Big Data Trends 2020 - Top 7 innovations
Name: 木村芳華
Student ID: D0740902
Website: https://addepto.com/big-data-trends-2020/
Student ID: D0740902
Website: https://addepto.com/big-data-trends-2020/
In the article, it talks about seven big data trends that will grow in the next few years.
1. Augmented analytics
Analyze the results can get useful knowledge to help to progress the company. We can find out the data that is valuable or unusual quickly by combining with the NLP and machine learning algorithms.
2. Optimization
Cold storage is the way to optimize cloud computing, it can help to store old or useless data, to provide space to keep the new and important data.
3. Edge Computing
It can cooperate with the cloud computing infrastructure, because it can expand to work in centralized servers, and also can be used in distributed on-premises servers and even the devices themselves.
4. In-Memory Computing
It is a technology that purpose to test patterns within data and analyze huge amounts of data. SAS is one of the companies committed to developing this technology.
5. DataOps
The full name of DataOps is Data Operations. It can let automated data testing and delivery more easily. DataOps is used for increasing the quality of data and lower down the time that data analyzing. DataOps has been used in business intelligence, data science, and analyzing data.
6. Chief Data Officers (CDOs)
More and more companies decide to hire CDO or CPO because of the GDPR. GDPR impacts big data analysis a lot because the companies had adapted more highly efficient and more simplify the big data analyze solving the problem.
7. Continuous Intelligence (CI)
It is a new technology, it can achieve through enhanced analysis and other big data and AI technology.
1. Augmented analytics
Analyze the results can get useful knowledge to help to progress the company. We can find out the data that is valuable or unusual quickly by combining with the NLP and machine learning algorithms.
2. Optimization
Cold storage is the way to optimize cloud computing, it can help to store old or useless data, to provide space to keep the new and important data.
3. Edge Computing
It can cooperate with the cloud computing infrastructure, because it can expand to work in centralized servers, and also can be used in distributed on-premises servers and even the devices themselves.
4. In-Memory Computing
It is a technology that purpose to test patterns within data and analyze huge amounts of data. SAS is one of the companies committed to developing this technology.
5. DataOps
The full name of DataOps is Data Operations. It can let automated data testing and delivery more easily. DataOps is used for increasing the quality of data and lower down the time that data analyzing. DataOps has been used in business intelligence, data science, and analyzing data.
6. Chief Data Officers (CDOs)
More and more companies decide to hire CDO or CPO because of the GDPR. GDPR impacts big data analysis a lot because the companies had adapted more highly efficient and more simplify the big data analyze solving the problem.
7. Continuous Intelligence (CI)
It is a new technology, it can achieve through enhanced analysis and other big data and AI technology.
The blog is written by Addepto website. Addepto is one of the top machine learning agencies operating worldwide. Therefore, this blog is considered to be reliable source of information.
ReplyDeleteThe blog stated that big data analytics is more convenient, much quicker, and cheaper for dealing with data. This blog mainly focuses on seven trends which shape the big data industry in the year 2020. The seven trends are comprised of: augmented analytics, optimization, edge computing, in-memory computing, dataops, chief data officers (CDOs), and continuous intelligence (CI).
After reviewed through this blog, I have learned a lot of new terms regarding big data which I have not heard before. For example, I know more about continuous intelligence. It is one of the method for improving decision making. The technology utilizes historical and current data to support the process of decision making in companies.
After all , this blog suggests that big data is a game changer in the AI industry which requires professionals to continually working on the development.