Augmented Analytics Market Major Players, Regional Segmentation & Forecast to 2030
Augmented Analytics Market Overview:
The global Augmented Analytics Market is expected to grow USD 35.6 billion by 2030 at a CAGR of 22.70% during the forecast period 2022-2030. The market is being driven by the increasing demand for data analytics solutions and the growing adoption of machine learning and artificial intelligence technologies.
Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation and insight explanation to augment how people explore and analyze data in analytics and BI platforms.
Key players in the augmented analytics market:
Some of the key players in the augmented analytics market include:
Augmented analytics offers a number of benefits over traditional data analytics solutions, including:
Increased speed and efficiency: Augmented analytics can automate many of the tasks involved in data analysis, such as data preparation and cleaning. This can free up analysts to focus on more strategic tasks, such as developing insights and making decisions.
Improved accuracy: Augmented analytics can use machine learning to identify patterns and trends in data that would be difficult or impossible to find using traditional methods. This can help analysts to make more informed decisions.
Increased engagement: Augmented analytics can use natural language processing and other technologies to make data more accessible and understandable to users. This can help to increase user engagement and adoption of data analytics solutions.
Applications of augmented analytics:
Augmented analytics can be used in a variety of industries, including:
BFSI: Augmented analytics can be used to improve fraud detection, risk assessment, and customer service.
Healthcare: Augmented analytics can be used to improve patient care, identify disease patterns, and develop new treatments.
Manufacturing: Augmented analytics can be used to improve product quality, optimize production processes, and reduce costs.
Retail: Augmented analytics can be used to improve customer targeting, personalize marketing campaigns, and optimize inventory levels.
Government: Augmented analytics can be used to improve public safety, reduce fraud, and make better policy decisions.