AI/ML
CPG R&D: the next big opportunity for digital transformation
Consumer Goods and F&B enterprises are hitting a critical innovation bottleneck. Traditional R&D strategies are failing to keep pace with market dynamics—product…
AI enabled real-time analytics improves fraud detection for banks
A fraud detection system scanning thousands of transactions can miss subtle red flags hidden in complex patterns. A seemingly legitimate transaction from…
Maximizing Project Success through JIRA Data Upcycling
JIRA has long been a staple in the world of project management, particularly for software development teams. Its robust features provide excellent…
How data-driven strategies can strengthen risk management in corporate banking
For decades, risk management relied heavily on historical data and reactive measures. Loan approvals were based on heuristic records, fraud detection focused…
6 data engineering fundamentals to accelerate generative AI deployment in banking
Generative AI-based models are quickly becoming essential solutions for enhancing operational efficiency, improving customer experiences, and mitigating risks in the banking and…
Scalable data architecture to create seamless digital banking experiences
The need for seamless banking experiences and personalized services is driving banks to leverage data and analytics for effective decision-making. According to…
7 essential skills for building a successful career in Data Science
According to the US Bureau of Labor Statistics, data scientist jobs are predicted to increase by 36% between 2021 and 2031. This…
Sigmoid’s 7 step approach for big data project success
A scoping exercise is the holy grail of your data project success be it Data Science, Product, or Data Engineering. In our…
Defining the right data analytics KPIs to drive business success
Business leaders often find it challenging to determine the right success metrics to assess the impact of Data and Analytics(D&A) programs. A…