Rising to the data challenge in the private markets
Rising to the data challenge in the private markets
There is a great quantity of unstructured data trapped and unused on the private equity market. Much of the information is essentially unusable, forgotten in spreadsheets, databases, and reports. This data can provide valuable information from partnerships to the portfolio of companies, co-investors, grant recipients, accelerators' alumni, etc.
There is a great quantity of unstructured data trapped and unused on the private equity market. Much of the information is essentially unusable, forgotten in spreadsheets, databases, and reports. This data can provide valuable information from partnerships to the portfolio of companies, co-investors, grant recipients, accelerators' alumni, etc.
The proliferation of databases, platforms, and tools has resulted in an inability to update and share data effectively and the impossibility of determining which database represents an effective ‘source of truth’ for data sharing between sources. Data about people and organizations are not effectively synchronized. Further, even if the issue of a universal personal digital identity was solved, there is no corresponding solution for organizational identity. This results in a trail of increasingly outdated organizational data being stored in a multiplicity of locations.
The proliferation of databases, platforms, and tools has resulted in an inability to update and share data effectively and the impossibility of determining which database represents an effective ‘source of truth’ for data sharing between sources. Data about people and organizations are not effectively synchronized. Further, even if the issue of a universal personal digital identity was solved, there is no corresponding solution for organizational identity. This results in a trail of increasingly outdated organizational data being stored in a multiplicity of locations.
Problems caused to investors
Problems caused to investors
Subsequently, the considerable expense investors endure to aggregate, curate and store data results in it being either ‘siloed’, inaccurate, and / or inconsistent. And the next investor that requires this data must start from scratch, go through a similar process at a similar expense, and continue this unnecessary cycle in an endless loop.
Subsequently, the considerable expense investors endure to aggregate, curate and store data results in it being either ‘siloed’, inaccurate, and / or inconsistent. And the next investor that requires this data must start from scratch, go through a similar process at a similar expense, and continue this unnecessary cycle in an endless loop.
In that sense, TeQatlas can have breakthrough potential, where insights can be ‘born from data’.
In that sense, TeQatlas can have breakthrough potential, where insights can be ‘born from data’.
Converting this knowledge for the benefit of society is an unimaginable benefit, with the potential to disrupt entire markets. Investors alone cannot extract these insights, and there are few, if any, incentives for maintaining consistency across disparate databases.
Converting this knowledge for the benefit of society is an unimaginable benefit, with the potential to disrupt entire markets. Investors alone cannot extract these insights, and there are few, if any, incentives for maintaining consistency across disparate databases.
The power of AI
The power of AI
We leverage innovative state-of-the-art technology and a scientific approach to establish different optimized algorithms for data integration. Based on data science integration, we leverage the capability to analyze huge amounts of data with accuracy and reliability quickly.
We leverage innovative state-of-the-art technology and a scientific approach to establish different optimized algorithms for data integration. Based on data science integration, we leverage the capability to analyze huge amounts of data with accuracy and reliability quickly.
Additionally, recent advances in computational methods increase the quantity and complexity of generated data. This massive amount of (un)structured data needs to be stored and interpreted, identifying correlations and patterns. This approach can predict new trends and needs in diverse markets. Data analysis is being used to uncover complexities and design novel strategies to optimize the search for active investors and capital-raising investees. This is only possible due to the available breakthrough technologies (ML/AI).
Additionally, recent advances in computational methods increase the quantity and complexity of generated data. This massive amount of (un)structured data needs to be stored and interpreted, identifying correlations and patterns. This approach can predict new trends and needs in diverse markets. Data analysis is being used to uncover complexities and design novel strategies to optimize the search for active investors and capital-raising investees. This is only possible due to the available breakthrough technologies (ML/AI).