The missing piece in Data Revolution

Data Revolution - Natural Language BI

Data Revolution is yet to fulfill its potential. Yes, the world is drowning in data but extracting meaningful information out of it is still a challenge. There are three main reasons for this to happen: there isn’t an easy way to access and analyze data; the volume of data is increasing faster than we are able to analyze it and most of data is unstructured. However these obstacles to Data Revolution have a new solution available… at least for companies.


The Journey of a Natural Language Analytics Company


As a co-founder and CTO of Wizdee, I have to say that during all these years of hard work we had faced a lot of difficult challenges. We were able to win adversity, but most of the times not without a fight. The weapons we used were all gathered while back in academia, where we worked with a wide range of Artificial Intelligence approaches to solve real world problems. Having this experience was crucial to build a product that transforms Business Intelligence in something that anyone can do by themselves. (more…)

What to look for in a Natural Language BI tool?

Evaluate a Natural Language Business IntelligenceYou are looking for a Business Intelligence tool. It must be easy to use, let you explore data by yourself, give real-time insights and have flexibility in the type of data it can handle. You read something about Natural Language BI tools. Seems cool and you want to know what is the best vendor in the market. But how do you evaluate them? What should you be looking for?

We give you seven different criteria.


Is Natural Language the future of Business Intelligence?

Natural Language Business IntelligenceWhy are major BI vendors adopting Natural Language technology? Why are Natural Language BI startups gathering so much attention and investment? The answer is simple: Natural Language is the future of BI. It has gone beyond being a cool extra feature to be the perfect solution for three critical issues on the BI industry: unstructured data, user adoption and mobile.