The Rise of Augmented Analytics:
Businesses today are drowning in data. The sheer volume and complexity of information available have made it increasingly difficult for organizations to extract meaningful insights using traditional business intelligence (BI) tools and the expertise of specialized data scientists. This is where augmented analytics comes in. This game-changing technology combines the power of artificial intelligence (AI) with BI to empower non-technical users to uncover valuable insights and make informed decisions.
And everyone is already joining the party. Data shows israel whatsapp number data that the demand for augmented analytics is expected to expand at a moderate CAGR of 21.8% from 2023 to 2033.
This article will explore the key components of augmented analytics, its transformative impact on business users, and the AI-driven functions that are redefining the data analysis landscape.
What Is Augmented Analytics?
Augmented analytics is the use of AI, machine learning (ML), and natural language processing (NLP) technologies to automate the process of analyzing data.
It helps prepare data, generate insights, and explain these insights in an easy-to-understand manner. This enables both technical and non-technical data scientists to make informed decisions without deep expertise in data science.