Data Engineering
Scalable data engineering workload platform services
Data engineering catered to your business needs
CloudBerry360 assists clients in overcoming prevalent risks and challenges in Data Engineering projects. Our success stems from collaborating closely with both business and IT communities to establish a shared understanding. We tailor solutions that offer compelling value propositions, addressing the specific needs and perspectives of both the business and IT sectors.
We provide a full spectrum of data engineering services designed to empower businesses to optimize and enhance their data management:
End-to-End Data Engineering Services: Comprehensive support across all phases of data handling.
Data Lifecycle Management: Includes data classification, security measures, storage tiering, and policies for data deletion and destruction.
Automated Data Engineering Processes: Robust data pipelines that integrate data from databases, files, APIs, and IoT sources.
Data Governance and Assurance: Adherence to the Data Management Body of Knowledge (DMBOK) to ensure proper data handling and compliance.
Data Quality Framework: Implements quality dimensions, lifecycle considerations, supporting methodologies, and scorecards to maintain data integrity.
Intelligent ETL Systems: Advanced extract, load, and transform processes coupled with intermediate storage solutions like data lakes.
Master Data Management (MDM) Services: Ensures consistency, accuracy, and accountability in master data across the enterprise.
Industry Expertise: Extensive experience serving sectors such as Healthcare, Fintech, Local and Central Government, and Education.
Leverage our top data science & engineering services to improve business efficiency
Databases & Storage
SQL (MySQL, PostgreSQL), NoSQL (MongoDB, Cassandra), and distributed systems like Hadoop and cloud storage solutions (AWS S3, Azure Blob).
Data Processing & Integration
Apache Spark, Apache Flink for real-time data processing; Apache Kafka for stream processing; and traditional ETL tools such as Talend and Informatica for data integration.
Data Orchestration
Apache Airflow and Luigi for workflow management to ensure seamless data flow and task scheduling.
Data Analytics & BI
Tools like Tableau, Power BI, and Qlik for data visualization and analytical reporting, coupled with Python and R for statistical analysis.
Machine Learning & AI
TensorFlow, PyTorch, and Scikit-learn for building and deploying machine learning models; MLflow for model management.
Data Governance & Quality
Solutions like Collibra and Alation for data governance, ensuring compliance with data quality standards and regulatory requirements.
Security & Compliance
Technologies ensuring data security, including encryption tools, identity and access management (IAM) solutions, and compliance frameworks to adhere to regulations like GDPR.
Cloud Platforms
Extensive use of AWS, Azure, and Google Cloud Platform for scalable, flexible, and cost-effective cloud services that enhance our data engineering capabilities.
