What Is Data Orchestration: Definition, Uses, Benefits
Data is one of the most valuable business assets. It’s the oil of our age.
Data is critical for day-to-day operations, product development, marketing, and more.
Data orchestration allows you to manage big data in a consistent, accurate, and predictable way.
Company databases continue to expand exponentially with more and more data to make use of.
In this blog post, we will cover the definition of data orchestration, how to do it and why it’s important.
What is data orchestration?
Data orchestration is the automated process of acquiring, cleaning, matching, enriching, and making data accessible across technology systems.
Data orchestration is a process that consolidates data from numerous storage locations and combines it in a rational manner so that it can be used by a company’s data analysis and management platforms.
Data orchestration makes it easier for businesses to access, manipulate, store, and analyze information.
Data orchestration tools can help reduce the cost of managing and analyzing data, while also making it easier to access real-time insights.
By automating these processes, organizations are better equipped to make more informed decisions based on the insights they derive from their data.
What kind of businesses need data orchestration?
Big tech organizations and corporations with multiple data systems and silos need data orchestration.
4 elements of data orchestration
The data orchestration process consists of 4 parts: preparation, transformation, cleansing, and syncing.
Preparation includes performing checks for integrity and correctness, applying labels and designations, or enriching new third-party data with existing data sets. Prepared data is structured and organized before it is input into the software used for data orchestration.
Transformation refers to converting data into a standard format. For example, the same date can be written in a variety of ways: March 15, 1990; 3/15/90; 15/3/90; etc. During the transformation process, these dates are converted to the same format. Once the transformed data is categorized and enriched, it can be leveraged for decision-making purposes.
Cleansing involves locating and correcting (or eliminating) corrupt, inaccurate, duplicated, or outlier data.
Syncing refers to the continuous process of updating data between data sources and destinations for consistency. Think of how your phone and computer might sync so contacts, text messages, and photos are on both devices.
Benefits of data orchestration
Leveraging data orchestration provides a host of benefits including:
- Better understanding
- Data governance
- Data security
- Real-time information
- Faster insights
- Cost efficiency
Scalability – Data orchestration is a cost-effective way of automating synchronization across data silos, enabling organizations to scale data use.
Better understanding – Better data organization leads to better understanding. This involves setting up a structure that makes sense for your business and understanding the purpose of each data set. Once you’ve established a data structure, make sure to document all your procedures for accessing, manipulating, and analyzing it. Data analysis is a critical part of being able to manage your data effectively.
Data governance – Data orchestration helps businesses stay in conformity with data privacy laws like the GDPR and CCPA. The legislation protects customer data collected by organizations and mandates that data collection times, location, and the reason for data collection are specified.
Data security – This is essential for avoiding potential threads and keeping customers safe. To do this, make sure to have a robust security system in place that covers everything from authentication and authorization to encryption and firewalls.
Furthermore, ensure that all of your employees understand the importance of data security and are properly trained on how to handle data responsibly.
Real-time information – Real-time data can be extracted and processed at the moment it’s created
Faster insights – Automated data orchestration streamlines data workflows so you can get business intelligence and actionable insights fast.
Cost efficiency – Automated data management will reduce manhours for costly IT professionals. The cost saved can be channeled into innovative pursuits that will advance your business.
The databases for companies continue to expand exponentially, and there is always more data to leverage and make use of than before.
Data usually comes in large quantities, which is why it can be difficult to manage it effectively.
Moreover, with the increase in data volume, it can be easy to lose track of its usage and purpose.
Ensuring that you can properly control your data is essential.
Whether this is through data orchestration tools we linked to above, or your own processes, having the right measures in place is key.
By having an understanding of what your data tells you about your business, you are better equipped to make decisions that will benefit the company in the long run.