Artificial intelligences requires a huge amount of data and is viewed to have vastly superior capabilities when compared to Big Data analytics (which also uses a lot of data). So, is big data analytics the little brother of AI?

While it’s an interesting analogy, calling Big Data Analytics the “little brother” to AI isn’t entirely accurate. It’s more appropriate to view them as related but distinct fields that complement each other. Here’s a more nuanced perspective:

1. Historical Development:

Big Data analytics emerged earlier and laid the groundwork for many AI applications. In this sense, it could be seen as a precursor rather than a “little brother.”

2. Relationship:

Big Data and AI have a symbiotic relationship. AI often relies on Big Data for training and insights, while Big Data analytics can be enhanced by AI techniques.

3. Complexity:

AI generally involves more complex algorithms and can perform tasks that mimic human intelligence. Big Data analytics, while sophisticated, typically focuses on finding patterns and insights in large datasets.

4. Autonomy:

AI systems can make autonomous decisions, while Big Data analytics usually requires human interpretation of results.

5. Scope:

Big Data analytics is more focused on deriving insights from large datasets, while AI encompasses a broader range of capabilities, including decision-making, natural language processing, and computer vision.

6. Interdependence:

Many modern AI systems rely on Big Data for training and operation. Conversely, Big Data analytics often employs AI techniques to improve its capabilities.

7. Specialization:

Both fields require specialized skills, but in different areas. Big Data specialists focus on data management and statistical analysis, while AI specialists often delve into machine learning algorithms and neural network architectures.

Rather than viewing Big Data analytics as subordinate to AI, it’s more accurate to see them as distinct but interrelated fields. Both have their own strengths and applications, and they often can work together to create powerful solutions in various industries, as demonstrated in this article with different expert opinions..