In today’s digital enterprise, data is both the fuel and the friction. Every business relies on data to make informed decisions, personalise experiences and deliver faster outcomes. Yet, as data volume, velocity and variety explode across hybrid and multicloud environments, many organisations are finding that their biggest challenge isn’t collecting data – it’s orchestrating it.
The art of DataOps
DataOps isn’t a tool, it is a discipline focused on improving the communication, integration and automation of data flows across an enterprise. It applies DevOps principles of agility, automation and collaboration to the world of data.
At its best, DataOps eliminates silos between data pipelines and business outcomes. It makes data workflows repeatable, reliable and observable, ensuring that analytics, AI and decision-making are powered by the right data, every time.
But achieving this in practice is difficult. Data pipelines today span hundreds of tasks across platforms like Snowflake, Databricks, AWS, Azure, Google Cloud and on-premises systems. Without orchestration and control, teams spend more time firefighting than innovating.
Organisations adopting DataOps benefit from:
- Accelerated time-to-insight by reducing data pipeline bottlenecks.
- Improved data quality through automated validation and testing.
- Enhanced collaboration between data engineers, analysts and business users.
- Increased agility in responding to evolving business needs and data sources.
Orchestration: A catalyst for DataOps success
Organisations are looking at bridging the gap between DevOps and DataOps – helping those organisations to move from data chaos to data confidence. If we dig a little deeper into what these core capabilities look like that orchestration embeds to amplifying the power of DataOps, we can see the below:
1. Unified orchestration across the data ecosystem
The ability to connect and automate the entire data journey – from ingestion and preparation to transformation, validation and delivery. Whether you’re moving files through a file transfer platform, transforming data in Snowflake or Databricks, or triggering analytics jobs in Power BI, organisations need to ensure that every workflow runs in the right sequence, with the right dependencies and at the right time.
2. Built-in data assurance
Data validation is an important part of the pipeline, not an afterthought. This means teams need to automatically verify that data is complete, accurate and within expected thresholds before it flows downstream. The result: fewer failed reports, faster issue resolution and more confidence in business-critical data.
3. DevOps agility for data pipelines
Developers want to treat data workflows as code – versioned, re-usable and integrated into CI/CD pipelines. This brings true agility to data operations, empowering teams to release and update data pipelines faster while reducing errors and manual intervention.
4. End-to-end visibility and governance
Visibility is a necessity, and the requirement needs to cater for a single pane of glass, where data and IT teams can monitor data workflows across all environments – mainframe, on-premises and cloud. Operational insights, SLA tracking and predictive analytics to prevent issues before they impact downstream systems or decision-making is critical to orchestrating successful data pipelines.
The value proposition: Why DataOps with Control-M is a game-changer
By combining DataOps methodologies with an intelligent orchestration platform, organisations can:
- Boost efficiency: Automate repetitive and error-prone data tasks while maintaining full operational control.
- Enhance reliability: Proactively detect and resolve failures to ensure consistent and accurate data delivery.
- Scale seamlessly: Manage growing data volumes and increasingly complex workflows without loss of performance.
- Drive business outcomes: Deliver trusted, up-to-date data faster, enabling better decisions and competitive differentiation.
Why it matters
In an era where time-to-insight equals competitive advantage, the organisations winning with data are the ones that have mastered DataOps – not as a buzzword, but as a discipline. They understand that delivering trusted, timely data to every corner of the business isn’t just an IT goal – it’s a business imperative.
The future of DataOps
DataOps is essential for modern data-driven enterprises, but its true power is realised when paired with a scalable, intelligent orchestration platform where, together, they can transform complex data challenges into competitive advantages, making organisations faster, smarter and more resilient in today’s digital economy.
Transform the way your organisation handles data.
Connect with Blue Turtle to see how Control-M and DataOps can streamline your pipelines, strengthen governance and deliver trusted data where it matters most.
Email info@blueturtle.co.za
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