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The latest trends in big data to be up to date

The latest trends in big data to be up to date

The trends in big data in 2020 predict an increasing complexity in the use of technology, the analytical data  and the internet of things (IoT).

The evolution of massive data analysis in recent years has been dizzyingly fast, so regardless of the economic context you see around you, you can be sure that 2021 will bring significant innovations.

"There will be more smart metadata catalogs, low-latency, low-bandwidth real-time analytics, and simulations and algorithms that will identify data patterns and anomalies." - says Dereck Framewall from ip locations org.

All of this will continue to result in business development and, therefore, will improve the possibilities for growth. If you are thinking of specializing in this area, check out the following trends in the data industry.

Hybrid and multi-cloud solutions

The cloud technologies continue to grow and improve. However, since the speed of the changes does not yet allow sufficient agility and functionality, a growing trend is the use of hybrid and multi-cloud implementations .

This occurs because, in reality, for the majority of the business fabric it is not easy to move its entire structure to the cloud and synchronize its platforms and data sources from a local solution. Also, remember that many companies have left their fingerprint on various clouds .

This adaptation and migration process can be an investment of time that, in some cases, lasts for weeks or months. Therefore, although profitability is evident, many companies resort to combining cloud and on-premises solutions in a hybrid model .

In doing so, they use the cloud to dynamically store and work and use local platforms for stable workloads.

Increased analytics

This strategy goes beyond analyzing data to obtain knowledge that can benefit business development. Combine the study of information with machine learning algorithms and natural language processing (PLN) to make your work much more productive.

In this way, it is possible to manage and understand the data and interact with it, as well as detect anomalous trends. In addition, machine learning algorithms, fundamental in the evolution of big data , facilitate the predictions and preventive strategies that your company may need.

This technology combines artificial intelligence and machine learning with the aim of optimizing the interpretation of data and the possibility of developing and sharing it more quickly.

All this data collection and analysis process, which serves to keep those who are especially valuable and significant, occupies around 80% of the technicians' work.

Thanks to augmented analytics , many of these tasks can be carried out automatically, which means a considerable reduction in the errors that are made in this process.

Edge computing

This information technology is based on one objective: to optimize the use of bandwidth and the response times in data transfer . This is achieved because the data processing is carried out in a physical space as close as possible to its destination.

The result is faster data flow and lower network traffic density. In other words, less accumulation of time delays is achieved .

If, in addition, you combine it with cloud computing, you will further reduce that latency and increase cybersecurity , since the sending of data through networks or other processors is decentralized.

The clearest example of the usefulness of this paradigm is in augmented reality and virtual reality. To develop optimally, these technologies require that latency be very low and that, on the contrary, bandwidth be as high as possible.

In memory computing

It is a technology designed to analyze in real time . Thanks to it, you can examine large amounts of information and detect patterns stored in internal memory or RAM. Additionally, this will prevent certain transactions from some applications and speed up processing.

Do not forget that, given its great benefits and its low cost, this is a trend that has a good chance of continuing to grow in the future.

The analysis of data in the internal memory , combined with machine learning techniques , offers fast and precise information that can be used in large systems and also in much smaller ones with great results.

Although specific hardware with a certain certification and configuration is required , this technology offers you many advantages, such as table storage and data replication.

Improved speech processing

Artificial intelligence, the internet of things and machine learning allow, with the help of natural language processing (PLN), that humans and machines interact.

This trend will give surprising results in the future thanks to programs that will understand written and spoken human language and will know how to give you various response options.

The data chief officer or responsible data

Although you can not consider it a technology, the chief data officer (responsible for data management and analysis) is an alternative that is prevailing in many companies. It is an evolving professional profile with growing specialization.

The application of the General Data Protection Regulation in the European Union of May 2018 required the figure of a specialist in data management and treatment . This technician, who initially was not specifically destined for analysis, is increasingly linked to this task.

The need to implement harmonized practices with data protection and analysis has made this area a new source of employment. An increasing number of companies handle large amounts of data and many of them want a professional who knows how to handle it in compliance with regulations and getting the most out of their analysis.

If you are interested in the field of macro data , now begins to train you on the latest trends in big data in the hands of internationally renowned teachers.

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