Author: Bikash Nahata Scenario # 1: Thousands of files flood the data lake every day. These files are dumped
Archive for category: Technical
A Practical Guide to Setting Up Your Data Lakehouse across AWS, Azure, GCP and Snowflake
| Blogs, Data Engineering, Technical, Data Engineering, data lake, Data Lakehouse, Data WarehouseAuthor: Ganapathy Subramanian Today, most large enterprises collect huge amounts of data in various forms – structured, semi-structured, and
Building Recommender Systems to Help People Find their Dream Home within Minutes
| Blogs, Other Industries, Technical, AI for Real Estate, Recommender SystemsAuthors: Sushant Kulkarni, Astha Kumar, Nitin Jain Every time you watch your favorite web series on Netflix or shop
Building a Patient-Centric Ecosystem with Data Analytics
| Blogs, Lifesciences, Technical, AI for Industry, AI for lifesciences, lifesciences, patient servicesAuthors: Vinayak Gupta, Saurabh Gupta, Asif Ghatala Meet Michelle, a 66-year-old senior citizen living by herself and diagnosed with
How Insurance companies are using NLP to streamline application approval
| Blogs, Insurance, Technical, Insurance Analytics, NLPAuthor: Varun Balutia Let’s say you’re looking to invest for retirement. You want the investment to give you a
How AI can help CPG companies unlock real value through in-store trade promotions
| Blogs, CPG, Technical, CPG Analytics, smart merchandizing, trade promotion optimization, Trade PromotionsAuthors: Raghavendran Murugan, Sunitha Gunasekaran The battleground for capturing the attention of wholesalers, retailers, and consumers continues to heat
Improve the Accuracy of Data-Driven Decision-Making, with A/B Testing Done Right
| Blogs, Technical, A/B Testing, Customer Analytics, data driven decisionsAuthor: Abhideep Jain A/B tests, as they are called, are quite common in the pharma industry. Large clinical trials
Why Self-Service BI is Important in an Agile Business Scenario
| Blogs, Data Engineering, Technical, BI tools, Business Insights, Data Engineering, Modern BIAuthors: Suganthi Murugesan, Varalakshmi Myilsamy In organizations where data-driven solutions are valued, Data democratization is becoming a necessity. Data virtualization
Improving Data Quality with the help of Tiger’s Data Quality Framework
| Blogs, Data Engineering, Technical, Data Engineering, data quality, Tiger data quality frameworkAuthors: Ajeeth Kumar A, Chetan Jaamdar, Gaurav Kantrod According to Gartner, poor data quality could cost organizations up to $12.9 million
Patient Services: Pharma’s Answer to Supporting Patients with Rare Diseases
| Blogs, Healthcare, Lifesciences, Technical, AI for lifesciences, lifesciences, patient servicesAuthors: Vinayak Gupta, Saurabh Gupta, Asif Ghatala Patients suffering from rare diseases and their caregivers often struggle to manage
Recent Posts
- Unleash the Full Potential of Data Processing: A Roadmap to Leveraging Databricks
- A Practical Guide to Setting Up Your Data Lakehouse across AWS, Azure, GCP and Snowflake
- Building Recommender Systems to Help People Find their Dream Home within Minutes
- Building a Patient-Centric Ecosystem with Data Analytics
- How Insurance companies are using NLP to streamline application approval
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