Augmented analytics may be the game-changer for your company.
Our best shot at decentralizing business analytics
At this point, every business recognizes the critical nature of data analysis for business growth and data-driven decision-making. By 2023, companies worldwide will have generated 163 zettabytes of data. So why, then, are so few businesses leveraging data to inform business decisions?
Data analytics is not for the faint of heart. Data on its own means very little; it only becomes information when combined with context. And can we then glean insights from the analysis of information?
The most challenging aspect of data analytics is frequently combining one dataset with other datasets for context to derive actionable insights.
Consider a company that discovers its sales have dropped by 10% in the previous quarter. The question is, is this due to the industry change? Or it is due to internal organizational factors, such as one of the advising channels not performing well. To determine this empirically, you may need to examine your web analytics, Google Analytics, and e-commerce data.
Data analytics isn’t exactly a plug-and-play task; precisely the issue Augmented analytics seeks to address.
What is Augmented Analytics
In 2017 Gartner released a report that defined Augmented analytics as
an approach that automates insights using machine learning and natural-language generation
Augmented analytics allows any business user looking at a specific business problem to ask/type simple questions in plain language and receive thoroughly analyzed results without manually analyzing and visualizing the response. Instead, augmented Analytics does the difficult part for you by automatically selecting the best visualization to answer the question.
A question might be, “How have our overall sales been over the last six years?”
By utilizing advanced machine learning algorithms, Natural Language Processing, and Artificial Intelligence, augmented analytics reduces a company’s reliance on data scientists and analysts.
Can’t Business Intelligence Tools do the same?
One could argue that business intelligence tools such as tableau and power BI
can do the same. The critical difference is that BI tools can visualize data, but you need to hire an expert familiar with the technology.
Even so, to derive insights from BI tools, some level of analysis must be performed.
For whom is augmented analytics intended?
Business users and executives benefit significantly from augmented analytics because they can quickly extract value from their data without requiring advanced technical skills or data management expertise.
Business users and executives can use augmented analytics to locate relevant data quickly, ask the right questions, and uncover insights in the context of their business.
With businesses increasingly reliant on data, users must query and comprehend data.
Even the best data scientists and analysts may not be the best business experts, which is why decentralizing business analytics to business users within the organization may be the catalyst for transforming the organization into a more data-driven one.
Augmented analytics is a relatively new concept whose advancements in cloud computing, machine learning, and natural language processing have accelerated its development significantly.
Further reading:
Augmented Analytics Starter Guided
Best practices of Augmented Analytics
