IBM has been on a mission to drive innovation with data. In this respect, they recently unveiled its most powerful quantum processor yet, at 16 and 17 quantum bits of quantum volume, respectively. They want people to interact naturally with data and insights so as to drive innovation and transformation. This goes hand-in-hand with the self-service analytics move that has started already. Today we focus on the Cognos Analytics aspect of self-service analytics.
IBM® Cognos Analytics offers smarter, self-service capabilities so one can quickly and confidently identify and act on insight. It’s designed to empower business users, giving them the self-service tools they need to solve individual or workgroup challenges.
And if you’re worried about the quality of data in self-service analytics, IBM has a solution for you too.
One can employ the Datawatch Monarch for IBM Analytics and Datwatch Monarch Server for IBM Analytics blend and prep structured and unstructured data for analysis in Cognos Analytics. The same tools are employed to prep data for Watson Analytics too.
Datawatch Monarch is the world’s most widely deployed self-service data preparation tool. More than 80 functions enable you to manipulate and enrich data with simple point and click. And, absolutely no scripting is necessary. Furthermore, Datawatch Monarch Server adds repeatability and automation to data processing and preparation.
In other words, data preparation tasks are fully automated. Prepared data can be delivered to all users and systems.
We, at Cresco International, have been working with Cognos Analytics for many years now. In fact, we have been associated with Cognos much before the time it came “IBM Cognos”. So as the self-service analytics phenomenon gains more momentum in the workplace today, we can show you the ropes on how to get started with it on Cognos Analytics. Drop us an email at info@crescointl.com and we can get on a quick call to schedule a demo with you.
Have you seen our latest product – Auto-mate? Ask us for a quick demo!
IBM information extracted from this page