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New Trends in Data Science

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Today, fewer and fewer executives base their business strategies on assumptions. Reasonable use of Big Data and the ability to work with data take a significant place in the work of companies. Artificial Intelligence and Edge are opening up new potential for data scientists to work with. Despite all this, all companies have not yet used this technology and require training in data skills. We propose to consider the main trends in the sphere of data science.

The ubiquitous use of Artificial Intelligence and Machine Learning

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AI and ML will soon be ubiquitous and more industries will become data-driven.

Numerous enterprises have noticed that AI and ML platforms have a huge number of advantages. In this regard, many are investing in rising technical knowledge.

The insurance industry has always incorporated the application of advanced technologies into its work with varying degrees of success due to the high level of regulation. However, the underwriting and proposal generation process is already automated. And at the moment, AI and ML are already being used to improve the quality of service and increase market share using the personification method. This method is an exceptional way to stand out from many other companies. However, without AI and ML, such a process can take a long time and entail a significant increase in costs. Such functionality in action will prove to be the most productive method of assimilating the satisfaction of individual needs. This will improve the customer experience and increase personalization. ML will help improve your products so that the consumer will be satisfied and make their choice in favor of your company.

Development of hyper-automation

Hyper-automation is a way to quickly define and automate a huge number of processes. Hyper-automation uses technologies such as RPA, LCAP, AI, and virtual assistants.

These tools are process-independent. They can be used in many areas. Such technology will be in great demand, and it will also become a determining factor in the development of the trend of hyper-automation.

Use of software as a service

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SaaS is a technology that provides software without purchasing it. You just pay for a subscription. That is, you subscribe for as much as you need. At any time, you can refuse this service, and your company will not be obliged to pay huge sums of money for such a service.

Also, a data storage service is provided for users. Your information will be protected by 99.9%

There is no such thing as a regular subscription with all the tools. You choose a set of tools that will be effective for you, and based on all this, the cost of such a service will be formed.

And if at one point you want to change your set of instruments, then your instruments will be recounted, and the tariff will be recalculated. It couldn’t be more convenient. You pay for what you need, not for a whole package of unnecessary services.

Data fabric

As employees become increasingly familiar with the usefulness of data science tools to make strategic decisions, automation, and machine intelligence help them to do so. The concept of data fabric has become a hot topic for the next stage of development.

Data fabric brings together disparate sources and streams of data in various topologies and provides many ways to access and work with this data for the organization’s personnel. It is a kind of large contextual background.

This technology will be of great service to large companies that need to be super flexible when it comes to data analysis. It allows you to work with multiple big data sources at once.

New workplaces

It should not be overlooked that the emerging trend in Big Data is creating new workplaces and kinds of jobs. Most employers, realizing the huge role of manipulating large amounts of data, will hire new employees to work with new technologies. Since this area is still on the path of growth, there is a huge potential for personal growth for every employee in this area.

To understand the difficult question of how to introduce new technologies into an existing workflow, Data Science & AI specialists offer their services. Masters of their craft will provide invaluable assistance in the implementation of effective working methods.

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