Today, data governance is under the spotlight. With over 1,000 AI-related policies now active across 69 countries, businesses are under more pressure than ever to keep track of where their data lives and how it’s used. Microsoft recently added AI-focused governance tools and pay-as-you-go pricing for its Purview suite, signaling
Every second, billions of connected devices send data from sensors, machines, vehicles, and smart infrastructure. Managing this flow has become a critical challenge for organizations deploying Internet of Things (IoT) solutions. IoT data management covers how businesses collect, store, process, and govern device-generated data, turning raw signals into useful insights
Imagine a leading US retailer preparing for a massive system upgrade. They migrate customer data from legacy databases to a cloud-based AI analytics platform, only to discover mid-process that sales forecasts are off by 15%—not due to bad algorithms, but because a forgotten ETL transformation from two years ago doubled
When companies start evaluating analytics consulting partners, the comparison is rarely between global tech giants. It usually comes down to firms that specialize deeply in data engineering, AI implementation, and enterprise modernization. That is where the discussion around Kanerika vs Tiger Analytics begins. Both companies operate in the data and
The short answer: DBT, Dataform, and Airflow are not interchangeable. They solve different problems at different layers of the data stack. DBT and Dataform transform data inside the warehouse. Airflow orchestrates workflows across systems. Most mid-to-large enterprises end up running DBT and Airflow together. Dataform is a strong option only
