Do You Know The Difference Between Data Analytics & Machine Learning?

Artificial Intelligence is a powerful technology, which has already transformed many industries worldwide. Many organization gets into the competition to comprehend to enhance their business.
Artificial Intelligence is not just emerged recently. This technology has been in talks for quite a long ago. But in these current years, the computing power, cloud-based service, and use of AI in place of humans have changed a lot.
Implementation of Artificial intelligence in marketing is growing and is anticipated to meet over $40 billion by the end of 2025. Maximum Chief Marketing Officers (CMOs) are well aware of AI, but many are not aware of the advantage of Artificial Intelligence and don’t know how they can embrace their business and promote their brand.
So, before adopting AI technology, it is very much necessary to understand and find out the difference between data analytics and AI machine learning.

Data Analytics

Data Analytics is used for retrieving valuable insights from gathered data. These insights are used for making efficient business decisions that help to increase the performance of organizations. Have a look at the major three types of Data Analytics.

Descriptive Data Analytics

Descriptive data analytics is the analysis of historical data, what has already occurred. It helps businesses to understand the transformations and how things are going with data. The major focus of descriptive analytics is to detect appropriate reasons behind precious success or failure in the past.
The best example to describe descriptive analytics is how we get results from the webserver using Google Analytics tools. These results help to understand what was done in the past and validate that a campaign was successful or not based on factors such as page views.

Predictive Data Analytics

Predictive data analytics tells us what is going to happen in the future based on previous experience. It helps the business to forecast future behavior and expected upcoming results. The companies that adopt predictive analytics can use historical data and validate with the present data to forecast the future with the help of predictive analytics approaches.

Prescriptive Data Analytics

Prescriptive data analytics is an advanced step in predictive analytics. It helps the organization to capitalize on vital business metrics.
Let’s take an example to understand how data analytics boost real-time businesses.
Now all we are familiar with Netflix. It is a very big brand utilizing data analytics to target advertising. It has more than 100 million subscribers. With the help of data analytics, Netflix not only gathers vast data but also considers the interests of the subscribers. By applying data analytics strategies, Netflix is increasing its business immensely.

AI Machine Learning

Machine learning has a similar concept with predictive analytics with one major difference. The AI-powered system can make predictions, research, and learn automatically.
Artificial intelligence is a blend of different technologies. Among those, machine learning is the most important technology used for solving complex customer-centric issues. Innovative machine learning models make predictions from data without any help from human beings. There is no need to code every time, when we feed with new data.
Let’s see the benefit of using AI Machine Learning on Social media.
Staring from ads to customizing your news feed, everything is possible with Machine learning models. AI-based devices and smart tools provides recommendations and suggestions for people when they do online purchases.
Machine learning algorithm understands the customer behavior with experiences. For instance, Facebook focuses the friends you are connected with, the profiles you are often visiting, your links, etc. Based on this analysis, machine learning models provides a list of suggestions that you can become friends with.

Conclusion

Every technology of Artificial Intelligence plays its significant role in doing specific business tasks. Machine learning, deep learning, and other interesting technologies have their significance.
In this article, as discussed above, we realized that Data Analytics is a process of reviewing previous data to predict future events and make the right decisions. Whereas, AI Machine Learning analyzes the data deeply, learns from it, and forecasts results that have to occur in the future.
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