Power up your BI with AI
If you’re a BI Analyst or a Citizen Data Scientist, you might have noticed a recent trend of augmenting BI with AI. It’s the next step in the evolution of a business intelligence solution.
Over the last decade, BI has become a staple in every organisation. It helped companies make sense of the massive amounts of data they collect by answering, “what has happened?”. But neat visualisations and dashboards looking into the past may not always be sufficient. So what’s next?
As BI maturity increases, the types of analytics evolve from descriptive to predictive. Predictive capabilities help us answer “what will happen next?”. It’s this capability that makes data science so valuable for business decisions.
BI solutions are not a one-time project; quite the opposite, they should continually evolve. A recent study led by Deloitte evaluated 152 cognitive projects and different strategies of implementing these initiatives into organisations. The results show that companies do better by taking an incremental rather than a transformative approach to developing and implementing AI, and by focusing on augmenting existing solutions rather than using revolutionary approach of replacing human capabilities with ambitious projects.
This means that implementing insight generated by ML into your existing analytics can be your first step towards AI. Sharing the results you generated with DSS can surface the value of predictive insights to more people.
If you’d like to learn more, check out Dataiku’s Power Visualizations with Dataiku + Tableau article and learn about the 3 main ways in which you can integrate Dataiku and Tableau:
Automating Tableau’s data pipeline with DSS and storing results in your preferred database
Exporting the dataset to .hyper file
Exporting the dataset to Tableau Server or Tableau Online with Tableau Hyper Export plugin.
