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How Do You Efficiently Assimilate Data?

In this second part of our series exploring data needs for DCM, we consider how data is most effectively delivered to support the needs of all market participants.

Delivering data in a visually attractive manner

Data mining and visualisation are two of the key challenges for DCM participants – in the days of instant access and turnaround, bankers don’t have the time to spend wading through vast quantities of information. Remember the days of headspin when bookrunners would be required to compile long tables with tens of columns at the end of on exhausting day on a roadshow? Today, information needs to be targeted, easier to digest and packaged in a visually self explanatory way to support quick decision making.

Combining data from various sources

Super useful insights are generated when data is combined from various sources. Today, data combining is largely happening manually by looking through pdf files line by line and trying to make some sense of it. In this digitally instant world we inhabit, how can this still be the routine? We need to systematise data from roadshows (non-deal or deal-related), orderbooks, market data etc historical or at present with a view to help DCM teams to have all the contextual information they need fast and accurately.

Converting unstructured to structured data

So far we have been talking about structured data – that is data already in a certain format and which can be mined, or combined to generate analytics etc. Much information though is still unstructured – IB chats, messages, word or pdf files with historical transactions or roadshows currently lie “hidden” in someone’s inbox or folder waiting to be read in order to become useful.

Tech has progressed vastly in the last few years, this unstructured information can be converted into data minable information, providing even more depth to bookrunners and issuers.

To learn more about DealPro’s functionality and how it delivers efficient access to relevant data, contact us at


The Finsmart Team