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Cognite 2021 Predictions: Five data trends to lead us towards a more sustainable future

vmblog 2021 prediction series 

Industry executives and experts share their predictions for 2021.  Read them in this 13th annual series exclusive.

Five data trends to lead us towards a more sustainable future

By Petteri Vainikka,  Vice President of Product Marketing at Cognite

The proliferation of data across business settings is rapidly changing how work is done. It comes as no surprise that the world is digitalizing, but the rate at which it is transforming, creates challenges for organizations without the data infrastructure in place to manage rapid and drastic change.

This is especially true for the heavy asset industry as companies in this space are simultaneously attempting to promote efficiency and meet increasing public pressure to address sustainability.

And as we close out 2020 and organizations begin to take stock of the past 12 months, many will need to further accelerate their digital transformation initiatives. But now, as businesses emerge from the uncertainty of the pandmeic, they will be looking to maximize their technological and operational capabilities, which starts with data. While data has the ability to boost revenue and make shareholders happy, it also has the ability to improve sustainability efforts, encourage workforce safety and unlock a variety of other benefits.

Here are the top five data predictions to lead the heavy asset industry into a more efficient digital world.

Centralized data management gives way to accessible data governance

In some industries, data is segregated and monopolized by individual organizations and projects. However, if we find ways to interpret and link data points, we will support faster and more efficient production. Use case-specific data models and scalable data templates will become the new focal point of enterprise data modelling; driving the evolution of the traditional central enterprise data model custodian role into an enterprise data model portfolio management role within IT.

AI will teach data to speak human

AI-driven active metadata creation will become more popular as we address data management - shifting the emphasis from data storage and cataloging, to a true human data discovery experience. The same shift- which has already taken place on the consumer side, where e-commerce has shifted from manual catalog filtering to automated content recommendations - will transform the enterprise data discovery experience, enabling new data consumers to access large, varied and complex data sets for the first time, on their own, unlocking the potential of citizen data scientist innovation.

Enterprises will invest more in metadata (and its management) than in data itself

As the cost and value of data storage continues to gravitate towards zero, and data science teams simultaneously scramble to convert existing data warehouses and lakes into business value, the evidence that there is  ‘no correlation' between volume and value of data, keeps growing. The focus and value of metadata will exceed that of the data itself, whether through manual tagging of images, AI-driven data set matching to uncover data relationships, or OCR/NLP methods to convert unstructured data into structured data. Data contextualization will be at the center or metadata curation.

Data operations (DataOps) will connect data custodians to data consumers in real-time, at unprecedented scale

Because there is a continued convergence of data management with data analytics, and an exponential rise of data consumers (such as data analysts, application developers, data scientist and citizen data scientist) the need to seamlessly operationalize data for business value across currently disjointed use cases will take centerstage for all digital transformation programs large and small.

Hybrid AI will come into focus

Engineers will use digital twin applications with the most flexible software best user experiences.  This will be a competitive field as engineers can world quickly all over the globe to create realistic simulation models.

There is little doubt that 2021 will be a busy year for data engineers as they strive to navigate DataOps, and execute digital transformation initiatives that unlock the value of data. And while accessing this data and harvesting its true value can be challenging it is absolutely necessary. Without it, utility companies run the risk of falling behind their competitors, losing consumer trust or favor, and may even go out of business. In a world where data is a businesses' most valuable asset, embracing its potential and capabilities to boost revenue, sustainability, employee safety and overall efficiencies will be critical to maintaining a competitive advantage.


About the Author

Petteri Vainikka 

Petteri Vainikka is the Vice President of Product Marketing at Cognite. His professional career spans across enterprise SaaS technologies, where he has found himself at the intersection of emerging transformational technology development and its commercial applications for customers. Prior to Cognite, Petteri worked in senior product management, marketing, sales, and general management positions for companies such as at Sumea, Rovio, Cxense and Ardoq. Petteri has a master's degree in technology from Aalto University in Helsinki.

Published Thursday, December 17, 2020 10:54 AM by David Marshall
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