Top 5 data engineering trends in 2023

Nowadays, the amount of available data is increasing rapidly. Organizations collect more and more data to boost their productivity and gain an advantage over the competition. As IDC predicts that the Global Datasphere will grow from 33 Zettabytes (ZB) in 2018 to 175 ZB by 2025.[1] To deal with such a huge amount of data, new tools and technologies are being developed. Therefore, due to technological development, 2023 is to be an exciting year for innovations.

Let’s see what trends in data engineering await us in the coming months.

At the beginning of the new year, it is worth analyzing some of the key trends related to data engineering services. First of all, this is what organizations will have to deal with in the first place:

Empowering digital teams in a more seamless way
Deriving more business value in sales

How can data engineering help you with these challenges? We’ve listed five major trends that will significantly influence data engineering as a discipline in 2023 and beyond.

ARTIFICIAL INTELLIGENCE

AI is a technology that has already had a huge impact on the functioning of virtually every industry. Without a doubt, we will see its further development in the future. When it comes to data analytics, AI will enable the following:

Automation of tedious and repetitive tasks
Better data management
More accurate forecasts
Convenient interactions with data for every person in the company

AI is rapidly advancing data engineering and analytics, helping companies understand the data they have collected. It enables analytic process automation (APA), so companies can analyze data and draw conclusions much faster. When using machine learning algorithms, employees don’t have to process large data sets manually. And this has a huge impact on the productivity of the organization.

DATA DEMOCRATIZATION

Another major data engineering trend in 2023 is the democratization of data. The data democratization definition refers to the principle that data is available to all employees in the company. It doesn’t matter whether the employee has specialized knowledge or not. If everyone in the company has intelligent insights, their work will be more effective and efficient. This trend brings more benefits. Data democratization reduces dependence on data distribution specialists and IT technicians. In addition, teams can make faster decisions with immediate access to data. A democratized data environment is an essential aspect of managing big data and realizing its potential.

DATA AS A SERVICE

Data as a Service (DaaS) is a cloud strategy used to facilitate timely access to business-critical data. These are tools to analyze and manage data anytime, anywhere. What’s more, companies have access to data sources collected by third parties. With DaaS, businesses don’t have to build their systems for collecting and storing data for various types of applications. DaaS eliminates redundancy and reduces the associated expenses. It aligns relevant data in one place, allowing data to be used and modified by multiple users via a single update point. In 2023, the global market for data as a service (DaaS) is expected to reach 10.7 billion U.S. dollars in revenue.[2]

NATURAL LANGUAGE PROCESSING

Big data, AI, IoT, and ML push the boundaries of interaction between people and technology. And Natural Language Processing gives these technologies a human face. Today, NLP helps people engage and interact with various intelligent systems using only human language. It focuses on how to program computers so that they can identify, analyze and process large amounts of information from natural languages.

NLP is expected to become increasingly significant for monitoring and tracking market intelligence. It will give users access to key information that was previously unavailable to them. In addition, it will allow companies to process customer sentiment. Thanks to this, they will be able not only to identify customer needs but also to design products and services.

REAL-TIME DATA

The last data engineering trend on our list is real-time data. The term real-time data refers to information obtained directly from the original source. They are made available as soon as possible. The special feature of real-time data is that if something changes in the original source, the company will see it immediately. Up-to-dateness is an unquestionable distinguishing feature. For this reason, real-time data is becoming increasingly valuable for businesses.

Real-time data requires a sophisticated data and analytics infrastructure. That means more expenses for businesses. Organizations, however, can gain a significant competitive advantage by receiving information on an ongoing basis. By using real-time data, businesses will be able to boost their productivity and analytics in 2023.

Conclusion

To sum up, data engineering is a constantly evolving field. Every year, new solutions and trends appear. The presented trends will definitely set the direction of work on data for all forward-thinking companies. Of course, these aren’t all the predictions we can expect in 2023. But one thing is for sure, data engineering is changing the way we live and do business.

https://www.statista.com/statistics/1132224/worldwide-daas-market/