For a while now, the job of traditional BI has been to support better business decisions through dashboards, reports, data models, metrics and more to help an organisation understand what is really going on within its operations.
But things are now starting to change as AI is becoming far more accessible, impacting the way businesses engage with their data. So this begs the question,
Will AI analytics be replacing or be something totally different from traditional BI?
In fact, I’d argue it may not be an either/or question.
Traditional BI Offers a Bedrock
Traditional BI offers organisations a highly effective framework for defining, collating and displaying any business information to get things such as.
--> Power BI is one of a myriad of reporting tools to create Dashboards, display KPIs, report or create standardised Metrics.
These types of platforms offer the governance, framework and data modelling necessary so that everyone in the business are speaking the same language, and where everyone is working from consistent, reliable, governed data. Because all a dashboard might demonstrate, the underlying data model can be key for any given reports in place and to really assess its data trustworthiness.
What Does AI Offer To analytics?
AI analytics can augment these capabilities of traditional BI tools by introducing far more proactive activities into a business’s analytics workflow. Where business users might have to hunt around and conduct their own investigations into figures or data trends, a BI dashboard can now automatically help the user through such activities such as:-
- Pattern Detection
*Anomaly Detection
Predictive AnalyticsSupport
Automation of certain analytic activities
Natural language queries that require the tool to understand the intent.
Generating insights directly from extensive or complex datasets.
Traditional BI and AI can coexist as part of a broader BI analytics and data architecture, bringing together what we know with what we have predicted (And AI doesn’t change this, a set of inconsistent figures, poor quality data and unreliable inputs into your data models are still not good no matter the platform).
Rather than “AI analytics will take the job of traditional BI,” as is often predicted, it really could become part of a dual system; a strong and reliable BI platform providing governed reporting, consistent standards and a solid, dependable foundation upon which AI can begin to enhance that intelligence.
-->AI should start being integrated to help us investigate our findings and see patterns that might not be contained in our standard reports, and that, the power lies in an enhanced approach.
As businesses embark on AI-powered journeys to revolutionise their analytics approach, the role of technology like CompentraAI will further be brought to light. Find CompentraAI here;-https://compentraai.com/
Conclusion
Traditional BI and AI analytics do not have to compete. The role of traditional BI provides for reliability, organisation and consistency of your enterprise data intelligence and on this foundation AI can add automation, better pattern and anomylty detection, predictive intelligence and a far more intelligent way in which users can explore data. It will undoubtedly be a hybrid solution which most enterprises adopt to get the best results from their existing business data infrastructure.
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