Platforms > Azure Data Factory

Azure Data Factory Consulting

Alphabyte is an Azure Data Factory consulting firm. We design, build and support data pipelines that move data from your ERP, CRM, databases and files into Azure, keep it current on a schedule and alert your team when something fails, so reports start from complete, accurate data.

Our data engineers handle the full pipeline, from source assessment to monitoring.

Success Stories

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What We Do

Azure Data Factory consulting for organizations whose pipelines must stay reliable as sources change and data grows.

Azure Data Factory, often shortened to ADF, is Microsoft's cloud service for building and scheduling data pipelines. It connects to on-premises and cloud sources, copies and reshapes data, and loads it into targets such as Azure SQL, Azure Synapse Analytics or Snowflake. Building a first pipeline is quick. Keeping dozens of them reliable is the hard part.

That is where an Azure Data Factory consultant helps. We plan the pipeline architecture, build ingestion and ETL pipelines with error handling and retries, and set up monitoring so failures are caught early. Every pipeline follows our ETL best practices, with documented business rules and automated quality checks.

For on-premises work we also build with SQL Server Integration Services, for an all-in-one analytics platform we work with Microsoft Fabric, and on AWS we use tools such as AWS Glue.

01

ETL Pipeline Development

Pipelines that load clean, rule-checked data into Azure SQL, Snowflake or other warehouses.

02

Automated Data Pipeline Design

Scheduling, dependencies and alerts so data arrives on time without manual steps.

03

Cloud & Hybrid Data Integration

On-premises systems connected to Azure without disrupting the operations that rely on them.

04

Data Ingestion Pipeline Implementation

High-volume ingestion from APIs, databases and files, with schema validation at entry.

05

Enterprise Data Integration

ERP, CRM, marketing and operational data combined into one trusted source.

06

Azure Data Factory Performance Optimization

Tuning, parallel processing and cost reviews for pipelines that have outgrown their design.

07

Scalable Data Integration Architecture

ADF with Data Lake, Synapse and Azure SQL, built to grow without a rebuild.

08

Pipeline Monitoring & Ongoing Support

Logging, alerts and ongoing support that catch slowdowns and failures before reports do.

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Our Approach

  • We catalogue your data sources and note volumes, how often each must refresh, the business rules applied today and the reports and systems that use the data. We also list manual exports and fragile scripts that pipelines should replace. Discovery usually takes 1 to 2 weeks and ends with agreed technical and business requirements.

  • We design the pipeline architecture, covering orchestration, incremental loading, data partitioning, error handling and where business rules should run. We also plan the integration runtime for on-premises sources and the target, such as Azure SQL or a data lake. You approve the blueprint and release plan before any build work begins.

  • We build pipelines with Data Factory's visual designer and with code where it helps, then test data accuracy, business rules and performance under realistic volumes. Results are reconciled against each source system. A first phase usually takes about 4 to 10 weeks, depending on the number of sources and how clean their data is.

  • We deploy through CI/CD pipelines with version control in Azure DevOps, so every change moves from development to test to production the same way. Access, authentication and network controls are configured to your security standards. Each release is repeatable and auditable, and can be rolled back if something unexpected appears after launch.

  • We configure Azure Monitor and Data Factory's own monitoring to track every run, surface bottlenecks and alert on failures. After launch we review run times and costs, tune slow activities and adjust schedules. Your team gets clear visibility into data operations and hears about a failed load before anyone sees a wrong number.

  • We hand over documentation covering data flows, business rules, schedules, dependency maps and troubleshooting steps, then walk your team through it. The aim is that your engineers can maintain, extend and tune the environment on their own. If you prefer, we can stay on for ongoing support and new data sources.

Azure Data Factory Success Stories

E-Commerce

Annmarie Skin Care’s challenge is common and is experienced by e-commerce shops across the spectrum: while relying on 3rd party applications provides quick access to the functionality necessary to run its shop, it creates scattered environments of data that make it difficult to gather meaningful insights.

