Data Orchestration 101: Benefits, Parts & Example 2026
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Astronomer aims to set up end-to-end lineage so that its customers can observe and add context to disparate pipelines. Astronomer builds data orchestration tools like Astro using Apache Airflow™ — originally developed by Airbnb to automate its data engineering pipelines. Data orchestration tools automate the process of bringing data together from multiple sources, standardizing it, and preparing it for data analysis. Before we begin, let’s quickly look into data orchestration tools and their capabilities. Data orchestration tools automate and streamline data workflows, integrating and managing data pipelines from diverse sources to ensure seamless, real-time access across platforms. Holder of an MBA in Digital Marketing and Business, he is passionate about SEO, e-commerce and artificial intelligence.
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Flyte is a workflow automation platform built to help ML and data engineers build robust and reusable pipelines. To understand the business impact of Control-M, let’s explore the Carrefour case study. As a result, Milliman could launch its platform at scale, while reducing IT and data management costs considerably. Azure Data Factory helps Milliman automate workflows for data integration and transformation using multiple data sources.
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In Atlan's AI Labs benchmark, adding that context improved AI's text-to-SQL accuracy by 38%. For orchestration in data engineering Data Revenue, a key requirement (besides workflow orchestration) was native Kubernetes support. The company’s backed by Tiger Global Management, Bessemer Venture Partners, and Atreides Management. So, Future Demand chose Metaflow to help its data scientists build, deploy, and manage their code with end-to-end visibility and zero engineering intervention.
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Case study: Carrefour drives proximity store growth with Control-M
Spotify’s finance team must prepare P&L projections for two years into the future, which involves collaborating with 8+ teams and running 15+ models to analyze each business unit. Let’s explore the Spotify case study to know how Flyte solves their challenges. Today, Ketan Umare heads Union Systems Inc. that’s building a managed version of Flyte.
- It sounds simple, but in practice it’s anything but.
- Mage is one of the best data management tools when it comes to visibility, especially regarding scheduling and managing data pipelines.
- They unify data from diverse centers, including cloud services, legacy systems, and data lakes, into a single, accessible platform for analysis.
- It ensures that ingestion, transformation, validation, and delivery all happen in the right order, under the right conditions, and with clear visibility into success or failure.
- Dagster is a versatile data management and orchestration tool that comes in handy during each stage of the data development cycle.
ETL isn’t an alternative to data orchestration; it’s the canonical example of it. For example, a cron job that copies a file every night is a simple automation. Utilizing ETL or ELT processes, data engineers can ensure that data is not only stored but also ready to be analyzed in a cohesive and comprehensive manner. At this stage, the integration of data from various sources becomes paramount. We’ll examine how data orchestration empowers data engineers and data scientists to build reliable, scalable, and efficient data pipelines, ultimately enabling organizations to unlock the full potential of their data assets.
That operational work pulls data engineers away from building pipelines. Running it in production means managing kubernetes, scaling components, handling infrastructure upgrades, securing access, and maintaining observability across environments. Airflow is straightforward to start with for a single team. Other tools in the category include cloud-native schedulers and newer Python-based frameworks, each with different tradeoffs around flexibility, ecosystem, and operational overhead. However, AI orchestration doesn’t replace data orchestration, it runs inside it.
Milliman found that actuarial firms were spending about 70% of their time managing data — updating models, creating files, and running reports. Traditionally, Zalora’s engineering and DevOps teams handled this process manually, which took up around 5 days and involved several manual errors. To understand how Airflow helps Wise with orchestration, check out the complete case study here.
Once it’s ready to use, it can be transferred to a CRM or emailing platform to launch a targeted campaign. What are the concrete use cases for data orchestration in marketing? Overall, effective orchestration helps businesses make better use of their data and generate greater value.
It's the automated coordination of data moving through your systems, making sure each step runs in the right order, depends on the right inputs, and retries when a step hits a transient failure. It runs the infrastructure for you, scales resources automatically, and adds enterprise features like cross-environment observability, role-based access control, and audit logging. Astro, built by Astronomer, is a fully managed data orchestration platform powered by Apache Airflow.
A specialist in digital marketing and customer relations, Olivier shares his experience in digital and growth strategies. A secure, compliant cloud architecture (GDPR, CCPA, etc.) makes it easier to manage orchestration workflows safely and efficiently. Of course, it’s essential to control data access and manage permissions based on user roles. A Customer Data Platform (CDP) supports this approach by enabling more efficient and consistent actions across the entire customer journey.
Vacation rental company Home Away was building apps for global travelers, complete with a real-time recommendation engine. Let’s delve into the Home Away case study to understand the problem Cloud Functions solves. Cloud Functions is a pay-as-you-go functions as a service (FaaS) product from Google Cloud Platform by Alphabet Inc. Today, Spotify uses Flyte to build its financial reports automatically. Spotify’s financial team wanted to automate the business casing and scenario analysis, and that requires a tool to automate the workflows (or pipelines).