Data management predictions for 2018

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What will 2018 unveil for the data management market? I searched expert opinions on technology trends for 2018 and matched them against my own to uncover the five major trends that I think we’ll see in data management this year:

1. Data movement becomes more important.

Cloud providers have proven that it’s easy to quickly build and deploy new applications at minimal cost. This means more applications will exist in the cloud -- and generate more data in the cloud.

But moving data in cloud infrastructures is expensive. Up to now, data management vendors focused on speed and flexibility, not on minimizing data movement. With increased cloud adoption, organizations will turn their attention to reducing costs by minimizing data movement. Hybrid- and inter-cloud data movement will become a focus area for data management solutions. Data management solutions will differentiate by how they eliminate data movement between clouds and on-premises infrastructure, providing new creative concepts.

2. Data protection is on everyone’s mind.

Data has become what oil was in the last century: A growth factor. As companies realize this and strive to gather more data, consumers are becoming increasingly aware of how much of their personal data is being collected and stored. Trust in an organization has always been a key driver for consumer behavior and will be even more so in a digital future. Protecting sensitive personal data and showing that consumer data is used only for good will become even more critical for organizations going forward. Data management solutions will address those aspects in 2018, especially as the General Data Protection Regulation goes into effect in May.

3. Real-time data management will drive the future.

We are approaching a real-time world where data is generated constantly and stays relevant for only a short period of time. The Internet of Things (IoT), with all kinds of new sensors and devices, is the key driver behind this trend. 2018 will show a stronger demand for sophisticated real-time capabilities to allow organizations to process the fast-growing volumes of real-time data. Any organizations looking to transform into a data-driven business will have to consider real-time data processing more than they did before. This growing demand will influence the data management platform adoption in 2018.

4. Machine learning will augment data management.

Machine learning algorithms will continue to enrich data management platforms. Users will find additional support from integrated machine learning capabilities while exploring, profiling, cleansing or analyzing data. Machine learning techniques will identify relationships, between data to help the user perform joins, unions and other data operations. The goal is to increase the productivity of the data consumer and make data management more pervasive, while at the same time make the data be more “self-aware.”

5. Self-service and increased productivity.

Traditional data management software was built to improve productivity of IT personnel. But with the rise of self-service analytics this focus is shifting towards improving productivity of the data consumer. In 2018, data management will emerge to be more data consumer friendly and therefore addressing the needs of 10 times more users as in the past. The driver behind this trend is the growing number of data consumers and their appetite for self-service, more insights and increased productivity.

2018 is sure to bring new innovations and trends for data management, so keep your eyes open and keep on learning.

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About Author

Helmut Plinke

Principal Business Solutions Manager

Helmut Plinke acts as Principal Business Solutions Manager for SAS, focusing on data quality and data governance technologies. Helmut is an enthusiast of data quality technologies to improve fitness of data and thereby help businesses to improve efficiency and gain competitive advantages. In his current role Helmut supports customers in designing enterprise data management solutions based on SAS technology. He is a specialist in data quality and data integration technologies for a long time now and has been part of some of the major SAS data quality and data governance projects in DACH and the Netherlands recently. With over 15 years of experience across multiple industries Helmut has also gained a wealth of knowledge and experience in technologies like business intelligence, content management and enterprise application integration from his past roles with other companies. Helmut has published in IS Report and speaks about the topic of data management at SAS and public conferences sharing his project experience and knowledge.

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