Last December IBM announced general availability of IBM Cognos Analytics, a business intelligence tool that improves on fundamental analytics processes while also integrating several cognitive computing processes that can’t be found elsewhere. As analytics software continues to evolve, self-service capabilities are becoming more and more popular. Self-service capabilities allow employees to more efficiently gather, organize, and interpret data as well as generate dashboards and reports. This saves analysts time and frustration and also allows IT to focus on more pressing issues than managing data and access permissions. IBM clearly understands this need and reflects this understanding in many of its improvements to Cognos Analytics.
Some of the improved features leading to better self-service capabilities are a fully-functional search feature and user-interface improvements. The search feature can search, sort and relate data to the user’s needs. Many of the key details in the search feature come from the use of natural language processing (NLP). NLP has its roots in cognitive computing, and although Cognos Analytics isn’t founded on a cognitive computing platform, IBM’s extensive experience with cognitive computing (IBM Watson Analytics) has proven extraordinarily useful for improving the BI capabilities of Cognos Analytics. The improved visualization features (UI) also borrow aspects from cognitive computing. Additional cognitive computing techniques found in Cognos Analytics include an automated assessment of the user’s intent and recommendations for data preparation, both of which require the software to “think” differently than traditional BI analytics tools.
A more recent development in the Cognos Analytics world came in March when IBM partnered with Datawatch. Datawatch’s Monarch solution has helped enhance the cognitive computing capabilities of Watson and Cognos Analytics. The combination of these three tools has allowed for greater quantities and types of data to be processed, which in turn allows companies to make quicker, more informed business decisions. After Datawatch and IBM partnered together in March, the city of Boston reported that it was able to gather, analyze, and deliver results on open311, weather, and demographics data. The data were gathered from various formats (e.g. PDF and and Excel files) and quickly processed for the desired end results. Datawatch Monarch aided in the quickness of gathering and combining data, while IBM Cognos Analytics generated interactive and easy-to-understand visuals that displayed important trends from the data.
Another company using IBM Cognos Analytics is Columbus Foods, a San Francisco-based food company. Cognos analytics has allowed Columbus Foods to optimize its customer satisfaction and inventory capabilities while also minimizing waste. Columbus Foods deals with issues like perishable inventory, customer fill rate, and communication issues between supply chain, sales, and manufacturing. With the use of IBM Cognos Analytics, Columbus foods has improved communication between these sectors thanks to self-service capabilities, increased their revenues, cut waste be eight percent and spent less time collecting data than before. All of these benefits are evidence of Cognos Analytics’ ability to improve BI solutions with unique cognitive computing techniques.