In an era where Business Analytics is about automating the data preparation and advanced analytics tasks, Augmented Analytics promises hopes for the future generation of Citizen Data Scientists. In Augmented Analytics, Machine Learning (ML) algorithms and Natural Language Processing (NLP) techniques together achieve automated Data Preparation and Business Intelligence.

This innovative technology offers sophisticated tools to the everyday business users, so they can quickly gather, collate, prepare, and analyze data to extract on-demand intelligence whenever they need it during their daily work. This novel approach to Business Analytics can easily transform any business operation, small, medium, or large without additional investment on skilled manpower or data center setups. The basic idea is to get Advanced Analytics to everyone’s desktop.

Augmented Analytics: The Future of Digital Science

According to the 2017 Gartner Critical Capabilities for BI and Analytics Platforms report,

“By 2021, the number of users of modern BI and analytics platforms that are differentiated by smart data discovery capabilities will grow at twice the rate of those that are not, and will deliver twice the business value.”

The article Augmenting Human Intelligence takes a first look at the Brainspace engine, which can analyze “data in context.” This unsupervised Machine Learning platform learns from data without any additional technological support, and offers excellent visualization capabilities for comparing millions of documents very fast.

So, why should you consider Augmented Analytics for your organization? Among the major reasons in its favor, the most popular one is the possibility of expanding the community of Citizen Data Scientists, who will be able to conduct advanced Data Analytics on their own. The built-in techniques and tools in Augmented Analytics can help the novice to utilize Smart Data Discovery (Augmented Reality) for improved understanding of data relationships and can guide the experts to leverage the smart tools for their focused business objectives.

The DATAVERSITY^® article What is Augmented Analytics and Why Does it Matter? discusses the benefits of Augmented Analytics. Moreover, the automated Data Preparation tools will undoubtedly enhance user adoption

In the case of Predictive Analytics, Augmented Analytics has the power to signal future course of actions from data-enabled, ML models and precedents.  As many businesses today rely on predictive capabilities of their Analytics systems to plan for the future, business owners and operators can certainly enhance the power of their existing analytics and BI platforms with Augmented Analytics.

Big Data can stretch the Predictive Analytics capabilities in the sensor-driven business operations, especially if the Analytics Platforms are enriched with Augmented Analytics or Augmented Reality.

Is Augmented Analytics the Next Trend in Digital Disruption?

In the Gartner post Augmented Analytics Is the Future of Data and Analytics, the author claims that the principle aim of Augmented Analytics is “automation” of competitive intelligence, which probably signals a completely new era in digital commerce. Yes, going by the current trends, Augmented Analytics has the power to revolutionize business operations, and wise business owners and operators are already exploring near-future adoption of this disruptive technology.

Information Week offers its own view of this impending digital disruption  in the article Augmented Analytics Marks the Next Wave of Analytics Disruption. According to this article, Self-Service BI may be considered the first wave of disruption in the Analytics market, while Augmented Analytics is set to be the second wave. The most notable point is that this new technology augments and enhances “human thinking,” thus, taking most of the intellectual pressure out of daily analytics tasks.

Human thinking is often clouded by personal biases, preconceived knowledge, and emotional judgments, which Augmented Analytics can accurately balance with completely data-centric, unbiased results.

Smart Data Discovery, or Augmented Reality, as described by Jen Underwood, a Business Analytics veteran, is an allied technology that can extend the built-in smarts of Augmented Analytics with ready-made visual of insights, hidden patterns, or correlations – putting the finishing touches with NLP-aided comments.

Why has Augmented Analytics Suddenly Caught Everyone’s Attention?

Games like Pokémon GO instantly took Augmented Reality (AR) to new heights of global popularity, and the mainstream fascination for this technology may be found in the Digitalist Magazine’s article Experience a Data Journey in Augmented Reality. The power to visually depict what is beyond the present gives AR a tremendous edge in digital consumerism.

As an example of this mind-blowing power, you can think of IKEA, which allows customers to digitally arrange and visualize the furniture in their rooms before making a purchase decision. Another good example is Boeing, which used AR in product assembly lines and in repair shops. A particular Deloitte Study includes the most popular Augmented Reality use cases in the enterprise; most of these industry applications have been applied to business collaboration, consumer demos and learning platforms, immersive learning, and product design and development.

