technology sgs

Data Science, Data Analytics and Artificial Intelligence have already provided new capabilities to various industries including B2B or B2C, sales, distribution, manufacturing, and logistics.  The impact and usage are only going to increase even more in 2020 and in near future. More companies will begin to explore and implement automated machine learning pipelines which are important elements of data science platforms. Daily processes such as data preparation, feature engineering, and modeling will get additionally augmented by tools that help automate these steps. These predictions were just an outline. The following content will give a more elaborate in above picture.

AI Chatbots: It is predicted that companies will increase the usage of natural language processing and building or integrating chatbots to their AI systems for improving customer along with user experience. Chatbots today just feature “if/then” commands which mean that they provide limited responses to queries from users. However, companies in the coming year will implement smarter as well as more conversational chatbots to provide customized as well as satisfying responses to users.

Data Science Ethics: A separate discipline or in other words unique regulatory mechanisms for data science may be formed in the coming years. Parameters will be defined on activities such as automated decision making, the times a human should be included, algorithm bias, and privacy among other issues. Such regulations can ensure that credible players are separated from bad actors.

End-to-End Model Management: This is simply predicting, analyzing and identifying solutions to problems that may arise in the life cycle of a business. The process covers deployment, monitoring models, different tiers of support, and oversight on whether business models need to be rebuilt. All these will be done on a single platform with technological advances of data science.

Need for Data Engineering: Data scientists will need to prepare relevant datasets for achieving business objectives before developing data models. This has become easier now and lesser time will be required owing to developments in data preparation.

Focus on Research and Development: Another important prediction for 2020 and a little after that is that businesses will increase focus on data science research and development initiatives by converting lab-concepts into real-time production.  Such a practice will enable finding solutions to business problems by analyzing real-time key performance indicators and not having to rely only on theoretical or simulation-based assessments.

Massive Automation: Most of a company’s data science tasks will be automated in 2020. This will result in increased productivity and broader usage by citizen data scientists. All incoming data can be streamlined, automated weekly reports can be created along with automated testing and analysis. Besides increased productivity, the emphasis on automation can also bring faster understanding of data that can be applied more quickly to achieve business results.

We hope this post has given a good picture of the trends that can be predicted for Data Science and AI in near future. Join us for more discussions as SGS Technologie is a specialized Data Science solutions provider and AI development company in Jacksonville, Florida. We will be excited for having the opportunity in analyzing the data requirements of your company.

Category

Predictions for Data Science and AI in Near Future


Data Science, Data Analytics and Artificial Intelligence have already provided new capabilities to various industries including B2B or B2C, sales, distribution, manufacturing, and logistics.  The impact and usage are only going to increase even more in 2020 and in near future. More companies will begin to explore and implement automated machine learning pipelines which are important elements of data science platforms. Daily processes such as data preparation, feature engineering, and modeling will get additionally augmented by tools that help automate these steps. These predictions were just an outline. The following content will give a more elaborate in above picture.

AI Chatbots: It is predicted that companies will increase the usage of natural language processing and building or integrating chatbots to their AI systems for improving customer along with user experience. Chatbots today just feature “if/then” commands which mean that they provide limited responses to queries from users. However, companies in the coming year will implement smarter as well as more conversational chatbots to provide customized as well as satisfying responses to users.

Data Science Ethics: A separate discipline or in other words unique regulatory mechanisms for data science may be formed in the coming years. Parameters will be defined on activities such as automated decision making, the times a human should be included, algorithm bias, and privacy among other issues. Such regulations can ensure that credible players are separated from bad actors.

End-to-End Model Management: This is simply predicting, analyzing and identifying solutions to problems that may arise in the life cycle of a business. The process covers deployment, monitoring models, different tiers of support, and oversight on whether business models need to be rebuilt. All these will be done on a single platform with technological advances of data science.

Need for Data Engineering: Data scientists will need to prepare relevant datasets for achieving business objectives before developing data models. This has become easier now and lesser time will be required owing to developments in data preparation.

Focus on Research and Development: Another important prediction for 2020 and a little after that is that businesses will increase focus on data science research and development initiatives by converting lab-concepts into real-time production.  Such a practice will enable finding solutions to business problems by analyzing real-time key performance indicators and not having to rely only on theoretical or simulation-based assessments.

Massive Automation: Most of a company’s data science tasks will be automated in 2020. This will result in increased productivity and broader usage by citizen data scientists. All incoming data can be streamlined, automated weekly reports can be created along with automated testing and analysis. Besides increased productivity, the emphasis on automation can also bring faster understanding of data that can be applied more quickly to achieve business results.

We hope this post has given a good picture of the trends that can be predicted for Data Science and AI in near future. Join us for more discussions as SGS Technologie is a specialized Data Science solutions provider and AI development company in Jacksonville, Florida. We will be excited for having the opportunity in analyzing the data requirements of your company.

Category : Technology

Let's build SOMETHING GREAT TOGETHER!