It was in 2005 that Roger Mougalas coined the term Big Data. Ever since, it has captured the imagination of industries across the spectrum, across the globe. After more than decade, the world is now staring at the next frontier in data – Augmented Analytics.
It was back in 2017 Gartner predicted Augmented Analytics to be the future of data, and in 2019, it already is the number 1 trend in data analytics. As per a research published by Allied Market Research this year, the global market for Augmented Analytics will reach USD 29.86 billion by 2025.
What is Augmented Analytics?
Augmented Analytics (AA) presents a novel solution to businesses to make sense of swathes of chaotic data. AA combines Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) to automate the process of insight extraction from data. The AA-driven tools organize, manage, filter, and analyze datasets to produce actionable insights, speeding the process of turning data into digestible information. Owing to the reduced manual involvement and dependence, businesses can rapidly analyze data at scale, and easily obtain patterns and trends.
Augmented Analytics is set to create a new standard for business growth as organizations consume and generate massive streams of data from multiple sources but face challenges in making the data readily usable. Let’s see how.
From Big Data to Smart Data
Augmented Analytics has a vital role to play in transforming big data to smart data.
Data is no longer just nice-to-have. It is the guiding force that shapes strategies, actions, and ultimately, results. While becoming data-driven is a priority for most advanced organizations today, big data and legacy data analytics tools no longer cut it. Data is abundant, pervasive, and thanks to technologies like IoT, growing at a rapid pace.
As per a study by IDC, more than a quarter of data created will be real-time by 2025, with IoT data constituting over 95% of it. Clearly, an opportunity of gigantic proportions exists for organizations.
However, the challenge lies in effectively and efficiently extracting the right insights from this big data. Traditional tools for analysis involve a series of complex steps and a great amount of manual effort. Moreover, a shortage of skilled data scientists means organizations often miss out on a wealth of business-critical insights. Augmented Analytics enables data scientists to automate the process of organizing, cleaning, and analyzing data, and ultimately building models. Data insights can be obtained directly by asking queries, thus eliminating the need to engage specialists for preparing time-consuming custom reports.
In fact, data scientists can focus on high-value tasks that leverage their expertise and drive top-line growth, instead of wasting time digging through and cleaning data. What’s more, AA will lead to the emergence of ‘citizen data scientists’ – salespeople, marketers, etc. – who will be able to extract deep & meaningful insights, something that wasn’t possible using traditional data analytics tools.
Augmenting the Transformation of Data Analytics
A business’ engine needs data to fuel growth. By automating a crucial part of the insight generation process, AA fuels this engine at an accelerated rate. When repetitive data cleaning and organization tasks are automated, data scientists will have more time on their hands for strategic analysis and decision-making. Additionally, this shrinks the scope for human error.
Smart data, fueled by augmented analytics, brings together the whole picture. When an organization’s data is siloed i.e. distributed across several different platforms, it presents a hurdle in smart decision making. To solve problems and identify areas for improvement, the decision makers must be able to view how the engine works on a whole, not how different parts work separately. By integrating data points into a unified system, decision makers and CMOs can track the entire picture on one platform.
How Augmented Analytics brings it all Together
Business intelligence is nothing but extracting insights from data; AI and ML learn from large datasets. Augmented analytics adds AI and ML to the foundation of business intelligence. How does this happen?
Let’s understand the problem first. Data preparation is a tedious process involving the export of datasets, followed by combining and structuring them for analysis. When organizations have huge datasets with millions of records, they must incur a huge manpower cost. Further, initial analysis by data scientists is another incredibly manual process for identifying patterns and digging for insights.
Presently, a business intelligence platform intakes data from multiple sources before data scientists process it for analysis. An augmented analytics system automates data preparation and initial analysis steps using ML and AI, solving the problem of considerable manual labor used in a traditional system, and freeing up data scientists’ bandwidth for high-value work.
Democratizing Data Analytics for all Stakeholders
Augmented analytics is fast becoming a popular data analytics tool, one that doesn’t need the involvement of data scientists, effectively collapsing the wall between asking questions and getting the right answers. One of the biggest advantages of embracing augmented analytics is the democratization of data.
Data scientists and analysts enjoy freedom from repetitive and low-value tasks like running routine reports. Instead, they can focus on solving complex queries and data science projects, offering critical business insights to the relevant stakeholders. For small companies that don’t have the resources to build a team of expensive data scientists, augmented analytics will infuse accessibility and affordability into data-driven insights.
A bigger advantage lies for marketers like you. Augmented analytics is set to change how you make sense of customer data on a daily basis. Unlike earlier you don’t have to rely on an analytics team for in-depth research and reporting, a dependency that made your work time consuming and inefficient. With augmented analytics tools, you can regain control and track the entire customer journey, right from acquisition metrics to retention insights.
With augmented analytics, everyone in the organisation will hold the power to make informed and data-driven decisions, without having to depend on data scientists to furnish the required information. Naturally, this opens the doors for businesses to accelerate their growth at an exponential rate.
There is no doubt that augmented analytics is here to set a new standard for business growth. The quicker you leverage this technology, the faster you will reap its benefits and be able to exploit growth opportunities. Do share your thoughts in the comments section below!