1. Increasing demand for advanced data analytics solutions to gain valuable insights and make data-driven decisions.
2. Rising adoption of cloud-based augmented analytics platforms for enhanced scalability and flexibility.
3. Growing focus on AI and machine learning technologies to automate and streamline data analysis processes.
4. Expansion of IoT and big data analytics, leading to the need for advanced data visualization and predictive analytics tools.
Industry
Report Coverage | Details |
---|---|
Segments Covered | Component, Deployment Mode, Organization Size |
Regions Covered | • North America (United States, Canada, Mexico) • Europe (Germany, United Kingdom, France, Italy, Spain, Rest of Europe) • Asia Pacific (China, Japan, South Korea, Singapore, India, Australia, Rest of APAC) • Latin America (Argentina, Brazil, Rest of South America) • Middle East & Africa (GCC, South Africa, Rest of MEA) |
Company Profiled | Microsoft, Qlik, Tableau, IBM, SAP, ThoughtSpot, MicroStrategy, SAS |
1. Data privacy and security concerns, particularly with the use of AI and machine learning algorithms for sensitive data analysis.
2. Lack of skilled professionals with expertise in augmented analytics and data science, leading to implementation challenges.
3. Regulatory complexities and compliance issues related to the use of augmented analytics for sensitive industries like healthcare and finance.