In today’s fast-paced business environment, executives are under increased pressure to deliver quick wins and measurable results. However, one capability that is often overlooked is data orchestration.
This oversight can sabotage progress as the promise of data modernization efforts fail to deliver expected outcomes in terms of ROI and improved efficiencies.
In this article, we will explain what data orchestration is, the risk of not implementing proper data orchestration, and how executives benefit from end-to-end data orchestration.
What is Data Orchestration?
Generating insights is a multi-step process. There are usually steps to ingest data, validate, cleanse, and transform the data to answer business questions. Finally, insights are delivered via dashboards and reports or data is pushed to systems for marketing automation or to external partners. Each of these steps may require a different tool.
What’s the problem with this setup? Each of these tools may include its own scheduler, and they will each run in a silo. Even if an upstream step fails or is delayed, the subsequent steps will run. This disconnect leads to surprises for executives expecting trusted insights. This in turn, leads to delays and data fires, which are disruptive and inefficient for the organization.
Imagine you are baking a chocolate cake. You would need a recipe, all the ingredients, and a functioning oven. However, you wouldn’t turn on the oven before buying the ingredients and mixing the batter if your milk had spoiled. Not having someone orchestrating all the steps in the right sequence would lead to a disorganized process that is inefficient and wasteful. You also know not to continue if there is a critical issue, such as spoiled milk.
Data orchestration solves the problem of having siloed tools by connecting all the steps in the data value chain. This way, if one step is delayed or fails, subsequent steps do not run. With a data orchestration tool, we can also notify someone to resolve the issue so they can act quickly, reducing fires and providing visibility to the entire process.
Why Executives Should Care about Data Orchestration
Executives make many decisions but rarely have the time to dive into technical details. They delegate research and expect quick wins. This creates mixed messaging. On the one hand, they want resilient, scalable, and future-proof solutions that address stakeholder concerns; on the other, they demand speed to deliver “something now.”
Vendors often leverage this tension to their advantage. Their tool may address an issue in the data value chain, but it is not in their best interest to explain how their solution won’t address the problems that stem from siloed tools and processes. Their goal is to close the sale; the executive is left with the consequences, and the stakeholders experience little improvement.
Stakeholders want to eat the chocolate cake. Focusing on a part of the process without considering data orchestration is like buying a new oven while ignoring whether the milk for the cake has spoiled. The result of changing a component may be ushered in with much fanfare, but the result is still compromised
A large Datacoves customer described the difference like this: “Before, we had many data fires, which were disruptive to many in the organization. Now, it’s not that issues don’t occur, it’s that we can catch them immediately and we can prevent bad data from reaching stakeholders.”
With data orchestration, adding new steps to the data flow is straightforward, auditing the value chain is simple, and identifying improvements becomes possible. The payoff is higher efficiency, fewer disruptions, and greater trust across the organization.
The Risks of Ignoring Data Orchestration
It is tempting to postpone data orchestration until the weight of data problems makes it unavoidable. Many companies take the “quick start” approach only to discover that the cost of moving fast was long term lack of agility and technical debt. A great example is Datadrive’s journey, before adding data orchestration, when issues occurred, they had to spend time debugging each step of their disconnected process. Now it is clear where an issue has occurred, enabling them to resolve issues faster for their stakeholders.
It is common for processes to be reworked because achieving the original business goals requires full visibility and control across the data lifecycle. Improving one step alone cannot deliver the desired outcome, just like a single egg cannot make a cake.
Organizations that lack data orchestration are in effect flying blind. Disconnected processes run out of order and issues are discovered by frustrated stakeholders. Resource-constrained data teams spend their time firefighting instead of delivering new insights. The result in delays in decision-making, higher operating costs, and an erosion of trust in data.
How Executives Can Unlock Value with Data Orchestration
If data orchestration is so important, why do organizations go without it? We often hear some common objections:
1. Lack of awareness
Many organizations have not heard of data orchestration and tool vendors rarely highlight this need. It’s only after a painful experience that they realize this essential need.
2. “It will add complexity”
It’s true that data orchestration adds another layer, but without it you have disconnected, siloed processes. The real cost comes from chaos, not from coordination.
3. “Another tool makes things harder”
Vendor sprawl can indeed introduce additional risks, that’s why all-in-one platforms like Datacoves reduce integration overhead by bundling enterprise-grade orchestration, like Airflow, without increasing vendor lock-in. Explore Datacoves’ Integrated Orchestration Platform.
4. “Data Orchestration makes processes more complex”
Data value chains are inherently complex, with multiple data sources, ingestion processes, transformations, and data consumers. Data orchestration does not introduce complexity; it provides visibility and control over this complexity.
It may seem reasonable to postpone data orchestration in the short term. But every mature data organization, both large and small, eventually needs to scale. By building-in data orchestration into the data platform from the start, you set up your teams for success, reduce firefighting, and avoid costly and time-consuming rework. Most importantly, the business receives trustworthy insights faster.
Conclusion
Data orchestration should not be seen as a “nice to have” feature that can be postponed. Mature organizations understand that it is the foundation needed to deliver trusted insights faster. Without it, companies risk setting up siloed tools, increased data firefighting, and eroding trust in both the data and the data team. With it, organizations gain visibility, agility, and the confidence that insights fueling decisions are accurate.
The real question for strategic leaders is whether to try to piece together disconnected solutions, focusing only on short-term wins, or invest in data orchestration early and unlock the full potential of a connected ecosystem.
For executives, prioritizing data orchestration will mean fewer data fires, accelerated innovation, and an environment where trusted insights flow as reliably as the business demands.
Don’t wait until complexity forces your hand. Your team deserves to move faster and fight fewer fires. Book a personalized demo and see how data Orchestration with Datacoves helps leaders unlock value from day one.
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