A useful application of AR is in building “mockups,” which instantly communicate difficult or complex concepts via easy to understand visuals. A University of Minnesota paper titled Augmented Reality: Applications, Challenges and Future Trend  aptly outlines the journey of AR from theory to industry practice.

The Visible Benefits of Augmented Analytics in the Industry

Some key benefits of implementing Augmented Analytics or Augmented Reality in the enterprise Data Management platforms – summed up from above discussions:

1. Given the Data Preparation and Smart Data Discovery capabilities of AR, data experts can now focus on more strategic business goals and methods to achieve those goals.
2. Many Citizen Data Scientists will now be encouraged to take ownership of their decisions.
3. Advanced tools promise positive outcomes from routine Analytics exercises in enterprises.
4. The solutions in the Augmented Analytics world will not only be more accurate, but clearly measurable and repeatable in many areas of businesses.
5. The automated capabilities of these new Data Management technologies will naturally improve user adoption and data literacy.

As of now, even the most advanced BI systems are limited in their capabilities to leverage the power of Big Data and associated technologies like IoT. As more and more global businesses become sensor-driven and multi-channel data driven, it will become imperative that these businesses adopt Augmented technologies, which includes Augmented Reality, Virtual Reality, Smart Data Discovery and more.

Notable Augmented Analytics Use Cases

Some current stories of Augmented Analytics in action include:

• Medical training via digital technology is playing a key role. For example, a surgeon busy conducting a critical surgery in the operating room can actually share his experience with junior doctors or consult with other medical staff waiting outside the room through AR display units. Google Glass, which failed to do well in the market, is an example of this application.
• In the military, the “Heads-Up-Display” has been used for many years, where AR technology has been used. Another example is the HUD used by defense pilots. The HUD communicates critical flight information to the pilot without distracting him from his focus. Read about AR applications used in Defense in the blog post titled 5 most stunning real-world applications of Augmented Reality.
• In agriculture, farmers now have sensor-drive, water management systems that alert them about excessive use of water. AR technologies are assisting farmers to track and monitor water use, soil temperature, moisture content and status of their crops, and other farming tools.
• Smart Cities all over the globe are using Augmented Analytics to process high volumes of collected data. As more Smart Cities follow and adopt this transformational technology in their city administrations, the city management practices will truly enter the Digital Age. With these advanced technologies in place, city planners will be able to simulate a “Smart City,” predict future natural disasters, and better manage their existing resources.
• In industries, top management uses AR to only the relevant data through sophisticated dashboards to make quick decisions. As most of the data collected are sensor-driven, smart technologies like AR are highly sought after to collect, manage, sort, and display that data in a capsule format so that the management can capture the most important insights before making their business decisions. The article 10 Killer Applications of the IoT and Augmented Reality shows how top organizations like Volvo, NASA, and Caterpillar are using AR for increased business efficiency and productivity.
• Product designers and developers in typical R & D units can now create a dummy on AR platforms and visualize their prototypes in minute details before actually beginning the physical product-development process.
• In the product documentation world, the user or technical manuals are now digitally available with complete and comprehensive flowcharts, exploded diagrams, and explorative visuals to make product usage, maintenance, and purchase easy. Bosch routinely uses overlaid circuit diagrams or 3D- animation graphics on an AR platform for preventive maintenance.
• A LA-based firm called DAQRI has designed a smart helmet to shield repair workers from hanging or falling objects. The smart helmet is also capable of guiding the workers with technologies like “thermal vision” for detecting overheated objects. Caterpillar is routinely using AR for its predictive maintenance unit. The workers are shown performance visuals of maintenance components, so that they can decide when some component needs repair or a replacement.

Future Predictions for Augmented Analytics

Today, global businesses need to accept the digital disruptions and “everything AI’ wave to create unlimited business value through data and Analytics. This signals a change in mindsets, technology infrastructure, adoption rates, and monitoring techniques to measure outcomes of change. The following critical Analytics-related predictions have been captured from the report 100 Data and Analytics Predictions Through 2021:

• The Year 2018 will witness 80 percent of Data Scientists adopting Deep Learning for their work. This year, 50 percent of digital agents will use Real-Time Analytics.
• The Year 2019 will standardize the use of NLP on BI and Analytics platforms. In this scenario, at least half of all data queries will be conducted through NLP or voice or automated tools.
• By 2020, more than a third of all Data Science activities will be automated boosting mainstream adoption and efficiency in businesses.

Photo Credit: mamanamsai/Shutterstock.com