Data Analytics

As data becomes the currency of the digital world, constraints like confidentiality, ownership, volume and quality of data are preventing companies from turning data into actionable insights. The paradigm of Edge analytics, real-time processing capabilities and advancements in AI/ML is helping companies leverage analytics for maximum business impact.  Analytics is delivering company growth through key insights that leads to new product creation and enhanced customer experiences.

Technology Platform: The right platform for data ingestion, data integration, data transformation and data storage considering cost constraints, data volume, and data growth considerations

Accurate Analytics Models: Measured insights into Machine Learning (Supervised, Unsupervised or Deep Learning), Vision-based analytics or Natural Language Processing (NLP) by considering the data characteristics in terms of volume and quality and ensuring the required amount of accuracy

Prioritization For Analytics Engagement: Identification and prioritization of business problems by working with function heads/business users of the customer while spotting trends and new business growth opportunities

Actionable Data Insights: Actionable insights/visualization from a data set by leveraging licensed data visualization/data discovery tools. We consider data volume, quality and regulatory compliance during each analytical engagement including platform selection, analytical model design, data visualization and business problem selection