We help organizations overcome the challenges of managing and processing large and complex data sets, enabling them to extract insights and value from their data; simplifying and accelerating the process of building and managing data pipelines by leveraging services and tools offered by providers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP)
Data Engineering
Foster a data-driven culture
Harnessing data for competitive advantage
Our Data engineering competency unit specializes in
- Developing pipelines and workflows that move data from various sources, such as
databases, APIs, and sensors, to a data warehouse or data lake. - Designing data schemas, optimizing data storage and retrieval, and ensuring data
quality and consistency
Our talent pool includes experts in
- Storage services, such as AWS S3 or Azure Blob Storage
- Distributed computing platforms such as Hadoop and Spark, AWS EMR or GCP Dataproc
- SQL and NoSQL databases
- ETL tools such as Apache Airflow, Talend, AWS Glue and GCP Dataflow
- Data warehouses such as AWS Redshift, Snowflake, and Azure Synapse Analytics
- Business intelligence and data visualization tools such as Tableau or Power BI
We offer the following services to help organizations overcome the challenges of managing and processing large and complex data sets, enabling them to extract insights and value from their data
- Master Data Management: Implementing MDM solutions, including data profiling,
data cleansing, data governance, data modeling, and data integration. - Data Migration: Planning and Execution of migrating large volumes of complex
data from on-prem to cloud, or cloud to cloud. - Data Integration: Services for integrating data from various sources into a single
data repository, such as ETL (Extract, Transform, Load) and ELT (Extract, Load,
Transform) processes.
- Data Warehousing: Services for designing, implementing, and managing data warehouses, including building data models, creating ETL pipelines, and optimizing performance.
- Data Lake: Services for building and managing data lakes, which are repositories for unstructured and structured data that enable organizations to store and process large amounts of data quickly and cost-effectively.
- Data Governance: Services for establishing policies and procedures for managing data, ensuring data quality, and maintaining compliance with regulatory requirements.
- Cloud Data Engineering: Services for designing and implementing cloud-based
data engineering solutions using services such as Amazon Web Services (AWS),
Microsoft Azure, and Google Cloud Platform (GCP). - Data Pipeline Automation: Services for automating the data pipeline using tools
such as Apache Airflow and other workflow management systems. - Data Visualization: Services for creating visualizations and dashboards that
enable users to explore and analyze data.