1. Enrico Serafini
(703)
4/16/2019

2. …just as true today as it ever was
Old lesson…
…just as true today as it ever was
4/16/2019

3. Our product
A web-based ecosystem where users can surface relevant data quickly, procure validated data and securely share their datasets
Problems we are trying to solve:
- Addressing the contradiction between data overload and not enough data
- Discovering and surfacing relevant data easily and quickly ( no need to be a data scientist!)
- Providing Data Governance (Validation, Security, Accountability)
Our Solution:
Applying analytics techniques and methods to the governance of data
Conditioning metadata before data consumption by Analytic Engines
Simplify and enrich data discovery in a secure and validated environment
Automating the population and harvesting of datasets
Enforcing Validation and Ownership of data
Save
Money
By intuitively surfacing relevant data at scale
Share Securely
Maintain ownership
Make
Money
Data as an asset
Trust Your Results
Validated data sources
Govern
Security and privacy enforcing ecosystem
4/16/2019

4. Data analysis problems
Valuable datasets =
Inability to surface relevance – The biggest problem with analyzing data is often accessing it (HBR, December 5, 2016)
Organizational Amnesia –What to do with all the knowledge that I already have? (MIT Sloan, March 3, 2017)
Organizational Ignorance –What’s your data worth? (MIT Sloan, Marc 3, 2017)
Data Democratization – Mo’ Data, Mo’ Problems – data democratization is not anarchy. (WebExpo 2017)
Unique data is an illusion – very vast minority of data is unique. Fact is lost in the jargon of Primary vs Secondary Data, Raw vs Processed data, or Derivative Data as applied to BigData….
It is estimated that There are tens of millions of open datasets – over 6x number of web sites when Google was first launched
The smallest fraction of datasets is published to be readily used by analytic engines (data.world estimates less than 10% of open data)
Dataset publishing is entirely manual using antiquated models
Average of 80% of total project time is spent on preparing data
Data sharing is notoriously difficult in the face of greater collaboration and exchange needs
What to do with all the knowledge that I already have? What’s your data worth? (MIT Sloan, Marc 3, 2017)
4/16/2019

5. A practical example…
4/16/2019

6. Planning for what to do requires complex analysis…
Real World Issue
Planning for what to do requires complex analysis…
Sifting, relating, many thousands of databases and official documents to determine the specifics needs of a mission
4/16/2019

7. Enable user to quickly find relevance
Our Solution
Enable user to quickly find relevance
Simplified, intuitive correlation, indexing and attribution of complex datasets via pExchange platform
integrated
4/16/2019