Do you work in data for a big company? Data can have an extremely useful purpose in helping a company succeed, whether that’s because data drives marketing, sales, or other business functions. Data can help companies make smart decisions grounded in fact and help staff avoid bias or other conflicts that might impede their ability to work well.
But what about the role of artificial intelligence in big data analytics? How can the two work together, and how can businesses benefit from it? This informative article will share all about the role of AI in big data and how a business can leverage this for smart decision-making. If you’re interested in this topic, continue reading to learn more.
Table of Contents
What is Data Analysis?
Data analytics and its use in business, such as to drive strategy, is the process of using various datasets to help teams make informed and verified decisions to drive sustainable business growth and ultimately increase revenue and profit, which is the ultimate goal of any business. By using the right KPIs and tools, companies can overcome human biases, use data analysis to inform their decisions, and make the best business decisions that are aligned with viable
business strategies and can provide favourable outcomes in commerce. Businesses must build robust data analytics teams that are qualified through a Master of Business Analytics and similar certifications when considering implementing AI for big data.
At a fundamental level, using data analysis to inform business decisions and strategy means aiming toward key business goals by leveraging verified, analysed, and crucial information rather than relying on guesswork or shooting from the hip. And artificial intelligence can play a large role in this, as we’ll now explore, after a brief explanation of what big data is.
What is Big Data?
The term big data refers to huge, complex, and high-velocity datasets. Big data is the fuel that powers the evolution of the AI model’s decision-making. Big data can be explored and analysed for information and insights that companies can leverage to increase revenue and profit margins. Big data analytics is the use of processes and technologies, which include AI and machine learning, to effectively combine and analyse massive datasets with the end goal of identifying patterns and developing actionable insights that companies can utilise. This helps businesses make faster, better, data-driven decisions that have an overall net positive outcome for the business.
AI Tech and Big Data Analysis
Emerging AI technologies, such as machine learning and large language models (LLMs), have many advantages over traditional, human-powered methods in data analysis. AI can speed up processes, reduce costs, and improve business decision-making precision.
Organisations across various sectors such as insurance, banking, fintech, and finance can benefit from AI’s advanced capabilities in things like image recognition, language understanding, and strategy optimisation. By integrating big data analytics and robotic automation, AI can transform organisations’ processes from lead to gold and address various governance principles to help businesses manage risks effectively.
AI models can help generate deeper, meaningful insights from big data, improve knowledge tests, and even enhance data visualisation for better business decision-making. However, challenges do exist and present to companies looking to leverage AI for big data analysis, such as the need for firm investments in hardware to support human teams’ performance alongside AI technology.
The ongoing evolution of AI, which is driven by human-level artificial intelligence and societal engagement, is pushing for advancements in computing power. The public discourse around AI’s benefits and potential negative consequences calls for a strategic approach from businesses to harness its full potential in data analysis.
The Interconnected Relationship Between Big Data and AI
Big data and artificial intelligence have a synergistic, interconnected relationship. AI models require a massive scale of data to help them learn and improve decision-making processes. Big data analytics leverages AI for better, more precise data analysis. With this convergence of the two, companies can more easily leverage advanced analytics capabilities like augmented or predictive AI analytics and more efficiently glean actionable insights from their vast stores of data. With big data AI-powered analytics, organisations can empower their users with the intuitive tools, learning, and robust tech that they need to extract high-value insights from data. AI tools will foster data literacy across organisations, while everyone reaps the benefits of companies becoming truly data-driven entities.
By merging big data and AI analytics technology, companies can improve key business performance indicators and efficiency by:
- Personalising and optimising the performance of digital marketing and strategy campaigns
- Using intelligent decision support systems fueled by big data, AI, and predictive analytics to make effective business decisions
- Anticipating and capitalising on emerging industry and market trends, as informed by big data
- Analysing consumer behaviour and automating customer segmentation approaches
Limitations of AI in Big Data Analysis
Artificial intelligence has some limitations in big data analysis that bring challenges for utilisation and implementation. AI algorithms lack interpretability, making it hard to understand insights from data. In certain decision-making areas like insurance and finance, the opaque algorithms used by AI can pose risks and governance challenges for companies. Also, relying on historical data to train AI models restricts their adaptability to emerging strategies and novel data sources.
Although automation can indeed speed up and cut costs in data analysis, providing precision and avoiding negative outcomes requires careful consideration. The heavy computing power required for big models like GPT-4 demands significant hardware investments for organisations, possibly creating gaps in human performance and presenting barriers to tech access. Organisational AI transformation approaches need solid governance to handle the various societal and ethical risks linked with AI progress and analytics for big data.
A Big Data Summary
This informative article has covered the role of AI in big data analytics and how AI can be leveraged for big data analysis for business performance and strategy. We’ve also shared some of the limitations that this tech has.
