What is the difference between AI analytics and traditional analytics?
Posted: Wed Jan 22, 2025 10:56 am
And because data analysis is automated, it removes dependencies on manual tasks, increasing the accuracy of results and timeliness of business intelligence reports. It also frees up time so luxembourg b2b leads employees can focus on more strategic and complex parts of their jobs.
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AI analytics uses machine learning algorithms to analyze big data, which enables it to process large volumes of complex, unstructured raw data quickly, accurately and easily. Traditional analytics, in contrast, requires more manual data analysis.
Even though traditional data analysis has been around for a long time, it has certain drawbacks that have led to the rising demand for AI analytics. For one, traditional analytics is not very effective in analyzing complex or large volumes of data.
More importantly, it can only analyze a limited scope of historical data to provide descriptive, diagnostic, predictive and prescriptive insights.
Bonus Resource: Get our top five AI social media marketing resources in one convenient toolkit. Download it for customizable templates and tips to drive smart AI adoption in your role and across your organization.
Get the toolkit
Want to know more? Discover how Sprout can help you harness the power of AI for social media marketing.
Schedule a demo
AI analytics uses machine learning algorithms to analyze big data, which enables it to process large volumes of complex, unstructured raw data quickly, accurately and easily. Traditional analytics, in contrast, requires more manual data analysis.
Even though traditional data analysis has been around for a long time, it has certain drawbacks that have led to the rising demand for AI analytics. For one, traditional analytics is not very effective in analyzing complex or large volumes of data.
More importantly, it can only analyze a limited scope of historical data to provide descriptive, diagnostic, predictive and prescriptive insights.