IBM Vision 2016 Wrap Up

I recently had the opportunity to attend the global event IBM Vision 2016. It provided not only an opportunity to meet up with former colleagues in Orlando, but a chance to learn about the latest advances in IBM products and services and how they aid organizations in the areas of financial and operational management, sales management and governance, risk and compliance. At the conference, attendees were able to learn how to capitalize on the latest advances in analytics in order to turn their companies into businesses that leverage cognitive computing.

To that point, I led a session that provided an overview of the IBM Watson-Cognos-Monarch trifecta announced in March and how the partnership allows users to quickly prepare data from virtually any information source that was previously inaccessible. Whether it be PDF and text reports, Web pages, JSON or log files, users can now prepare data to be analyzed expeditiously vs. spending countless hours using spreadsheets and other time consuming means. Attendees also learned how to provide more transparency around data manipulation and promote reuse of data models.

Not only is it easy to prepare an optimized data file for direct import into IBM Watson Analytics and IBM Cognos Analytics, the data itself is an eye opener. So often data is manipulated or shaped in the hopes it will support an idea or a hypothesis relating to one’s business. We need to move away from Q&A-driven analysis according to keynote speaker and Vice President Watson Analytics and Business Intelligence at IBM, Marc Altshuller. Instead, Altshuller suggests a move toward unbiased inquiry which would decrease the time spent prepping data and more time analyzing the data itself. Using Monarch from Datawatch with IBM Cognos and Watson, users are able to do just that – bring in data that otherwise may have never been utilized, analyze it and look for patterns that could provide meaningful insight for their business. It allows the data itself to make discoveries.

Furthermore, with a self-prep tool such as Monarch, business users have the agility they need vs. having to depend on their IT counterparts. In turn, demands on IT workers are lessened, yet they gain a greater sense of the business user’s needs allowing them to be more strategic in their roles.

 

Want to know the top 10 ways data preparation helps IBM Watson Analytics users? Download our white paper.

You can also discover 7 reasons why Forsyth Alexander is adding Datawatch Monarch for IBM Analytics to Watson Analytics.