What is the Data Orchestration Process?
Organizations’ appetite for data never seems to be satisfied. Over the last few years, however, companies’ eyes have grown larger than their stomachs. They spend inordinate time in the kitchen preparing their own data and excessive money on sustenance from gourmet data “chefs.” Meanwhile, their ability to digest all this incoming data falls further and further behind. Their internal systems are not sophisticated enough and their metabolisms are not fast enough to parse, process, and turn data into energy.
Finding it hard to digest all your data? A low-code ETL offers a maintainable, scalable solution for receiving, using, storing, and activating the data you need to make wise decisions.
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In short, their data orchestration is out of whack.
Defining Data Orchestration
K3 defines data orchestration as a is a formal, often automatic four-step process:
- The coordinated receipt, collation, and use of data from diverse sources coming in various formats, at different times.
- The transformation of this data to consistent taxonomies, sequences, and chronologies so it can be combined, calculated, and analyzed.
- The implementation of data transformation to feed decision-making, create business projections and forecasts, and facilitate strategic rather than transactional production, scheduling, logistical, marketing, finance, and other activities.
- Storing the transformed data for use in future orchestration efforts, as fuel for yet-to-be-developed data science, and trend analysis.
Why Data Orchestration is Hard
In addition to the glut of data pouring into organizations every hour, companies don’t often know where it’s going or how to access it efficiently once it gets there. Data comes from dozens of sources, both external and internal, and must be extracted from and flowed to hundreds of files, databases, data lakes, single-function platforms. Untangling this maze of connections, breaking down their silos, and translating their syntax requires sophisticated, yet accessible technology.
Too many organizations try to handle these tasks themselves, creating proprietary processes that may seem elegant at the time but are nearly impossible to sustain and maintain. That’s why nearly 90 percent of organizations wallow in low business intelligence.
Data orchestration requires a software suite that breaks through silos to manage across systems and platforms so IT teams can automate processes to increase decision times, save storage, retrieval, and computation costs, and reduce data-entry errors. A low-code option like K3’s ETL (extract, transform, load) interface elevates data from a pile of information to a reservoir of actionable insights.
As with any orchestra, data orchestration is the art of coordination. We employ finely tuned K3 connectors, architecture, and business logic in the industry. But all this technological “talent” would be wasted without the platform’s orchestration. The software acts as the conductor, ensuring each instrument plays its part precisely.
Schedule a demonstration and let us show you how to make beautiful music with K3 data orchestration.
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We’ve written before about the rise of data orchestration, the process by which enterprises connect disparate data sources so information flows to a central repository