Any idea what the top data trend is for 2019? Three years ago, Gartner said blockchain was “near the peak” of its hype cycle for emerging tech — however, it has since been downgraded to number nine. With Gartner announcing the latest data and analytics top ten this week, it’s an opportune moment to see what will be making the headlines. Let’s run down the list:

Trend No. 1: Augmented Analytics

Augmented Analytics is the next wave of disruption coming our way. It uses machine learning (ML) and AI techniques to transform how analytics content is developed, consumed and shared.

Trend No. 2: Augmented Data Management

Augmented data management leverages ML capabilities and AI engines to make enterprise information management categories, including data quality, metadata management, master data management, data integration as well as database management systems (DBMSs), self-configuring and self-tuning.

Trend No. 3: Continuous Intelligence

Continuous intelligence is a design pattern in which real-time analytics are integrated within a business operation, processing current and historical data to prescribe actions in response to events.

 Trend No. 4: Explainable AI

Explainable AI in data science and ML platforms, for example, auto-generates an explanation of models in terms of accuracy, attributes, model statistics and features in understandable, real language.

Trend No. 5: Graph

Graph analytics is a set of analytic techniques that allows for the exploration of relationships between entities, such as organisations, people and transactions.

Trend No. 6: Data Fabric

Data fabric enables frictionless access and sharing of data in a distributed data environment.

Trend No. 7: NLP/ Conversational Analytics

By 2020, 50 percent of analytical queries will be generated via search, natural language processing (NLP) or voice, or will be automatically generated.

Trend No. 8: Commercial AI and ML

Gartner predicts that by 2022, 75% of new end-user solutions leveraging AI and ML techniques will be built with commercial solutions rather than open source platforms.

Trend No. 9: Blockchain

The core value proposition of blockchain, and distributed ledger technologies, is providing decentralised trust across a network of untrusted participants. The potential ramifications for analytics use cases are significant, especially when leveraging participant relationships and interactions.

Trend No. 10: Persistent Memory Servers

Persistent memory represents a new memory tier between DRAM and NAND flash memory that can provide cost-effective mass memory for high-performance workloads.

While some of the trends are easier to comprehend, for non-data specialists, than others, it’s essential for business leaders to at least know what they are and consider how one or more could improve their business processes. Doing so will help them determine what skills sets and infrastructure they require to run successful operations.


But first, cookies! We use cookies to ensure you get the best experience on our website. Find out more about this