DataSecOps, what it is and how to enable data as a product

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Learn why data security is increasingly critical to your business’ most important asset and how the DataSecOps approach can help.
Among the multiple paradigms that are in the air in the present and near future plans linked to the digitalization of the activities of all organizations, DataSecOps appears, which is a combination of concepts linked to data -driven operations and data security , which constitutes an essential factor of resilience, since data is among the most valuable assets there can be.


The operations-focused perspective is closely related to agile development, which in turn is linked to the agility with which daily activities are carried out. In the current state of business, which is very dynamic and has multiple variables constantly interacting, it is necessary to develop new functionalities at the software or online services level and this impacts data management ( DataOps ).

Then, the multiplication of resources in the cloud or hybrid environments, in a scenario of increasingly sophisticated cyberattacks, forces us to add the security layer (SecOps) to end up forming the overseas chinese in canada data that we will discuss today.

Data-driven, cloud-enabled digital transformation

Data at the center
To put this into context, no one can argue anymore that data can remain in silos disconnected from each other. Nor can the value of data be minimized . This is where the idea of ​​treating data as a product emerges. What is this?

To be prepared to enter this new data-first phase , a results-oriented mindset is needed, aligned with the organization's capabilities and integrating various functionalities, with the intention of solving problems and optimizing benefits.

It is worth reviewing availability to focus on data discovery , data security and reliability, as well as how explorable and understandable it is. With all this in place, working with data can be approached as with any other type of product development: identifying and responding to unmet needs, adopting key criteria such as agility and reuse.

In other words, this implies that organizations work with data in such a way that it can be an input product for the different areas to fulfill their own function in the whole, even for the executive levels in charge of making decisions.



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The artificial intelligence market is expected to grow at a CAGR of 18.6% in 2022-2026.

Source: IDC



From DataOps to DataSecOps
In this path of reconsideration or cataloging of data, some time ago there was talk of DataOps, referring to the data that arises or is generated in the business process. An important characteristic is that a good part of this data is generated by an army of clients in a dispersed, dynamic and remote manner.

But DataOps also refers to the collaborative data management practice focused on improving communications, integration, and automation of data flows between data managers and data consumers across the organization. It's a concept closely related to data democratization.