There will be a lot of data analysis trends to prepare in 2020, and it is important to document the new trends to explore. Data analysis is amazingly changing the entire industry and many organizations today.
This technology has attracted widespread attention through major shifts, and companies and organizations are adopting this technology to go beyond traditional analytical methods. It can be seen that the power of data analysis is also accepted by companies all over the world.
What is data analysis?
It is making major changes to the decision making environment for brands and recruiting. Since then, we have been witnessing significant changes in the way data is analyzed in terms of how it is conducted, but seeing the impact of this technology on us in the coming year will be even more exciting.
So let's take a look at the hottest data analysis trends and forecasts for 2020 .
- Data Analysis Automation
Data analytics automation is the number one and most important, and it has proven to be the most popular technology in every industry, so it can enhance and improve business potential. In addition, it is now expected that 40% of database work will be automated by next year. We hope that automation will help business leaders effectively understand future developments to help their companies conduct appropriate analysis to drive decision making.
- IoT and data analysis merge
Beginning in early 2020, we will witness a significant shift in 20 billion active IoT devices, which will then collect more data for analysis. In large high-tech IT companies that have incorporated IoT devices into high-end operations, most business leaders have seen its development to implement assistive technologies to run intelligent data analytics. As a result, the world may recognize more analytics solutions for IoT devices to provide relevant data and transparency.
In addition, due to the lack of data science professionals, approximately 75% of companies may suffer losses when they realize the mature benefits of the Internet of Things.
- In-memory calculation
In 2020, in-memory computing is likely to be greatly affected, as the reduction in memory costs has made IMC mainstream. While becoming mainstream, IMC is an excellent solution that offers a range of analytical advantages. Now, IMC's latest persistent memory technology has reduced cost and complexity. Moreover, persistent storage technology is a new storage layer between NAND flash and dynamic access memory.
Because large-scale implementations of IMC solutions are manageable, many organizations are using in-memory computing to enhance application performance while providing tremendous opportunities for future scalability.
- Data as a service
In the next few years, enhanced analysis will become dominant. By introducing new ways to create, develop, share, and use analytics, and by taking an unusual move by combining AI and ML technologies, the technology has shaken the industry.
Enhanced analysis has become the most preferred and popular technology for business analysis. Some of the important benefits of enhanced analysis are:
It can automate many analytical functions such as preparation and analysis.
It includes the creation of the model and the insights generated, which will make it easier to specify the objects that interact with it.
- Smart city development
There is no doubt that the Internet of Things is creating many new opportunities for data science and analytics. In addition, the development of smart cities and modern cities has made the requirements for data collection, data processing and distribution mandatory.
Most likely, smart city data will help with medical care and active care. In addition, it is predicted that by 2020, 30% of smart cities will introduce robotics and smart machines into their medical services. This technology provides residents with a seamless user experience.
- Consumer equipment development
The latest trends in tabs, laptops, personal devices, smartphones and web usage indicate that by 2020, more than 50% of mobile consumer interactions will increase, depending on the user's past and real-time mobile behavior.
Future trends in 2020 show that as long as the analysis tools are easy to use and access, 50% of the analytical queries will be generated using voice or NLP technology.