How can AI optimize data analysis?
Posted: Sun Dec 22, 2024 5:12 am
In recent months, the market has been shaken by the arrival of the Open AI tool, ChatGPT, a resource that creates texts, songs, poems and even essays. In just five days, it broke the record of 1 million users and generated new discussions about the role of AI in everyday work.
Educators, in turn, were apprehensive because the new feature could facilitate plagiarism and copying without any kind of reflection. Do you know what ChatGPT's secret is? Data analysis.
In this content, you will understand how AI helps analyze data and perform tasks such as ChatGTP, among others. Check it out:
Summary:
What is data analysis?
What are the main advantages of data analysis?
What are the data analysis methods?
How can AI contribute to data analysis?
How can AI optimize data analysis?
AI and the fundamentals of data analysis
What is data analysis?
It is undeniable that data has stimulated the emergence of new technologies in record time. It has never been so easy to make decisions based on information that, once processed, becomes a business strategy.
With the help of analysts, AI interprets data that becomes models and helps optimize processes, making them faster, more assertive and intelligent.
In other words: AI can identify behavior patterns of a group of consumers, for example, to offer tailored solutions.
This way, the company can make data-driven kuwait whatsapp number code decisions more accurately and based on tangible, protected information rather than perceptions. “Interpreting information about the habits of this customer or group of customers” is the function of AI.
What are the main advantages of data analysis?
There are several, but the three main ones are:
Improve products and services: it is possible to map purchasing behaviors, preferences, consumption patterns, occurrences, among other information. From there and based on customer knowledge, create more appropriate products and services.
Strengthen market presence: whether on social media or through distribution channels, the company is able to choose the best means to showcase products and services, which helps to communicate more efficiently with the customer.
Correct your operating strategy: through constant monitoring, the company is able to correct operating strategies, intensifying those that yield results.
What are the data analysis methods?
The first step before analyzing a large amount of data ( Big Data Analytics ) is to clean it. To do this, the professional needs to remove duplicates, discrepancies, and incomplete information, discard information that is not useful, correct errors, and identify gaps. Once this is done, it is possible to begin data analysis, which can be:
Descriptive: considered the starting point for analysis, this aims to describe real scenarios and map behaviors and trends based on them;
Diagnostics: in this analysis, the aim is to establish the consumer profile so that the company's actions are more assertive;
Predictive: In this model, information is used to project scenarios and trends.
Prescriptive: the idea here is to evaluate the scope of the decisions and what they may entail. This way, the best direction can be defined.
How can AI contribute to data analysis?
After understanding the importance of data analysis and the types of assessments that can be made, it is now time to understand how AI can help with this assessment.
Medicine, for example, especially radiology, is benefiting from AI in the diagnosis of imaging exams. Some laboratory networks in Brazil have already adopted the technology developed in Israel to diagnose chest CT scans in less than 20 minutes using AI.
The response is so complete that the tool can map small clots capable of causing a pulmonary embolism, for example, optimizing the time taken to perform exams by up to 40% .
Of course, the AI assessment does not replace the medical opinion, but it helps to detect risks and, therefore, request additional or even more specific tests.
In the case of diagnosis, AI compares images from several other exams, reducing the chances of error by providing a more assertive diagnosis and, consequently, reducing the number of invasive procedures.
AI is also present in people's daily lives: in banking apps, in surveillance cameras with facial recognition (a method that is banned, it is true, in some countries because only certain models are used), in controlling products in stock, in homes with smart assistants and even in apps that map routes, among others.
The most recent and anticipated use is in car automation. The industry is conducting tests to make cars more economical, fully autonomous and extremely safe. This type of car is also the subject of studies in Brazil .
How can AI optimize data analysis?
It is already known that AI has the ability to evaluate a large amount of information and, in this way, extract insights or patterns. But how exactly is this done?
The data is analyzed by software that identifies and groups it with the help of machine learning and deep learning, processes that help to break down information, such as an image, into smaller models to search for matches.
However, this process needs human expertise to understand the algorithms .
Once this is done, reports are generated that provide information to the strategic areas of the companies. Although the expansion of AI is a reality, there are also growing discussions around the conscious use of this technology.
One such discussion was recently raised by MIT (Massachusetts Institute of Technology), which created Verta – a start-up that jumped straight from the laboratory to help companies monitor and manage machine learning models, making them more secure.
AI and the fundamentals of data analysis
Through the Verta platform, MIT scientists can track models, audit and test each one before implementation, and then monitor performance.
The idea is that products are developed with the help of AI, but in the correct way – which, according to critics, does not yet happen with ChatGPT, for example, which, by gathering hundreds of pieces of information from unsafe sources, can provide incorrect results.
According to MIT, AI is extremely important, but it is also essential that the data source is valid. In other words, once again, it is human error that will certify or compromise the validity of the information .
That's why the institute's platform helps track different versions of models and helps understand how they were built, how data was used and what checks were made.
There is undoubtedly a long way to go for companies to learn about AI. But the good news is that this journey can be shortened by experienced technicians and solutions like those offered by BigDataCorp.
