April 1, 2019

Promethium unveils a radical new approach for data analytics

Promethium, an emerging player in data governance and analytics, met recently the IT Press Tour for a very interesting session.

Founded in 2018 by Kaycee Lai we already met at Primary Data and Waterline Data, the company has raised $2.5M from Zetta Venture Partners, Generation Ventures and others. Based on his own experience and time at these companies including Delphix, he realized that there is a missing piece in data governance. The other founders are Dr Shuo Yang, VP Engr, who worked at Google, EA or Huawei, and Azary Smotrich, principal architect, who also spent some time at Waterline Data.


And to close the loop, the name Promethium is related to the chemical element, its symbol is Pm, atomic number 61, very rare with 500-600g on earth. It explains the name of the domain name of the company pm61data.com.

The volume of data coming from various sources and the competition advantage they represent have impacted the industry in such a way that having fast, super fast, insights become a fundamental business component. But this is a mission like finding a needle in the haystack.


The 5 first steps described above are tough, take time and error prone. During all this time and effort, data are not validated, not guaranteed to be accurate and in case of divergence, it implies a direct loss of time with a potentiel business impact. At the time where fast insights are a key competitive advantage, the battle is lost and such approach can't satisfy current users.

With the BI tool, Data Warehouse and more recent data scientist wave, the industry realizes that 70% of the bI TCO is in labor according to a recent Tableau study. It means that among the 3 components - technology, process and people - the last 2 elements continue to represent a heavy portion.

The idea of Promethium is to address these 5 steps impacting the global experience and reduce them to 2 thus compacting the time to answers. The 1st step is about Questions to select the right and accurate data plus a second step to retrieve data from various sources. So we understand the 1st step is a core component of the solution illustrated by the slide below and reduces drastically the time consumed with other solutions. Promethium said this time drops from several months to a few minutes, so a spectacular return.

The other key attribute is the automation approach avoiding human long interactions that impact these steps.

The second value beyond time is the improved accuracy meaning that you can enrich the model to cover more data for just a few more minutes. It was impossible with classic approaches.


Promethium architecture is super flexible leveraging standards, ML, metadata indexing techniques, API integration and web services to automate the global process. Among the data sources, classic ones of course such databases like MySQL, Oracle, Teradata, Hadoop from Hortonworks or Cloudera, Aurora... files of course in multiple format. The company has identified 3 use cases to start: Pre-analytics, Dat Governance and Project Prioritization.

The solution is very promising. We hope to meet again Promethium during a future edition of the IT Press Tour to learn more from end-users deployments, ROI and business values.
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