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Data Orchestration to Get the Most from Your Data in 2024

Gulbahar Karatas
Updated on Jan 2
2 min read

Gaining valuable insights from business data requires high-level analytical capabilities and successful data management is critical to improving an organization’s analytical skills. Data orchestration automates data management processes by automatically ingesting data from multiple sources, merging it into a central repository, preparing it, and making available data to all internal tools. It assists companies in:

  • collecting real-time data from multiple sources
  • combining, organizing, and preparing collected data for data analysis
  • preventing possible data issues such as data silos, and data fragmentation.

Data collection

When a customer engages with an organization’s service or product, each touchpoint can generate new data. The data generated can be stored in silos or siloed over time. Siloed data is not fully accessible to other departments and creates information barriers between departments. 

Data orchestration tools automatically collect data in real-time from all different sources to keep organizational data up-to-date and establish data governance to centralize data access for all groups within an organization. They simplify the implementation of a data governance strategy by connecting all data systems across the organization. Data orchestration tools ensure that incoming data complies with the organization’s data governance strategy, otherwise, these data sources are blocked.

Data preparation and transformation

Data orchestration tools collect data from different types of sources, and these sources may contain different types of data. In this case, not all collected data can be used in the same system, so they need to be handled differently. Data from diverse systems is transformed into a compatible and consistent format by an orchestration tool to ensure that it works within a specific task. If the properties of the collected data are not standardized, orchestration tools check the properties of the incoming data and standardize its properties and values. For example, customer names are one of the values of data, and all names should be checked and transformed based on an internal standard data schema. If there are outliers, they are removed by the orchestration tools.

Data unification

After converting the collected data into a compatible and consistent format, the orchestration system creates a single and unified view of all customer profile data. It ingests customer data in real-time and keeps the data updated to show the current state of the customer profile.

It brings together all the data collected from all the company’s sources, such as websites, applications, and other touchpoints.


Once unified profile data is created, data orchestration makes this information available to the tools used by the company’s teams on a daily basis. The transformed data is sent to data storage systems such as data warehouses, databases, or data lakes. From here, the orchestration tools make the data available to all teams and their internal systems. There is no need to load data into your system. 

Further Reading

If you have any further questions about data orchestration, we would like to answer them:

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Cem Dilmegani
Principal Analyst
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Gulbahar Karatas
Gülbahar is an AIMultiple industry analyst focused on web data collections and applications of web data.

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