The Blueprint: Smart Analytics is a periodically refreshed analysis of the enterprise analytics services capabilities of key service providers, with an emphasis on the smart analytics sub-set of the Triple-A Trifecta of intelligent automation technologies.
The 2018 Blueprint builds on the previous years' research, including reports on the broad enterprise analytics services markets and sector-specific analyses. The scope for this study includes services across the data to insight lifecycle, including analytics consulting, data management, reporting and visualization, and advanced analytics.
Key Market Dynamics
Data and analytics take center stage as key business drivers: Data and analytics have found new stakeholders and executive support in 2018 as automation, AI, and machine learning have become commonplace terms in boardroom discussions. Managing data has become a strategic imperative for business growth, with renewed interest and accompanied investments across business functions.
Continued momentum with double-digit growth for most service providers: Smart analytics continues to be the biggest revenue driver within the digital portfolios of most global technology services firms in our research. The author observes double-digit growth for this market, with several providers reporting between 20% and 35% revenue growth YoY as the demand for smart analytics continues to grow exponentially.
The analytics services value chain is undergoing a complete change due to technology shifts: The proliferation of intelligent automation technologies, the mainstreaming of open source platforms and big data infrastructure, and trends in broader digital transformation are starting to change the face of data and analytics services. Enterprise clients are demanding new efficiencies and smarter processes across the board.
Leading service providers have been willing to invest in new services and solutions to support future growth. Examples include the use of:
- Machine learning for automating data discovery, cataloguing, and correcting master data
- NLP and virtual assistants to improve self-service
- RPA to auto-populate routine reports
- Machine learning to automate model validation and maintenance, and improve algorithmic accuracy and predictive and prescriptive capability through deep learning techniques.
Key Topics Covered:
- Introduction and Key Definitions
- Executive Summary
- Key Market Trends
- Research Methodology
- Blueprint Grid
- Service Provider Profiles
- Market Direction and Recommendations
- CSS Corp
- NIIT Technologies
- Fractal Analytics
- Tech Mahindra
For more information about this report visit https://www.researchandmarkets.com/research/xctlkd/smart_analytics?w=4