Built with BigQuery: How to supercharge your product data with Google Cloud and Harmonya
Harmonya relies on BigQuery to build and maintains data pipelines and train and serve machine learning models for its product enrichment service.
Harmonya relies on BigQuery to build and maintains data pipelines and train and serve machine learning models for its product enrichment service.
In today's fast-paced, data-driven world, deeper data insights and faster time to value are paramount if you want your business to stay competitive and thrive. Decision-makers need instant access to all their data sources to make sound business decisions — and they need to have trust in their data. However, data quality is often overlooked. According to Gartner, poor data quality costs organizations an average of $12.9 million annually. What’s going on?
During the COVID-19 pandemic, telcos made unprecedented use of data and data-driven automation to optimize their network operations, improve customer support, and identify opportunities to expand into new markets. This is no less crucial today, as telcos balance the needs to cut costs and improve efficiencies while delivering innovative products and services.
The world is undergoing a remarkable transformation fueled by data. Organizations have accumulated silos across their data infrastructure to support various workloads, languages, tools, and formats because of technology limitations. These silos can have major consequences in the form of greater operational burden, security vulnerabilities, increased total cost of ownership, incomplete insights, and reduced agility.
Containers have emerged as the modern approach to package code in any language to ensure portability and consistency across environments, especially for sophisticated AI/ML models and full-stack data-intensive apps. These types of modern data products frequently deal with massive amounts of proprietary data.
Financial dashboards bring performance into focus by collecting the most important metrics and indicators in one location. But when organizations build their financial dashboards from the ground up, challenges often arise. A primary hurdle is making the right design choices to create dashboards that drive successful business decisions. To overcome this hurdle, it helps to incorporate ideas that have already been implemented, evaluated, and improved on by others.