DataOps
Industrial Model

Modeling of data and digital processes for the new generation of data and interoperable workflows.

The new generation of projects and professionals in production contemplates the dynamic use of data in all disciplines and dimensions within our reach. The large volume of information generated by assets equates to an exponential model where data can be lost. For this, we help our clients to adopt practices in DataOps, to model the way in which the information flows will be used in the future without having to worry about the growth and management of the necessary context.

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Industrial DataOps, powered by Highbyte.

The new generation of projects, today more than ever, focuses on building a completely digital model of operations. With the convergence from the physical to the digital world, software construction projects require a standardized guide on how to build them.

It is the responsibility of data science to offer more and better analytical tools, where more and better information flows can be created to comply with descriptive, predictive and prescriptive improvement processes.

Industrial DataOps allows data scientists to create stability and consistency of data coming from machines, to transform it into standard information processes, distribute it and avoid losses or inconsistencies.

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What do we mean by Industrial DataOps?

To the creation of automated processes, methodologies and coordination of the analytical teams, which improve the quality of the results and selected data. It also refers to the best practices to interconnect equipment with their data, the contextualization and support of data scientists, to create a powerful ecosystem for advanced industrial information management.

An industrial model of DataOps, recognizes the nature of the data, understands that the processes are part of the operation and therefore, the precision of the analysis can make it a complex situation to process.

One of the primary objectives in industrial DataOps is to leave the data pipeline ready, either to grow, increase data flow and support new decision models supporting Artificial Intelligence. Having this type of methodology and services will make your digital transformation initiatives much easier.

Infoportal can help you get started with your DataOps model. Let’s make it happen that your production assets can better respond to your information needs and expectations.

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Why is a DataOps model important to the industry?

Industrial data projects mean a high volume of processing and storage. An industrial data-op model helps to efficiently use capabilities and avoid generating obscure, meaningless, or non-contextualized data.

If your responsibility in the operation involves renewing yourself technologically, increasing digitization to achieve better yields, Industrial DataOps is a key piece to better develop your analytics projects.

When to start a DataOps model?

Building digital transformation projects can be compared to building your physical infrastructure. Being in the process of building a digital infrastructure, it is definitely a good time to be able to create a digital blueprint or how-to guide.

Taking an example where, most of the time, the information requires several clicks or to copy and paste from an excel to another system, it is time to ask if the information generates value.

If you have multiple systems and industrial assets working and you require greater agility to interconnect them between the business indicators and the technical terms of operation.

What do we use DataOps for?

Corporate initiatives for the management a dynamic information with high dependence on processes and information flows.

Data work in multiple plants, different platforms and different departments.

Architectures to think about growing storage for advanced analytics and data science processes.

When we require a structure to feed the artificial intelligence models in production.

When we require a proven model for cybersecurity initiatives and information dispersal structure.

Preparation to convert monolithic database handlers into new generation and high capacity databases.

We invite you to talk with our advisors

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