AI vs. Big Data

What is What, Terms and Predictions

Aug 10, 2021

3 min read

Artificial Intelligence and Big Data are often seen as contradictory constructs, rather than areas that can work hand in hand. But is this really the case? The following article deals with terms, predictions and tries to answer the questions like whether AI really replaces Big Data in the foreseeable future.

What is Artificial Intelligence?

Artificial Intelligence (AI in short) is concerned with the imitation of human thinking processes with the help of machines, especially computer systems. How does AI work? Generally speaking, AI systems work by ingesting vast amounts of labeled training data, analyzing the figures for correlations and patterns. The resulting patterns are then used for making predictions about future states. Chat Bots can be considered as an example, that make use of AI, since they are learning to answer the questions more concretely, the more information the get from previous users.[1]

What is Big Data?

Big Data refers to large volumes of data originating from various sectors and sources, that are stored, processed and analyzed using specialized solutions. [2] These different types of data originate, for example, from sensors, devices, video/audio, networks, log files, transactional applications, web and social media. Much of it, generated in real time and at a very large scale[3]. The term Big Data has already been present in science and practice for several years. Often, the challenges of Big Data, the 3Vs in particular, are refered to the constant growth of data (Volume), the increasing of Variety and Velocity and also the increasing speed of data changes [4].

How Big Data and AI complement each other?

Both areas are rather dependent on one another. Nowadays, sources of data are becoming more and more complex than traditional data sources, because they are being driven by AI, mobile devices, social media and the Internet of Things (IoT). [3] Therefore, one can conclude that AI depends on Big Data, since the latter provides the important data sets for the former being able to deliver a solid base for decision-making for the end user. Here a concrete example for a better understanding: Companies make use of AI and Big Data for scouting user ratings within the internet and social media networks. Therefore, issues can be quickly identified and resolved to improve customer goodwill, by using tools such as supervised learning and natural language recognition. [5]

Practical Examples

Newer approaches like Bring the Compute to the Data or Bring Machine Learning/Algorithms to the Data are a good example of how both fields interact with each other. Especially, since big providers like Google, Amazon and Microsoft provide link services such as databases and data warehouses with AI services, it is no longer necessary to integrate the data into other platforms or systems [6].

ML with Google BigQuery - Image by Author — ML with Google BigQuery – Image by Author

Tools like BigQuery ML democratize the use of Machine Learning. Data Scientists and Analysts can use BigQuery ML to build and run models directly within the data platform. Predictive analytics can help with business decision making. So in this context Data Science can be executed directly with and directly within Big Data technologies.

Summary

In conclusion, one can state that AI depends on Big Data. Only with the vast amounts of data, artificial intelligence technologies can be able to imitate human thinking processes. Therefore, both areas are dependent from one another. Therefore, new technologies and approaches such as IOT, ML or Self-Service-BI are needed to conquer the increasing data amounts and create a solid base for the company managements’ decision-making. In this case, it is important to note that both, Big Data and AI are not competing against each other, but rather depend on and benefit from one another.