Trends 2019, A Plethora of New Age Data and Analytics Emergence

by March 3, 2019 0 comments

In 2019, augmented analytics, artificial intelligence along with resolute memory server will continue to be the hallmark emerging competitive trends and it is expected to drive innovation over the next couple of years.

Gartner Analysts Donald Feinberg and Rita Sallam, in their presentation at Gartner Data and Analytics Summit held in Sydney, released the list of leading trends in data and analytics that have the capability to transform the business environment.


Augmented Analytics

The novel archetype of augmented analytics has emerged out in the market. The core of this technology is the use of machine learning automation to enhance human intelligence and augment entire data and analytics workflow. The technology is crucial for impartial contextual awareness, acting on insights and unbiased decisions. It is expected that by 2020, augmented analytics will act as an authoritative catalyst of the newest form of trade among analytics and business intelligence.


Augmented Data Management

Augmented Data Management performs suitable machine learning and artificial intelligence capabilities for vital information management tasks. The process, as explained by Gartner, is “self-configuring and self-tuning”.  This augmentation is likely to impact data management software which included data quality, metadata management, master data management, data integration, and database management systems. In the next 2 years, half of the analytical queries will be created through search, natural language processing or voice.


Continuous Intelligence

Continuous Intelligence is a new age machine driven pavement to analytics which enables the user to get to all data and pace up the analysis regardless of a variety of data sources and vast volumes. This approach lets the machine to automate continuously and frictionless. The projection of the technology by 2022 depicts more than 50 percent of major new business systems will employ continuous intelligence using real-time context data for improvisation of decisions.


Explainable AI

Explainable AI (or Transparent AI) is that category of artificial intelligence whose actions are trustworthy and understandable by humans. Explainable AI or XAI is deployed for implementation of a social and rightful explanation of actions. The debate still goes on over – if artificial intelligence can be smart or transparent because of the increasing complexity of internal AI.  Despite all if’s and but’s, it can be foreseen that by 2022, 75 percent of new end-user solutions anchoring AI/ML techniques will be designed with commercial platforms rather than open-source platforms.


Graph Analytics

The surge of innovation enveloping big data has introduced the world with a number of open source graph databases to execute hassle-free analysis. Arguably, many of the prevailing techniques are unable to handle the volumes and velocities of big data. In light of the solution to this issue, graph analytics leverage the technique of analyzing focus data to the real world and identify key factors influencing the graphical trend. Over 75 percent of big organizations are expected to employ the technology for analyzing forensic behavior, privacy and customer trust issue and to reduce brand and reputation risk.


Data Fabric

Data fabric is not a newly-tossed term; its relevance has been there over the years in the industry. When organizations struggle to integrate their data into a single, scalable platform, data fabric provides a comprehensive approach to hit the mark. With the expansion of companies and their data usage, there is a need for a better data solution at this hour. The forecast illustrates that the requisition of graph processing and graph database will accelerate at 100 percent annually by 2022. The technology will enhance data preparation and enable more complex and adaptive data science.


NLP and Conversational Analytics

Natural Language Processing and Conversational User Interface is an interesting way of interacting with devices either using phones, smart home assistants (Alexa and Google Home) or any IoT devices. Regardless of the format, the AI-powered conversational analytics assistant is capable of interpreting dictated commands by the user. Data management manual tasks will be minimized by 45 percent by the addition of such technology through 2022 adding up to automated service level management.


Commercial AI and Machine Learning

Artificial Intelligence and Machine Learning have marked their impression in the industry in the past few years and continue to grow at a high pace to revolutionize the lives we live. Earlier Gartner report predicted that in the next 2 years, artificial intelligence will become investment priorities for approximately 30 percent of C-suite executives. Additionally, by 2022, customized designs of data tools will be introduced as static infrastructure which will enhance the redesigning for dynamic approaches.



Since the disruptive inception, blockchain technology has provided the global community with transformed and novel solutions in certain areas including finance, authentication, and data security.  The very technology created by Satoshi Nakamoto is a distributed ledger platform which enables the information sharing (not copied) across a network. Most sanctioned blockchain uses are going to be replaced by ledger DBMS products by 2021, says Gartner release.


Persistent Memory Server

PMEM or Persistent Memory is a solid-state high performance (byte) memory devices which allow the device to have DRAM like access to data. The technology has the same speed and abeyance of DRAM and the non-volatility of NAND flash. Non-volatile dual in-line memory module and Optane DC persistent memory modules are two prototypes of the technology. Persistent memory will serve around 10 percent of in-memory computing memory GB consumption by the year 2021.

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