, on-premises, or in a hybrid environment
▪️Connection to on-premises and cloud data sources, including secure perimeters
▪️Support for multi-cloud scenarios (AWS, Azure, Google Cloud)
▪️Scalable architecture tailored to business needs
Quick deployment without complex infrastructure
Streaming Data Transfer
High-performance real-time data transfer.
Data Transformation and Data Warehouse Modernization
Automating data transformation and accelerating modern data pipelines.
Open Lakehouse
Building open lakehouse architectures based on Apache Iceberg.
Data Quality and Governance
Providing trusted data for users and systems.
Application Integration and APIs
Creating secure APIs and optimizing integration processes.
Application Automation
Responding to events and actions based on real-time data.
SAP Solutions
Maximizing the value of SAP data.
Integrations and Connectors
Access and integrate data from any source.
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