Data science has become a buzzword across industries, attracting organizations eager to tap into its potential. However, the reality of implementing data science in the enterprise often falls short of expectations. A survey conducted by NewVantage in January 2019 revealed that 77% of companies face challenges with business transformation, resulting in three-quarters of data projects failing to deliver value. Gartner, a prominent research and advisory firm, has consistently criticized the success of data science initiatives. Their January 2019 report stated that even analytical insights won’t drive business results until at least 2022. It’s clear that achieving success in data science is an uphill battle. The hype around data science and AI has led to inflated expectations, while the track record of these projects and teams is heading towards disappointment. The gap between perception and reality needs to be addressed to avoid falling into the pit of failure.
How Data Science increases the value of Businesses?
- Data Modeling Using Neural Networks, Machine learning and Deep Learning
- Data Modeling and Algorithms Deployments on Docker, Kubernetes, On-Premises or Public Cloud
- Generate Intelligent bits of knowledge in Real-Time
- Operational and Cognitive Intelligence
- Enhance use of IT foundation
- Increase labor force cooperation
- Develop tweaked measurable models and calculations
- Leverage progressed client, operational and IoT investigation
- Generate and convey wise experiences in close to ongoing
We assist our customers with diminishing income spillages and lift primary concern profitability utilizing progressed information science arrangements. With our team of experts, you can explore new market opportunities and discover innovative ways to design and optimize operations.