Doing business in the era of information technology and data processing This makes data and data analysis more important.
Data Science and AI are beginning to be used to enable businesses to respond to customer needs and deliver more value to the business.
Gartner, Inc. has compiled 5 important trends in the future of DSML as follows:
1. Cloud Data Ecosystems Cloud data ecosystem
In the future it will be a world of information. The systems used for storage and processing must be efficient.
By Cloud Data Ecosystem It is a system used for data management and data processing based on the cloud (Cloud Computing) which is the storage and service of computer capabilities via the internet.
It helps in data management and data analysis in an efficient way. It focuses on the software approach to building, deploying, and managing modern applications, putting data in a connected cloud ecosystem. Rather than integrating separate or self-contained systems
Gartner expects that more than 50% of cloud data ecosystems will be used by 2024 to enable organizations to access and use data efficiently. According to business needs and business data analysis
2. Edge AI Streaming Artificial Intelligence Behavior
Edge AI data processing is done in large, remote data centers (centralized data centers).
Make it close to the storage point. Data analysis using deep neural networks will occur at the first capture point in the edge, rather than in the data center as has been the case in previous generations.
Edge AI: Systems that require fast processing and decision making that are close to the source data. or users This results in the ability to respond quickly to events. Including streaming events and reducing data loss during transmission.
Gartner predicts that by 2025, more than 55% of all data analyzed using Deep Neural Networks will occur at the edge of the AI endpoint.
3. Responsible AI, artificial intelligence that increases responsibility
The principles of Responsible AI are to focus on the potential impacts of AI use and to act carefully to minimize risks. It emphasizes social issues, safety, privacy, fairness, and transparency in the AI development and use process.
Gartner predicts that by 2025, Responsible AI will cover many aspects of making the right business and ethical choices when organizations freely use AI, such as business and social value, risk, and trust. Trust, transparency and accountability
4. Data-Centric AI, artificial intelligence that focuses on data
Data-Centric AI is a concept for developing and using artificial intelligence (AI). By giving importance to data as the most important part in the system's working process.
In Data-Centric AI, data is managed efficiently from collection, data cleaning, data preparation, data processing, data quality checking, and data security.
Gartner predicts that by 2024, over 60% of data will be synthesized by AI to simulate reality. future situation and reduce risk And it is an important concept in preparing for the use of AI in organizations and projects that require good results in analyzing current and future data.
5. Accelerated AI Investment Investment in artificial intelligence is increasing rapidly.
Investment in AI will continue to grow rapidly. By increasing budget and resources to develop and use AI. in an organization or institution Including industries that want to grow through AI technology and businesses that use AI.
Gartner predicts that by the end of 2026, investment in AI will accelerate to more than $10 billion. Baseline AI models help organizations prepare and adapt to rapidly changing trends. of a world where AI and technology are growing rapidly
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