In this post, we will talk about the difference between Big Data and Artificial Intelligence, two driving factors behind various technological innovations that have been developing today’s digital environment and Industry 4.0.
These two trends share the same objective: To get the most out of the enormous amount of data currently generated. On the one hand, Big data refers to the storage and processing of gigantic amounts of structured, unstructured and semi-structured data, all with great potential to be extracted and organized in such a way that they provide information of high value to organizations and companies.
On the other hand, Artificial Intelligence consists of a combination of algorithms proposed to design and develop machines that can imitate the functions and logic of a human being (for example, learning, reasoning and making decisions).
Importance of Big Data and AI, The true importance of Big Data for companies lies in the possibility of optimizing the solution to problems that already have an answer, solving issues that do not seem to have an answer, and finding problems that nobody knew existed. In short, it offers companies a new point of view and a more clear and more concise perspective.
The data can be reorganized by having a large amount of information; thus, difficulties can be identified quickly and understandably. On the other hand, artificial intelligence is a basis for automatic learning and the future of those complex processes in terms of decision-making.
Its use makes possible the detection of fraud, compelling predictions of store purchases and virtual help for customers, among many other benefits. This technology is essential in the daily environment and affects many other sectors.
Many large companies such as Amazon or Facebook consider that AI is the one that will mark a pattern and difference between companies. What is the relationship between Big Data and Artificial Intelligence? Although these two concepts revolve around data, each has very different functionalities. There is a ‘reciprocal‘ relationship between Big Data and Artificial Intelligence.
Big Data functionalities: Big Data acts as an input which receives a large group of data that needs to be processed and standardizes it to turn it into valuable and high-value information.
Artificial Intelligence functionalities: AI is the consequence of this process. It consists of a group of software that takes advantage of the output created by these results to develop algorithms that allow programs and mechanisms to generate intelligent behaviour and reason as humans do, offering various advantages and benefits for companies.
Big Data is, for this reason, the fuel on which AI works. The latter feeds on the processed data, analyses and learns from it, generating and recognizing patterns and developing sophisticated analytical solutions for various sectors.
The increase in data and the high speed of its processing have made possible the development of Artificial Intelligence, which uses all this information to analyze the environment and act on it later. However, they commonly need to avoid buying these terms since they are two concepts that feed off each other and always go hand in hand.
The role that Big Data plays in AI As we mentioned before, artificial intelligence requires data to build its intelligence, initially, continuously, and later. The larger and broader the amount of data that AI can access, the more things machines can learn, and for this reason, the more accurate and efficient their results can be.
As AI becomes more innovative, less human intervention is required to control processes and monitor what machines are running. AI lives its continuous learning phase, constantly fed with data.
In the same way that Big Data turns out to be necessary for Artificial Intelligence, the same happens to the contrary. Such vast amounts of data would only be as meaningful with AI models, which can unlock and realize the potential of these data stores and transform them into their intelligence.
Difference Between Big Data and Artificial Intelligence
We have already talked about this. Still, we will mention in a little more detail some of the most relevant characteristics of each technology:
Big Data: In what is called the data age, companies can have a large amount of information from which they can make strategic decisions.
Descriptive Analytics: How has the business been performing so far?
Predictive Analytics: How will the business work?
Prescriptive Analytics: What do we do to optimize our business?
Artificial Intelligence: As we already discussed, AI gives meaning to the data. You can identify which ones will be useful while discovering patterns between them to optimize business processes.
Machine Learning and Deep Learning: You can learn from data to get new insights. Reinforcement Learning – Find the best strategies from the data.
Natural Language Processing: Extract the value of information in audio and text.