Current Data Orchestration Trends & Predictions

Data orchestration is becoming more prevalent in many industries, and data orchestration technology is evolving at a rapid pace. See the current trends here.
Last updated
May 2, 2024

Data orchestration is becoming more prevalent in many industries, and data orchestration technology is evolving at a rapid pace. Being able to seamlessly manage data across systems and platforms is key for organizations that want to stay at the top of their industries and make the most of their expensive data collection investments.

In 2024, companies will continue to embrace data orchestration and its benefits. If you want to stay ahead of the curve, it’s best to pay attention to the current and future trends for data orchestration. In this blog, we’ll be taking a look at some of the top trends and predict where data orchestration might be going this year and beyond.

What is Data Orchestration?

Organizations big and small generate large amounts of data from various sources. To effectively use this data, it helps to have tools and platforms that allow you to manage, organize and analyze it.

Data orchestration is a process that allows organizations to collect, transform and analyze data from multiple sources. This helps data reach the right person at the right time, empowering organizations to gain more insights from their data and use it more effectively.

With data orchestration, companies can streamline their data operations, eliminate data silos and make it easier for all employees to utilize data. This leads to numerous other benefits, like better insights for driving revenue, more effective strategies, improved customer experiences and more.

In short, data orchestration is a necessary process in the age of big data. When companies have an effective data orchestration strategy in place and the right tools, they can use their data more efficiently and effectively. In other words, it’s well worth taking the time to invest in a data orchestration strategy. With that being said, let’s dive into some of the biggest trends for data orchestration in 2024 and beyond.

Real-time data processing

Real-time data processing will be one of the biggest trends to take over the world of data orchestration. Companies need to be able to quickly and efficiently process their data, and real-time data processing is the next step in that journey.

Various industries need to be able to gain insights and make decisions in real time, and data orchestration tools are stepping up to the plate to allow them to do so. In hyper-competitive industries, real-time data processing can become a necessity. While this is a more costly data orchestration method, the benefits can be worthwhile for the right organization. 

Industries such as finance and healthcare are embracing real-time processing to streamline operations and make faster decisions. Finance organizations can use real-time processing to stay on top of the markets and make trades and decisions with the most up-to-date price information possible. The health and fitness industry can use real-time data to monitor metrics and detect anomalies or trends in vitals. These are just a few examples of how real-time processing capabilities are improving the capabilities of organizations and opening up more opportunities. Real-time processing is a trend to watch as it continues to develop and evolve.

Data democratization

Data democratization is another key data orchestration trend to keep an eye on in 2024. Data democratization seeks to make an organization’s data more usable and accessible to all users. To do this, there need to be fewer data silos, more intuitive tools, self-service analytics and other measures to make it easier for technical and nontechnical users alike to utilize data in meaningful ways.

Since more industries and organizations are embracing data-driven decision-making, democratization is more important than ever. To achieve true democratization, organizations can take steps such as:

  • Encouraging a data-driven culture — Companies can make data an essential component of their culture rather than a tertiary one. This means encouraging employees to utilize and engage with data and training them on how to use data effectively.
  • Making data accessible — Companies can implement intuitive tools to make it easier for users to access, understand and analyze data.
  • Investing in data literacy — By investing in training and knowledge-building, organizations can help employees understand data tools, sharpen their analysis skills and truly understand the data they work with daily.

In short, data democratization is about giving users the tools, knowledge and empowerment they need to use data efficiently and effectively. Embracing data democratization will be a necessary trend for companies that truly want to make the most of their data.

Artificial Intelligence and Machine Learning

Artificial intelligence and machine learning have become mainstream in recent years, and data orchestration will also see a greater emphasis on these technologies. With AI and machine learning, organizations can automate many of the processes for collecting and managing large volumes of data.

While automation tools have been used for years in data orchestration for simple tasks, the increased capabilities of AI and machine learning mean that these automation tools will be able to be trained to handle more complex data management tasks. This allows teams to focus on more strategic tasks and avoid some of the more tedious aspects of data management. 

AI and machine learning can also help to improve data quality and reduce human error that can happen in manual data management. Additionally, machine learning can be used to identify patterns, correlations and more. In short, automation can help increase efficiency, improve insights and put more time in the hands of users. 

Tools like Secoda AI make it even easier for organizations to implement AI in their data orchestration processes. Secoda AI allows companies to stack OpenAI on top of their metadata and get contextual search results from across your tables, columns, dashboards, metrics, queries and more. Users can also automate tasks like turning text to SQL, generating data documentation, tagging PII data, tagging columns and more.

Low-code data integration

Another growing trend in data orchestration is low-code data integration. Low-code data integration allows organizations to easily integrate data from multiple sources with little to no code. This lessens reliance on IT teams and shorter development cycles when implementing new data sources.

These low-code data integration tools have intuitive UIs and allow users to easily plug in other tools and data sources. Nontechnical users can also create custom workflows using these tools, thanks to pre-built connectors. For pre-built connectors that don’t exist, IT teams can still build custom APIs to connect data sources. 

Low-code data integration makes it easier to streamline data operations. There is less manual data importing, less tedious work for IT teams and more integrated workflows that deliver data where it needs to go. This method of data integration also offers cost savings since there is less time spent on development cycles, manual coding, debugging and other tasks. This allows organizations to get their data integration projects up and running faster.

In short, low-code data integration simplifies data integration at a micro and macro level. Organizations can leverage these tools to increase productivity, improve data literacy, streamline operations and save money.

View data as a comprehensive product

Organizations need to have a more comprehensive, holistic view of the data they collect. This may mean treating data as a product rather than focusing on just the pipelines that deliver data. Prioritizing data products and assets can improve insights and ensure the smooth operation of data orchestration processes.

Organizations are harnessing this product-focused view by taking a declarative approach in data pipeline management, reusing code with abstractions in cloud environments and leveraging modern data engineering tools.

Data governance and compliance

In an increasingly complex data landscape, businesses need to ensure they are properly governing and complying with regulations surrounding their data usage. This includes understanding and adhering to industry-specific regulations, as well as broader laws such as GDPR and CCPA. When you create a data orchestration strategy, paying attention to the latest compliance regulations will be essential. Fortunately, data orchestration helps make it easier for organizations to automate compliance.

Data governance can also be improved with data orchestration. Data governance ensures your data is properly managed, protected and utilized. It can include everything from data integrity to access control.

While data governance and compliance can be easier with automation tools, democratization also means that data is more accessible and usable by a wide range of users. Governance and compliance will continue to be essential components of any data orchestration strategy. In 2024 and beyond, more technologies will continue to emerge to help organizations with their compliance and governance efforts.

It will be interesting to see how this area continues to evolve in the coming years. Overall, it helps organizations pay attention to all the data orchestration trends as big data continues to grow and become more integral to regular operations. By paying attention to the trends, you can ensure your organization maintains a competitive edge and gets the most out of your data investments.

To that end, it also helps organizations use the right tools to help with their data orchestration efforts. Secoda is a great tool for organizations that want to improve their data orchestration strategy.

Try Secoda for Free

Secoda is the ultimate tool for improving data orchestration. Secoda is easy to integrate with your current data stack and offers several tools for artificial intelligence, data democratization and more. It is an all-in-one platform that contains tools for data discovery,  documentation,  sharing,  access management,  lineage, monitoring, and data cataloging. Ready to see how Secoda can help with your data orchestration? Try Secoda.

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