E-CommerceRead More

Pharmaceutical Custom ERP

NutriOriginal had a complex set of requirements touching on multiple facets of its business; it explored out-of-the-box ERPs, but could not find an enterprise solution that checked all of the boxes. NutriOriginal sought Alphabyte’s expertise in implementing an Enterprise Resource Planning (ERP) platform

Pharmaceutical Custom ERPRead More

Your Azure Data Factory Consulting Team

Pipelines work best when the team that builds them also understands the warehouse and reports they feed. Alphabyte is a Microsoft Solutions Partner, founded in 2015, and has served 100+ organizations. We work with mid-market companies, large enterprises and public sector organizations. Our engineers have built production pipelines handling millions of records, integrated complex hybrid cloud environments and designed data architectures that support enterprise-wide analytics and reporting.

Our team holds Microsoft certifications including Azure Solutions Architect Expert and Azure Administrator Associate. See the full list on our certifications page.

We work with mid-market and enterprise organizations. Related services: data integration services, Azure managed services and data warehousing services.

Get Started
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Frequently Asked Questions

  • Azure Data Factory is used to move and prepare data. Organizations use it to copy data from ERP, CRM, databases, files and APIs into Azure, apply business rules, and load the result into a data warehouse or data lake on a schedule. It also orchestrates other steps, such as running stored procedures, so a full nightly load runs as one monitored process.

  • An Azure Data Factory consultant designs and builds the pipelines that move your data. That covers assessing sources, planning the architecture, building ingestion and ETL pipelines, setting up integration runtimes for on-premises systems, deploying through CI/CD and configuring monitoring. At Alphabyte our consultants also reconcile results against source systems and document everything, so your team can run the pipelines with confidence.

  • Most organizations look for help when pipelines fail without warning, when loads run too long or cost more than expected, or when a new warehouse needs data from many sources. Other common triggers are a move from on-premises SQL Server to Azure, a backlog of manual exports, or a first ADF build that has grown hard to maintain.

  • Cost depends on the number of data sources, whether they offer modern connectors, data volume, how often data must refresh and how much cleanup is needed. Azure usage for Data Factory is billed separately by Microsoft. We scope the work with you after discovery, often starting with the sources that matter most, so you see results early and can plan later phases with real information.

  • SSIS is an ETL tool that runs on SQL Server, usually on your own servers. Azure Data Factory is a managed cloud service with connectors for cloud and on-premises sources, and it can run existing SSIS packages in Azure. SSIS suits stable on-premises work, while ADF suits cloud and hybrid environments. We work with both and can help you choose.

  • Microsoft Fabric is a wider Microsoft data platform that brings pipelines, storage, warehousing and Power BI reporting together. Its pipelines share much of their design with Data Factory. ADF suits organizations that want a dedicated integration service alongside existing Azure databases. Fabric suits teams that want one platform for analytics. We help you compare them for your data and team.

  • A first phase usually takes about 4 to 10 weeks after a discovery phase of 1 to 2 weeks, depending on how many sources are involved and how clean their data is. A single pipeline can be quicker. Larger programs are delivered in phases, with the most valuable sources connected first and further sources added in later releases.

  • Yes. Data Factory uses a self-hosted integration runtime, a small service installed inside your network, to reach on-premises databases and file shares securely. We plan where it runs, how it is secured and how it scales, so hybrid pipelines move data between legacy systems and Azure without disrupting the operational systems that depend on them.

  • Yes. Many projects start with pipelines someone else built. We review each pipeline for failures, slow activities, duplicate work and unnecessary cost, then tune, refactor or rebuild what needs it. We add the logging, alerts and documentation that are often missing, so your team understands what each pipeline does and can keep it running.

  • An in-house hire suits steady work on pipelines that already run well. A consulting team covers architecture, ADF pipeline development, security, CI/CD and monitoring, which helps when you are building a new platform, moving off on-premises servers or fixing pipelines that fail often. Some clients use us to build the foundation, then hand routine changes to internal staff.

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