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Driving change in 2022: trends in data management

‘The data integration tool market is seeing renewed momentum, driven by requirements for hybrid and multi-cloud data integration, augmented data management, and data fabric designs.’ – Gartner

The rise of hybrid work is changing how we manage data. It raises the question of how to ensure data security, as well as how to guarantee data quality.

While these problems are challenging, they create opportunities for innovative companies to address this coming year. So, with that in mind, let’s take a look at three data management trends driving change in 2022.

1. More services from a single vendor

While you may hire one company for your data transformation and another for your storage, the service landscape is evolving. Fivetran, for example, bought out Teleport and HVR last year. TIBCO had the same idea, buying Information Builders for a rumored $1 billion. Now both companies provide a larger range of data services, including more data analytics for better insights.

There will also be a shift to more subscription-based models. What’s more, many companies will form partnerships to combine their resources and build data management products together.

And while the major players have the resources to make big changes, smaller vendors will also start acquiring the technology to develop new and interesting products. We expect that some of these will address security in the cloud, especially as remote working looks set to continue post-pandemic.

2. Intelligent data management

Machine learning and automation will reduce manual data management tasks by 45 percent in 2022, according to Gartner. This is no surprise—after all, huge corporations are already offering machine learning as a service with platforms like AWS and Azure making it easier for companies to quickly adopt machine learning and use it to augment their services.

Machine learning operations (MLOps) is also on the rise with faster, easier, and more mature machine learning deployments ahead. This will result in machine learning integrations even in complex data projects.

More intelligent technology will help with the current skills shortage too. Gartner predicts that AI-enabled automation in data management and integration will reduce the need for IT specialists by 20 percent come 2023.

But in the meantime, we’re already seeing more basic users improve their skills. As more companies adopt self-service models, staff are better understanding and managing data as a result.

3. Focus on the user

Some complex projects will always require trained data engineers. But as companies continue to implement hybrid and remote working policies, self-service platforms are enabling staff to quickly access data rather than waiting on their overburdened IT departments to provide it for them. It’s also resulted in an increase in data lakes which provide the singular point of access so necessary for distributed workforces.

In fact, more and more end users need better data access, as well as a clearer understanding of the data they’re handling. It’s therefore crucial we build products with them in mind.

CloverDX Wrangler is a new interface for CloverDX that enables users with simpler use cases to quickly and easily create data transformations. It uses the same powerful execution core as CloverDX, so whatever job you’re building in Wrangler you can always pick up and carry on in the full platform.

Driving the future of data management

2022 will be an innovative year for data management with more diversified and intelligent services. They will also be more user-centric, providing more data management capabilities for business or less-technical users.

You can check out our webinar on Driving Data Change in 2022 for more information on trends in data management in 2022. But don’t hesitate to contact us if you’d like to discuss how you can drive change in your business this coming year and beyond.

Read MoreCloverDX Blog on Data Integration



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