AI vs Big Data – Everything You Need to Know

Today, there’s a lot of buzz around artificial intelligence and Big Data for their power and effectiveness. Together with human intervention, these two technologies give a new dimension to computer computing and boost organisations’ cognitive abilities. In this guide, we’ll explore what Big Data and AI are, how they work together, and what the future looks like for both technologies.

So let’s get reading!

What is AI? 

AI is a widely popular branch of computer science used to build intelligent machines to carry out tasks that demand human intelligence. There are four types of artificial intelligence:

• Reactive machines – Follows basic AI principles to perceive and react to real-world activities; no memory, and limited specialised duties
• Limited memory – Ability to store previous data and make predictions; has greater future possibilities
• Theory of mind – Theoretical concept; understands the ways living things analyse and think, leading to behavioural changes and creating a connection between AI and humans.
• Self-awareness – Such AI involves a high level of understanding of one’s surroundings and emotional state.

Famous examples of AI include self-driving cars, Alexa, Siri, and other intelligent assistants, chatbots, and so on. 

How Is AI Transforming the World?

• More Job Role

While reports suggest that over 75 million jobs will disappear with AI, experts believe it may create 133 million new and advanced job roles. They further stated that the new job roles would allow the workers to focus on jobs they are most satisfied with. 

• Bridging Language Gaps

AI-powered tools are eliminating the language barrier with their unique languages. Whether translating speech and text or teaching a new language, AI offers a personalised experience to quicker understanding.

• Creative Computational Activities

Computer scientists are now experimenting with their “creative side” and creating different software to perform specific tasks and solve any problem thanks to AI. 

• Advance Health Care

AI has made health care a lot more accessible, which will only improve in the coming days. From AI-powered medical chatbots to consulting physicians online and symptoms checking, everything can be done from an app in a safe, affordable, and convenient manner. 

• Efficient Public Administration

Although AI-powered tools come with their restrictions, there are ample possibilities to transform government activities. For example, methods like role-playing and gamification can help the government officers analyse different complex cases, understand the challenges associated with the system, pay for assignments provide a better solution. 

What Is Big Data?

Big Data is large volumes of datasets that are challenging to analyse and interpret by regular data management systems or humans. However, when analysed with modern tools, businesses can retrieve quality information to make informed business-related decisions. 

There are three primary properties of most Big Data sets:

• Volume – includes millions of data points, regardless of the importance
• Velocity – refers to the Big Data application where data is analysed and interpreted for the latest findings.
• Variety – contains various data sets within the database and uses different data analytics programs to correlate data

Importance of Big Data 

The significance of Big Data is no longer about how much data you have in your database but how you use it. Analysing data from sources can help you:

• Reduce costs
• Reduce decision timing
• Develop new products
• Make smart decisions
• Determine the causes of issues
• Recalculate risk portfolios
• Fraudulent activities

How Does Big Data Work?

Businesses use five significant steps to work with structured, unstructured, traditional, and semistructured data.

• Big Data strategy – A strategy to improve how businesses gather, store, manage, and use data and share with outside sources. It sets the stage for developing an organisation’s existing and future tech initiatives.
• Big Data sources – Knowing data sources like social media platforms, streaming data from IoT and IT systems, cloud data sources, or data from open sources like government data sources.
• Big Data management – The latest computing systems are quick and powerful to analyse, manage, and store large sets of various types of data quickly. They access and ensure quality checks for data analytics.
• Data analysis – With technologies like in-memory analytics and grid computing, companies can gain insight and value from data.
• Data-driven decisions – Accurate analytics leads to more accurate decisions. Competitive businesses use analysis reports to make data-driven decisions for more profits.

AI vs Big Data: Major Differences 

Big Data is the raw, large datasets that should be structured and integrated to make them useful for the company, whereas AI is the ultimate result of data processing. 

AI is about making better decisions and doing things better without errors. AI-enabled tools are specially designed to analyse and interpret data and find solutions accordingly. With the successful use of machine learning, computers learn to react differently to different situations and predict actions in the future for similar conditions.

Big Data is extensive, varied datasets that include transactional data, structured and semistructured data with unique uses, and mainly depends on gaining insight. For instance, when you stream shows on Netflix, how do you think it suggests shows and movies similar to what you usually watch? Again, it deduces your interests and advises accordingly. 

How Does AI and Big Data Work Together?

Even though AI and Big Data are different technologies, they work well as AI is mainly dependent on data for building intelligence using ML. Big Data segregates “useful” data from large datasets so that AI or ML can use it. Also, Big Data is essential for data learning. AI needs data to upgrades its actions and makes adjustments, so Big Data provides data continuously. 

The more data Big Data feeds in to processors, the better is the outcome. It improves how algorithms study behaviour and learn by trial and error. So it’s clear that the more data an AI-powered tool has, the higher are the chances of achieving accurate results. 

In the past, there weren’t any advanced processors, quality data sets, or fast internet facilities to generate real-time data, but today everything is available for designing a better tomorrow. From fast processors, massive data sets to high-speed internet facilities, there’s no use of AI without Big Data. 

AI And Big Data: The Future

AI and Big Data can achieve more combined. When data is fed into an AI engine, it becomes more competent to function without errors. The evolution will continue in the coming years to minimise human involvement. AI algorithms will need more data to process information and provide accurate real-time results based on interpretation.  Hence, it’s safe to say that Big Data will continue to grow as AI is now the most popular option for automating tasks and saving business resources. 

Conclusion

These days organisations extensively use Big Data and AI to improve their business operations and provide seamless customer service. Although there are different integrating techniques, data specialists and AI engineers should choose the methods that generate the best results. Therefore, companies should train their tech and data professionals to upgrade their skills to make optimum use of these two emerging technologies.