How AI Is Making BI Smarter

Business Intelligence, a tactic for enterprise decision making tool, has been around for more than two decades now. It started as a tool for querying and reporting, then online analytical processing and later for data visualization. Gradually, it has moved from just visualization to data analysis, descriptive inferences to self-service analytics tool. Eventually, visual data discovery, and business analytics solutions continue to evolve.

Undoubtedly, future unfolds with multiple data sources viz. – ERPs, Open Sources, Social Media so on and so forth, with huge data repository and requirement to discover and analyze real time. Predominantly, it’s an imperative that business users need to directly use so that is always a push to make the solutions easier to practice.

Artificial Intelligence, here, plays an important role in identifying the right data from a massive pool of repository and discovering relevant insights faster to the business stakeholders. We will move to AI enabled smart analytics which will augment human decision making. Infact, smart capabilities like NLP and machine learning algorithms will further empower BI and analytics in future. It will cover areas like data preparation, discovery, analysis, predictions and prescriptions.

Also, Artificial Intelligence will restructure data into easy-to-understand insights at a scale, with features comprising natural language processing (NLP) search, recommended insights and automated narratives. Let’s have a quick look on how AI will further simplify and make the processes smarter:

• Data, both structured and unstructured, can be collected in an un-curated format and ML algorithms can be applied on real time to get meaningful output. AI can derive the information out of data at a scale much faster than ever before.
• AI augmented analytics using ML will help business owners to grow their data-driven decision-making. It will be accessible, understandable, and actionable. Though it will be not as simple but with AI & BI tools one can reach to a point & click, generate predictive models automatically to avail real time insights.
• NLP based search will become prominent. This will put business stakeholders in driving seat. They will get visualization and business insights without data analyst’s support. This will be further enhanced by voice-based NLP search in future.
• Machine learning will automate insight recommendation. Business users will be able to do close the loop interaction with transaction system and get faster turnaround to their business situations.

 All in all, we will see AI augmented smart analytics aiding and enhancing existing BI Analytics ecosystem. It will further simplify the user experience to the extent that whenever a user will ask a question that will be converted to text and interact with back-end systems using NLP search, which will then collect data in real time from multiple systems, apply right model using ML algorithms and update the user with the best possible answer using visualization, insights and automated recommendations.

And if accepted, these can be further integrated back to transaction systems that makes required impact to the business. Basically, decision making will become smarter, faster and impactful and this will be achieved with little to no human intervention.

Though there is no magic wand around and this realization will certainly take some time. Also, there might be possible hurdles in reaching there as there is a need to surpass governance, trust and data security issues. Having said that, surely there will be solutions to overcome them and AI lead BI Analytics will disrupt the decision making in future.