Smart data for companies: the first step towards BI
Posted: Wed Dec 11, 2024 9:09 am
More and more companies are embracing digital transformation by boosting their businesses with smart data. And the reason is simple: decision-making with smart data becomes more precise and accurate.
However, smart data is not just about having data. It is about knowing how to use it, maintain it and optimize it. In other words, what matters is the quality of the data. That is why smart data is the first step towards Business Intelligence (BI).
Why is smart data relevant for companies?
We can say that Smart data is all the data impacts of overseas chinese consumers in uk that comes from Big Data, but filtered, managed and optimized with a value-based approach. If artificial intelligence methods are also added, it is possible to transform this data into business opportunities.
With smart data, decision-making is more coherent, because the higher the quality of the data, the better prepared it is to be analyzed more quickly and better. Therefore, the data extracted with smart data can be used directly.
Companies that invest in smart data are not only investing in owning data, but also in providing intelligence and value to that data so that it can be used in business decision-making.
Differences between smart data and big data
Although these terms are often confusing, the truth is that their objectives, the type of information, and the quality of the data are different.
In terms of the type of data or information, big data is the quantity of information and smart data is the quality of that information. If we take into account the quality of the data, big data stores a large amount of data without discretion, while smart data describes data that has been filtered and prepared to be used directly, as it is error-free.
Business Intelligence techniques for companies
Business intelligence (BI) combines business analytics, mining, visualization, data tools, and data infrastructure. It incorporates not only data but also best practices that help businesses make data-driven decisions.
Implementing business intelligence models in a business means having a comprehensive view of all the organization's data, no matter how small it is. In addition, it is about using this data to drive change, eliminate inefficiencies and adapt quickly to market changes. Something so important in the economic and business context in which we operate today.
Some BI processes for companies are:
Data mining
Data mining aims to discover trends in more complex data sets through databases, statistics, and machine learning.
Reporting
Report generation is another of the Business Intelligence applications or techniques for companies. Presenting data in reports makes it easier for everyone involved to draw conclusions and make decisions.
Descriptive analysis
Through BI we can have preliminary data to discover what happened at a given time.
However, smart data is not just about having data. It is about knowing how to use it, maintain it and optimize it. In other words, what matters is the quality of the data. That is why smart data is the first step towards Business Intelligence (BI).
Why is smart data relevant for companies?
We can say that Smart data is all the data impacts of overseas chinese consumers in uk that comes from Big Data, but filtered, managed and optimized with a value-based approach. If artificial intelligence methods are also added, it is possible to transform this data into business opportunities.
With smart data, decision-making is more coherent, because the higher the quality of the data, the better prepared it is to be analyzed more quickly and better. Therefore, the data extracted with smart data can be used directly.
Companies that invest in smart data are not only investing in owning data, but also in providing intelligence and value to that data so that it can be used in business decision-making.
Differences between smart data and big data
Although these terms are often confusing, the truth is that their objectives, the type of information, and the quality of the data are different.
In terms of the type of data or information, big data is the quantity of information and smart data is the quality of that information. If we take into account the quality of the data, big data stores a large amount of data without discretion, while smart data describes data that has been filtered and prepared to be used directly, as it is error-free.
Business Intelligence techniques for companies
Business intelligence (BI) combines business analytics, mining, visualization, data tools, and data infrastructure. It incorporates not only data but also best practices that help businesses make data-driven decisions.
Implementing business intelligence models in a business means having a comprehensive view of all the organization's data, no matter how small it is. In addition, it is about using this data to drive change, eliminate inefficiencies and adapt quickly to market changes. Something so important in the economic and business context in which we operate today.
Some BI processes for companies are:
Data mining
Data mining aims to discover trends in more complex data sets through databases, statistics, and machine learning.
Reporting
Report generation is another of the Business Intelligence applications or techniques for companies. Presenting data in reports makes it easier for everyone involved to draw conclusions and make decisions.
Descriptive analysis
Through BI we can have preliminary data to discover what happened at a given time.