By using real-time data analysis and historical data analysis (submitted to anomalies and patterns detection), data scientists are able to detect and prevent potentially fraudulent activity before it occurs.
Generate, trough data, additional revenues by automating recommendations with intermediaries, making targeted interactions with customers possible.
Discover how to add value to your retail business and to personalize each customer engagement trough by integrating a multichannel data approach across your real-time reporting and your data science models.
Digazu’s platforms will help the companies leveraging the value of their data, by extracting data only once, sharing the transformations on data, and loading transformed data multiple times.
Today’s business are trying to become more data centric or to develop their data culture. To do so they have to start leveraging insights from their data. Therefore, ETLs (extract, transform, and load) are essential in data integration strategies.
Data challenges across companies and departments; time-to-market, cost and feasibility of your data science projects all depend on your processes and tools.
Digazu’s platforms were made to create added value for companies from their data and make complex data engineering easier and Faster.