Data Management Trends in 2022

In this blog post, we will discuss some of the most important trends we can spot so far, and explore how they will develop further by the end of the calendar year.

We will also take a look at how Java developers can take advantage of these trends to create innovative data management platforms.

But, first of all, let’s summarise what data management platforms are.

Data Management Platforms

A data management platform (DMP) unifies the collection, organisation, and activation of first-, second-, and third-party audience data from any source, including web data, data from your smartphone, and beyond. It's the foundation of data-driven marketing, allowing companies to acquire personal insight into their audiences.

DMPs are useful for businesses because they do not only store big, heavy, raw data. They also allow for the data to be sorted and analysed, thus enabling the marketing managers to use it effectively for each following campaig n
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The data is collected over many different platforms and can be used for personalised ads, customisation of content, targeted campaigns, etc. This makes it a significant tool in optimising a marketing and sales funnel.

Data Management Trends in 2022

So without further ado, here are the top data management trends for 2022:

Big data
Cloud-based Platforms
Artificial Intelligence

#1 Big Data

With the advent of big data, businesses have been able to collect and store vast amounts of data. This has led to a need for new tools and techniques to manage this data effectively.

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The major benefit is that it enables these businesses to better manage their data. It also provides a competitive edge to them by allowing for the collection and interpretation of large amounts of data.

The usage of big data has increased significantly in recent years due to the advancement of technology. This has led to the development of new tools and techniques for managing big data.

The most popular tool for managing big data is Hadoop. Hadoop is an Apache open-source framework that allows for the distributed processing of large datasets across clusters of computers.

While Hadoop is currently in-demand, trends are showing that the expansion of such tools is yet to come, and we will see more different tools, optimised for the needs of different industries.

#2 Cloud-based Platforms

Cloud-based platforms offer many advantages over traditional on-premise solutions, including scalability, flexibility, and cost savings. As more businesses move to the cloud, we expect to see a corresponding increase in demand for cloud-based data management solutions.

Cloud-based platforms offer many advantages over traditional on-premise solutions. One of the biggest advantages is that they are useful as a data storage tier for disaster recovery, backup, and long-term archiving.

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Even if you are moving to a cloud-based data management solution, you will still store a lot of data offline. Since the safety of data should be among your first priorities, it is always good to have secure data recovery software such as Hetman Software among your assets.

#3 Artificial Intelligence

AI has changed our everyday lives significantly, and we are yet to discover all the opportunities it has in improving the way we do business.

Artificial intelligence is already being used by some businesses to automate tasks like customer service and marketing. However, we believe that there will be even more impact of the use of AI in data management as well.

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Particularly, using AI, including machine learning and deep learning, can help us analyse and understand an exhaustive amount of data rather quickly. Implementing AI in data management platforms shows that it can result in optimising, reorganising, and improving platform performances overall.

Risk & Opportunities in Data Management 2022

Even though there are many benefits of managing big data with tech-equipped platforms, there are some hidden risks involved, worth mentioning here. If not thought through, using data management platforms can lead to making your information harder to access and read, store and analyse.

If we have a better understanding of what the potential risks might occur, we can plan ahead to prevent them from happening in the first place.

Let’s overview the main threats you might face over time.

1. Security Protocols Are Not Reliable

As we mentioned earlier, security is a top priority when it comes to managing data. The more personal data you store, the more important security should be.

While data management platforms are becoming more and more sophisticated, so is a digital crime. In order to prevent security breaches, whether you work with data on the cloud or on-premises, your tech team must run regular scans and stay alert for potential red flags.

Keep your software up-to-date and your data safely encrypted at all times.

2. Policy Issues

When it comes to data collecting policies, they must be set in place by your legal team personally. This means, that this is not something AI could potentially help you with.

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Keep your business transparent and make sure all clients are aware of what data are you storing and for which purposes. Always allow them to refuse to share their personal data with your database.

3. Team Efficiency

The more the industry develops, the harder it might be to keep up with the upcoming trends, novelties in software, and changes in your business strategy.

For those employees who will be in charge of collecting, managing, and using the data - make sure to provide sufficient training in order to prevent potential bottlenecks and workflow stumbling blocks.

It is never too expensive to invest in the education of your team.

4. Cost Efficiency

If you decide to create your own data management platform, you should be aware of all potential costs this might have for your budget.

Consider what would be the cost of hiring developers to create, improve, and maintain your platform. Developing such a system can cost you up to $50k, so at the current time many businesses, especially SMEs, are going for hosting their data on third-party management platforms.

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