Dipanjana Das's Contact Details

Dipanjana Das's Company Details

TIBIL Solutions

, , United States • 51 - 200 Employees
Information Technology and Services

We are a data engineering and analytics company enabling organizations leverage data for competitive advantage. TIBIL enable businesses from Banking & Financial Services, Retail, Healthcare, Manufacturing, Social Sector verticals to achieve better agility, growth and profitability.Our name TIBIL is derived from Mayan script meaning "GOOD". Founded in 2010, TIBIL is headquartered in Bangalore with offices in Illinois and Hyderabad, India. We serve more than 60 clients in USA, Middle East, APAC and India. We have a strong leadership team with collective experience of 150+ years and pedigree of working in F500 companies.Our solutions help you achieve your business goals through reliable and intelligent data management. We offer data validation, data engineering and feature engineering services to integrate, verify, prepare and transform data into formats that can be accessed by analytical models and tools. We drive data analytics using new generation data analysis tools, ML/AI, and industry-grade statistical models to deliver advanced, real-time analytics.We leverage our iDEA framework to:1) Integrate and organize large volumes and diverse formats of data from disparate sources2) Transform the prepared data into derived variables3) Analyse the data and build models for analytical solutions4) Derive insights to help you architect key decisionsWe help you find answers for the following in your quest to derive insights for your business initiatives:1) Do we have all the data that I need?2) Have we considered all sources of data?3) Is our data accurate and reliable?4) How do we make sense of the data generated from initiatives such as IoT, mobility and cloudification?5) How do we convert these huge volumes of data into a format that I can leverage for analytics?6) How do we convert all my data to get visual reports for forecasting, app usage, user behavior patterns?7) How do we leverage ML and AI algorithms and models to convert data to business insights