There is a mutually beneficial relationship shared between Big Data and Artificial Intelligence (AI) applications. This means the success of AI applications is dependent on the successful big data input. Currently, AI is being applied to assist businesses in serving meaningful insights from their data to improve decision-making. The key aspect here is that the more the machine learning models use data, the better and more efficient they become over time, leading to increased speed, efficiency and productivity across all operations within a business.
These key benefits highlight just how important the relationship between big data and AI is, and as a result, it is crucial to understand the way the technologies work with each other to deliver meaningful and actionable insights. To further understand their relationship, let’s look at three ways AI can be leveraged to deliver better insights using big data:
1. AI is creating new and enhanced methods for analyzing data
Deriving meaningful insights from data previously required a lot of manual effort for a business’s staff. Historically, software engineers used a SQL query or a list of SQL queries to analyze their data. Using AI, a variety of new and improved methods of acquiring data insights have now become available. As a result, AI and machine learning applications are now leading the path for developing new and more efficient methods for analyzing vast or massive quantities of data.
2. AI can be used to alleviate common data problems
The value derived from big data sets is intrinsically linked to data quality. Data of subpar quality has little to no worth in the business’s decision-making process. The ugly truth of several big data projects is that around ¾ of their effort is spent on cleaning and prepping the data for analytics. Machine learning algorithms in AI applications are capable of discovering outlier and missing values, duplicate records and standardized data for big data analytics.
3. Analytics become more predictive and prescriptive
Previously, data analytics was mainly used as a retrospective tool to conduct post-analysis on what has happened. Forecasts and predictions were basically historical analyses. Big data decisions were hence dependent on past and present data points with a linear ROI.
AI is paving the way for new opportunities that support enhanced predictions and forecasts. AI algorithms can be programmed to make a decision or execute an action depending on the forward-minded insights. Essentially, allowing big data to become more predictive and prescriptive.
The Future of Big Data and AI
In the coming years, we can expect there to be increased availability of intelligent enterprise software capable of leveraging big data to gain meaningful insights and solve problems. It will also lead to the development of new techniques for analyzing data to gain real-time insights. Reports made by AI applications will offer a higher level of context for proposed solutions for organizational problems than what was previously available. Accordingly, organizations will experience a greater and more significant ROI from all their stored data.
Currently, as the world copes with the effects of the pandemic, several data scientists are leveraging various big data and AI applications in order to assist in the fight against the virus. Big data and AI are therefore playing a key and transformative role in the way authorities respond to and deal with the Coronavirus outbreak.