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IoT data orchestration: accelerating the digital transformation with data analysis

Today, all companies collect a large quantity of data of various kind, relating to operational processes, business movements, market situation, or customers. Precisely because it comes from different sources and its nature can differ wildly, data is often stored in separate archives that have no contact points. But to make the most of it, it needs to be managed in a harmonious way: the key to it is data orchestration.



When it comes to data, companies are immature

Gartner says that over 87% of companies have low business intelligence and analytics maturity, which prevents them from getting the most out of their data. Unfortunately, improving business intelligence and analytics maturity is not easy. Gartner suggests solving the problem by abandoning the logic of storing data in isolated and static silos, in favor of reasoned data governance. Easy to say, but not so easy to do: acting according to Gartner’s recommendations can mean facing a very complex process.


However, it is an undisputed fact that data is fast becoming one of the most crucial assets available to a business: it is fundamental for day-to-day operations, product development, marketing, and more. Data feeds the analyses that optimize business processes and decisions. Furthermore, the fact that AI and machine learning algorithms are increasingly effective makes the information that can be extracted from data even more valuable. In addition, the need for data-driven business models will continue to increase as consumer expectations, market pressure, and technologies evolve. Therefore, the ability to use data more effectively can generate a true competitive advantage in today’s digital economy. However, companies that until now have stored their data in siloed systems find it extremely difficult to implement effective data governance because there are too many systems to keep track of. This can be solved by data orchestration.



Data orchestration: what is it?

With data orchestration we mean the centralized control of the processes that manage data through disparate systems, such as data centers or data lakes. Basically, data orchestration is an automated process that takes data from multiple storage locations and allows you to programmatically create, plan, and monitor the pipelines of that data. Data orchestration platforms create a perfectly “in-tune” data management “orchestra”, giving the ability to monitor the systems, perform detailed analytics, and acquire insights in real time.


Data orchestration tools provide the integration capabilities that IT teams need to develop and manage data processes that embrace different technologies. These tools, which can take various names (service orchestration, workload automation, hybrid data integration, etc.), allow IT teams to design and automate end-to-end processes that incorporate data and files from across the organization, without having to produce custom scripts.


Through pre-set connectors and APIs, data orchestration platforms enable IT to rapidly integrate new sources and existing data silos into ETL and big data processes. Orchestrators also allow IT to operate from a centralized location to manage data access, provide resources, and monitor systems. All of this can be done on on-premise data warehouses and cloud databases.



With data orchestration, the IoT is simpler, more flexible, and more dynamic

The IoT is increasingly an integral part of the digital transformation of businesses. Thanks to the ability to increase productivity, improve the customer experience, and open up to new business models, the number of OEMs that integrate it into business processes is growing. However, often the quantity, heterogeneity, and geographical dispersion of the connected devices, added to the variety of data collected, make centralized, secure, and reliable management of the IoT infrastructure difficult.


A help to companies comes precisely from data orchestration, which, by integrating IoT endpoints, data processing software, and separate systems into a single management platform, simplifies the monitoring, extraction, and processing of data from the dozens of devices, returning organic and easily usable insights, to make truly data-driven business decisions. Orchestration tools return standardized data to the applications that organizations use on a daily basis, enabling pipelines to run at the right time, in the right order and manner, so that the data OEMs need is there when they need it and quickly accessible.


Data orchestration simplifies the IoT infrastructure by leveraging the ability of platforms to connect quickly and securely to virtually any device, wherever it is, to process data both on the edge and in the cloud, and transmit it with the right priority to the right registration system. This saves time and resources that can be dedicated to value-added projects. But it is the whole business that benefits from it because there are shorter ramp-up times, easier installations, and immediate insights, as well as greater security in compliance with the GDPR.



Data orchestration brings value to the company

The goal of data orchestration is simple. Making the right data available to obtain the right insights in real time and be able to make truly data-driven decisions, which will turn into real value for the company and bring concrete results. Also, data orchestration is one of the most effective options for most organizations that have multiple data systems as it does not require massive migrations or extra storage locations, which could sometimes involve the complication of having to manage an additional data silo.


By ensuring greater interoperability and enabling previously unavailable applications, data orchestration simplifies the integration of the IoT into business digital transformation strategies, changing the way they create value for their customers and for themselves.

Tag: IoT