In a recent CRN article, Rick Whiting outlined a number of emerging data trends for service providers to be aware of as the year progresses. We’ve provided a summary of some of the most potentially significant trends below, including: 

Analyzing Data Across Multiple Clouds 

As businesses store more data in cloud platforms, analyzing information spanning on-premises and multi-cloud platforms can become a challenge. To address this, expect to see new technologies and solutions aiming to provide a unified, virtual view of dispersed data. Companies will be able to choose between the traditional data warehouse, in which data is collected from multiple sources and managed in a central location, and this emerging virtual approach. 

Data Fabric 

According to the article, Whiting believes we’ll continue to hear more about this architecture for integrating, accessing, and managing data across multiple heterogeneous platforms and technologies. More businesses are relying on data scattered across hybrid-cloud and multi-cloud networks, making data fabrics essential for connecting this information to power business applications, AI, and analytics. They will become even more significant in the coming year as organizations look to accelerate analytics migration to the cloud, ensure security and governance, and further digital transformation initiatives. 

Data Observability 

As organizations invest more heavily in analytics, it follows that the standards for data quality, reliability, and completeness increase. This is where data observability comes into play, as it gives companies a way to monitor for these and other metrics, providing a richer view of all data assets. 

Large-Scale Use of Machine Learning 

As the adoption of machine learning accelerates, easy-to-use ML tools and automated ML software will automate the technical elements of many data science tasks. This, in turn, will enable data scientists to do their jobs more efficiently and open up data science capabilities to a wider audience of data analysts. The cloud is also becoming the preferred platform for housing ML projects, making it easier to manage and deploy ML features at scale.

The Rise of Comprehensive Data Governance Platforms 

Another growing trend for service providers is comprehensive data governance platforms. These solutions comprise capabilities such as data catalogs, data access control, data security, and other capabilities that companies previously addressed via point products. Implementing a comprehensive platform that encompasses these and other requirements streamlines operations and stands to greatly improve data governance efforts.

For more on the above and other emerging analytics trends, check out the CRN piece in its entirety.