To summarize the product capabilities, let me re-introduce the problem it solves. The long chain of tasks represents at least 7 type of actions and each of these silos can be optimized but it is limited to its own perimeter.
These silos are often deployed with specific dedicated products and it makes the insights quest a tough long journey. Promethium took a very different path and it was the vision of Kaycee Lai coming from Waterline Data, collaborating in tons of analytics projects with various partners. Integration was a nightmare and finally products glue is a must but not enough. The company approach shakes classic techniques with a first phase of questions powered by the integration of Natural Language Processing aka NLP, followed by a data discovery step from various data sources such Hadoop with Cloudera, Hortonworks and MapR flavors, databases with Oracle, Teradata, SQLServer and MySQL, S3-based data repository like Snowflake, AWS, Redshift, RDS and Athena and soon Salesforce.
Then queries and results phases with additions of AI intelligence. Based on this method, Promethium is able to shrink the time, manual efforts and TCO by a high factor inviting the user to test multiples scenarios in the time it took in the past.
All this beauty is realized by Data Navigation System aka DNS with 5 modules:
- Data Discovery with Smart Bot and Smart Explorer,
- Data Modeling with NLP Question Builder, Data Map Builder and Directions Builder,
- SQL Builder with SQL AI,
- Data Virtualization with Kaleidoscope to watch and check generated SQL commands and finally
- Data Governance with Guardian to check compliance.
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