About Azure Data Engineering

Microsoft Azure's cloud-based platform to design, build, manage, and optimize data pipelines, ensuring efficient data movement, transformation, storage, and analytics within a scalable and secure environment. Azure provides a variety of tools and services for end-to-end data engineering workflows, enabling organizations to manage big data and extract valuable insights.

Key Components of Azure Data Engineering

Azure Data Factory (ADF)

A cloud-based data integration service that allows you to create, orchestrate, and automate data pipelines. ADF enables ETL (Extract, Transform, and Load) operations, allowing data engineers to move data between different sources, transform it, and load it into data stores.

Azure Synapse Analytics

An analytics service that combines big data and data warehousing. It allows seamless integration with data lakes, supports querying with both on-demand and provisioned resources, and provides a unified platform for data ingestion, preparation, and analytics.

Azure Data Lake Storage (ADLS)

A scalable, secure data lake that supports both structured and unstructured data. It is optimized for storing large volumes of data and integrates with other Azure services like ADF and Synapse.

Azure Databricks

An Apache Spark-based analytics platform, Azure Databricks offers fast, optimized big data processing, AI, and machine learning capabilities. It integrates with other Azure services, enabling collaborative work for data engineering, data science, and machine learning workflows.

Azure Stream Analytics

A real-time analytics service designed to process and analyze streaming data from various sources such as IoT devices or social media streams. It provides insights with low latency, making it ideal for use cases like fraud detection and monitoring.

Azure SQL Database and SQL Data Warehouse

Fully managed relational database services that support data storage and querying for analytics. These services offer scalability, high availability, and integration with other Azure data services.

Azure Cosmos DB

A globally distributed, multi-model database service that allows the ingestion of high-velocity data and scales across multiple regions for low-latency, high-availability access.

Azure Machine Learning

A platform for building, training, and deploying machine learning models. Data engineers and scientists can collaborate to turn data into actionable insights using machine learning algorithms.

Azure Event Hub and Azure IoT Hub

Services designed for ingesting large amounts of event or telemetry data from IoT devices, applications, or other systems. These services integrate with Azure’s analytics and data storage tools.

Azure Data Engineering Workflow

work flow diagram
Azure Cloud

Who We Are?

Object Automation System Solutions Inc is a transformation partner that focuses on enhancing customers' vision and growth by understanding their key business drivers, enterprise needs, go-to-market models, pricing and partnership models, and network slicing and exposure journey.

What We Do?

Our Service Offerings:

When considering offers to provide around Azure Data Engineering, we can tailor them based on requirements and the needs of clients. We provide from consultation and implementation to support and optimization:

Data Strategy Consultation and Assessment

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  • Offer: Provide an in-depth consultation to help clients assess their current data architecture and suggest a roadmap for Azure Data Engineering adoption or optimization.
  • Details:
    • Audit of existing data pipelines, storage solutions, and analytics practices.
    • Recommendations for migration to Azure Data Engineering or improving current infrastructure.
    • Cost-benefit analysis and ROI estimation of adopting Azure services.

End-to-End Data Pipeline Implementation

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  • Offer: Build and deploy data pipelines from scratch using Azure Data Factory, Azure Databricks, and other Azure services.
  • Details:
    • Designing, building, and automating ETL/ELT pipelines.
    • Data ingestion from multiple sources (on-premise, cloud, IoT, etc.).
    • Data transformation, cleansing, and storage in Azure Data Lake or Azure SQL Database.
    • Real-time and batch processing options

Data Migration to Azure

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  • Offer: Migrate on-premise or other cloud-based data warehouses and lakes to Azure, ensuring minimal disruption.
  • Details:
    • Secure, seamless migration of data from traditional systems (e.g., SQL Server, Oracle) or other cloud platforms (AWS, Google Cloud) to Azure.
    • Use of Azure Migrate, Azure Data Factory, and other Azure tools to ensure a smooth transition.
    • Performance tuning and optimization post-migration.

Data Lake Design & Optimization

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  • Offer: Design and optimize Azure Data Lake Storage (ADLS) for efficient data storage and management.
  • Details:
    • Setting up scalable, cost-effective data lakes using ADLS.
    • Implementation of data security, governance, and compliance policies.
    • Integration with Azure Synapse and other analytics services.

Real-time Data Processing Solutions

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  • Offer: Build real-time data streaming and analytics pipelines using Azure Stream Analytics and Event Hubs.
  • Details:
    • Design and implement real-time data ingestion and processing workflows.
    • Use of Azure Event Hubs or IoT Hub for handling large-scale event and telemetry data.
    • Real-time dashboards and reporting using Power BI or third-party tools.

Machine Learning Pipeline Deployment

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  • Offer: Build and deploy machine learning pipelines integrated with Azure Data Engineering workflows.
  • Details:
    • Integrate data engineering workflows with Azure Machine Learning for predictive modeling, forecasting, and AI-driven analytics.
    • Design and deploy machine learning models in production using Azure Databricks and Azure ML.
    • Support for automated model retraining and scaling.

Managed Data Engineering Services

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  • Offer: Ongoing management and monitoring of Azure Data Engineering workflows.
  • Details:
    • 24/7 monitoring of data pipelines for failures or performance issues.
    • Regular tuning and optimization of data processing workflows.
    • Backup, recovery, and disaster recovery planning.
    • Service-level agreements (SLAs) for availability and performance.
    • Auditing, logging, and monitoring for secure data access and usage.
    • Optimization strategies for resource usage, such as serverless options, storage tiers, and auto-scaling.
    • Cost-saving techniques by leveraging pay-as-you-go pricing and reserved instances.

Training and Upskilling Services

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  • Offer: Provide hands-on training and workshops for client teams on Azure Data Engineering tools.
  • Details:
    • Tailored workshops on using Azure Data Factory, Synapse Analytics, Databricks, and other services.
    • Best practices for designing and managing data pipelines.
    • Training on monitoring, security, and optimization within Azure.

Curriculum/Courses

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Our Azure Data Engineering Curriculum empowers numerous professionals and scholars in mastering comprehensive web technologies.

Download Curriculum for Azure Data Engineering

Why Choose Us?

Our Focus, Quality and Agility in Advisory, Solutioning and Execution partnership

  • Deliver faster and secured Services
  • Understanding the customer's challenges.
  • Developing the appropriate value proposition.
  • Pricing Strategy.
  • Proposing customer solutions.
  • Technology solution partner strategy.
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Would you like to dive deeper into any specific technology within Azure Data Engineering?
Reach our team hr@object-automation.com