By the end of 2024, 75% of enterprises will shift from piloting to operationalizing AI, driving a 5X increase in streaming data and analytics infrastructures – Gartner
People. Process. Technology.
Three core concepts that form the foundation of modern digital transformation including the discipline of data analytics. But just like democracy, there’s a fourth pillar slowly rising from the ashes of the modern stack of cluttered data analytics tool.
The data practitioners across the world has started to identify the critical role AI is set to play in modern data analytics.
A simple example to substantiate the above claim. During the pandemic, data analytics emerged as a powerful tool in the arsenal of medical professionals to battle the spread and contain it. A study by Gartner revealed that “AI techniques such as machine learning (ML), optimization and natural language processing (NLP) provided vital insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures.”
The pre-covid models of business intelligence dependent on historical data will fall short especially considering the agility and scale at which modern businesses function and a key reason for this shift in mentality can be attributed to the shortcomings of the dashboard.
Dashboards had its run. It was good while it lasted. But let’s shift our attention to the future. The same study from Gartner also points out that “Dynamic data stories with more automated and consumerized experiences will replace visual, point-and-click authoring and exploration. As a result, the amount of time users spend using predefined dashboards will decline. The shift to in-context data stories means that the most relevant insights will stream to each user based on their context, role or use. These dynamic insights leverage technologies such as augmented analytics, NLP, streaming anomaly detection and collaboration.”
Studies across the world has spoken about the introduction of Conversational AI as a proactive and viable alternative to traditional reactive data analytics platforms. But what fuels conversational AI? Apart from the tiny little pieces at work behind, one name stands out.
Natural Language Processing (NLP).
NLP is a field of computer science that deals with applying linguistic and statistical algorithms to text to extract meaning in a way that is very similar to how the human brain understands the language. It’s also called computational linguistics and employs machine learning coupled with linguistics to model after human speech. NLP is the driving force behind your conversational AI engines when it is able to understand the little pieces of question your sales leader pose to your data platforms like “What was the lowest revenue figure of Q1?” It intuitively picks out that figure means the sales figure and Q1 was for January, February, and March combined.
NLP ensures that the system understand the association between the words, the context in which it’s used, and converts them into boolean expressions the “computer” will understand. Technologies like Conversational AI aim to simplify information access and slowly but effectively replace graphical user interfaces in the longer run.
In layman terms, building an innate hands free operation right from the beginning and making business intelligence machines ‘almost human’.
Conversational AI is the way forward for making sure that users are easily able to access data insights. The user dependency on other teams is greatly reduced thereby making sure that insights are accessed within the required time frame. Delays in decision-making and their impending effects can be mitigated by investing in conversational AI driven data analytics platforms.
Even though there are a multitude of reasons to invest in, we will concentrate on the three major impact points of Conversational AI in data analytics.
By far the biggest impact of Conversational AI will be ensuring data access to the last man in the organization. The barrier for entry to Bi and big data will be nullified gradually, and a much needed information access will be granted to the frontline managers.
A study by HBR reveals that the new frontier has its fair share of challenges and it’s imperative that frontline managers are equipped with the right data analytics tools to make intelligent and impactful decisions.
Gone are the days when you have to sift through tonnes of spreadsheets or squint your eyes to the smallest possible micron level to get that one insight. The one insight that speaks about sales performance for the previous quarter. Humans always need momentary insights to the one data question they have and they absolutely do not have time to go in search of it. Conversational AI will ensure that the answer for their data questions land in front of them thereby increasing the findability of data – a concept modern data users desire.
A sales leader absolutely has no use reading through the attrition rate of the organization (unless it’s the sales team of course!). The same goes for the shareholder in your organization who is least bothered about the most effective supply channels for your product. They’re looking for insights that matter to them and makes sense to their goals.
However, the annual report that lands in their desk has all this information scattered across the 100+ pages. Data insights along with being momentary is also contextual in nature. A conversational AI platform built for data analytics will ensure that the insight they seek will be delivered to their channel of consumption.
Conversational AI powered business intelligence is increasingly gaining acceptance amongst the organization exactly for the above mentioned reasons.
The closing notes are pretty simple. The world is increasingly going conversational. Majority of the global workforce will be interacting with conversational platforms daily. The business intelligence function of an organization is also part of this transformation. Interested to learn why conversational insights is the future of business intelligence and experience it in action? Make sure to view our webinar Simplified Information Access using Conversational AI