Talk to our team and understand how AI can help optimize the performance of your company's products and services safely and assertively.
Educators, in turn, were apprehensive because the new feature could facilitate plagiarism and copying without any kind of reflection. Do you know what ChatGPT's secret is? Data analysis.
In this content, you will understand how AI helps analyze data and perform tasks such as ChatGTP, among others. Check it out:
Summary:
What is data analysis?
What are the main advantages of data analysis?
What are the data analysis methods?
How can AI contribute to data analysis?
How can AI optimize data analysis?
AI and the fundamentals of data analysis
What is data analysis?
It is undeniable that data has stimulated the emergence of new technologies in record time. It has never been so easy to make decisions based on information that, once processed, becomes a business strategy.
With the help of analysts, AI interprets data that becomes models and helps optimize processes, making them faster, more assertive and intelligent.
In other words: AI can identify behavior patterns of a group of consumers, for example, to offer tailored solutions.
This way, the company can make data-driven kuwait whatsapp number code decisions more accurately and based on tangible, protected information rather than perceptions. “Interpreting information about the habits of this customer or group of customers” is the function of AI.
What are the main advantages of data analysis?
There are several, but the three main ones are:
Improve products and services: it is possible to map purchasing behaviors, preferences, consumption patterns, occurrences, among other information. From there and based on customer knowledge, create more appropriate products and services.
Strengthen market presence: whether on social media or through distribution channels, the company is able to choose the best means to showcase products and services, which helps to communicate more efficiently with the customer.
Correct your operating strategy: through constant monitoring, the company is able to correct operating strategies, intensifying those that yield results.
What are the data analysis methods?
The first step before analyzing a large amount of data ( Big Data Analytics ) is to clean it. To do this, the professional needs to remove duplicates, discrepancies, and incomplete information, discard information that is not useful, correct errors, and identify gaps. Once this is done, it is possible to begin data analysis, which can be:
Descriptive: considered the starting point for analysis, this aims to describe real scenarios and map behaviors and trends based on them;
Diagnostics: in this analysis, the aim is to establish the consumer profile so that the company's actions are more assertive;
Predictive: In this model, information is used to project scenarios and trends.
Prescriptive: the idea here is to evaluate the scope of the decisions and what they may entail. This way, the best direction can be defined.
How can AI contribute to data analysis?
After understanding the importance of data analysis and the types of assessments that can be made, it is now time to understand how AI can help with this assessment.
Medicine, for example, especially radiology, is benefiting from AI in the diagnosis of imaging exams. Some laboratory networks in Brazil have already adopted the technology developed in Israel to diagnose chest CT scans in less than 20 minutes using AI.
The response is so complete that the tool can map small clots capable of causing a pulmonary embolism, for example, optimizing the time taken to perform exams by up to 40% .
Of course, the AI assessment does not replace the medical opinion, but it helps to detect risks and, therefore, request additional or even more specific tests.
In the case of diagnosis, AI compares images from several other exams, reducing the chances of error by providing a more assertive diagnosis and, consequently, reducing the number of invasive procedures.
AI is also present in people's daily lives: in banking apps, in surveillance cameras with facial recognition (a method that is banned, it is true, in some countries because only certain models are used), in controlling products in stock, in homes with smart assistants and even in apps that map routes, among others.
The most recent and anticipated use is in car automation. The industry is conducting tests to make cars more economical, fully autonomous and extremely safe. This type of car is also the subject of studies in Brazil .
How can AI optimize data analysis?
It is already known that AI has the ability to evaluate a large amount of information and, in this way, extract insights or patterns. But how exactly is this done?
The data is analyzed by software that identifies and groups it with the help of machine learning and deep learning, processes that help to break down information, such as an image, into smaller models to search for matches.
However, this process needs human expertise to understand the algorithms .
Once this is done, reports are generated that provide information to the strategic areas of the companies. Although the expansion of AI is a reality, there are also growing discussions around the conscious use of this technology.
One such discussion was recently raised by MIT (Massachusetts Institute of Technology), which created Verta – a start-up that jumped straight from the laboratory to help companies monitor and manage machine learning models, making them more secure.
AI and the fundamentals of data analysis
Through the Verta platform, MIT scientists can track models, audit and test each one before implementation, and then monitor performance.
The idea is that products are developed with the help of AI, but in the correct way – which, according to critics, does not yet happen with ChatGPT, for example, which, by gathering hundreds of pieces of information from unsafe sources, can provide incorrect results.
According to MIT, AI is extremely important, but it is also essential that the data source is valid. In other words, once again, it is human error that will certify or compromise the validity of the information .
That's why the institute's platform helps track different versions of models and helps understand how they were built, how data was used and what checks were made.
There is undoubtedly a long way to go for companies to learn about AI. But the good news is that this journey can be shortened by experienced technicians and solutions like those offered by BigDataCorp.
Talk to our team and understand how AI can help optimize the performance of your company's products and services safely and assertively.