The technology has made its mark by building a massive shift where the businesses and organizations are adopting it to reach beyond the traditional ways of analytics. It has been seen that the strength of data analysis is also embraced by enterprises all over the world.
It is in the process of making significant alterations in the decision-making landscape for branding and recruitment. Since then, we have been witnessing that data analytics is making a remarkable shift in how the business is being done, but it would be more stimulating to see what the technology holds for us in the coming year.
Therefore, let’s have a look at the top data analytics trend and predictions to watch for 2020.
1. Data Analysis Automation
Data analytics automation is the first and foremost, and it turned out to be the most preferred and favoured technology across every industry so that the business potentials could be enhanced and improved. Moreover, it is now expected that 40 percent of the database work to get automated by the next year. We are hoping that the automation is going to help business leaders to efficiently see further ahead to assist in propelling their enterprises with the appropriate analytics to drive decisions.
2. IoT Merged with Data Analytics
With the beginning of the year 2020, we are to witness a remarkable shift, 20 billion active IoT devices, which would subsequently collect more data for analysis. In big tech IT firms where IoT devices have already been embraced in high-end operations, most of the business leaders are already witnessing beyond it to implement the assisting technology to run intelligent data analytics. Hence, the world is likely to acknowledge more analytics solutions for IoT devices to offer relevant data along with transparency.
Additionally, because of the lack of data science professionalists, around 75 percent of companies could suffer while accomplishing the matured benefits of IoT.
3. In-Memory Computing
In the year 2020, in-memory computing is likely to get strong influence, since the reduction in the cost of memory turned IMC more mainstream. IMC is an excellent solution for a range of benefits in the analysis while being mainstream. The latest persistent-memory technologies of IMC have now led to a reduction in cost and complexity. Moreover, Persistent-memory tech is a new memory tier that is well situated between NAND flash memory and dynamic access memory.
As the wide-scale implementation of the IMC solution is manageable, several organizations are now adopting in-memory computing to enhance application performance while providing a significant opportunity for future scalability.
In the coming years, Augmented analytics would become dominant. The technology has already shaken up the industry by making the unusual move by merging AI and ML techniques by introducing fresh ways of creating, developing, sharing, and consuming analytics.
The augmented analytics have already become the most preferred and popular techniques to use for business analytics. Some of the significant benefits of augmented analytics provide are:-
- It can automate many analytics capabilities like preparation, analysis.
- It includes the building of models, as well as the insights generated, which will be much easier to specify with which to interact.
5. Smart Cities Development
Undoubtedly, IoT is, however, creating many new opportunities for data science and analytics. Additionally, the development of Smart and modern Cities has made the requirement for the data collection a compulsion, as well as data processing and dissemination.
Most probably, smart cities data would assist with medical nursing and proactive health care. Moreover, it was predicted that by 2020, 30 percent of the smart cities would introduce robotics and intelligent machines at the medical services. The technology is leveraged to offer a seamless user experience for residents.
6. Consumer device development
The latest trends with tabs, laptops, personal devices, smartphones, and web-use to showcase that by the year 2020, more than 50 percent of mobile consumer interactions would be increased and are determined by the user’s past and real-time mobile behaviour.