Augmented Analytics: Analytics Acquires Machine Learning and Natural Language Processing

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Augmented Analytics: Analytics Acquires Machine Learning and Natural Language Processing

By: Wade Curtis

Small to medium businesses recognize the importance of data analytics but have some barriers preventing them from participating. It can be difficult to collect meaningful data and analyzing and interpreting the data requires a skill set that an SMB would more than likely need to hire a consultant. Many times, these consultants are not a financially viable option. Even larger businesses that can afford a consultant or dedicated data scientist may not have their time used efficiently as much of their time is spent cleaning up the data and other pre-analysis tasks.

Enter Augmented Analytics. In mid-2017, Gartner stated that Augmented Analytics would be an maturing technology in the next two to five years and by 2020 Augmented Analytics will be the main driver of new purchases of business intelligence and other data analysis platforms. Augmented Analytics is the use of machine learning and natural language processing in the data analysis and presentation.

Machine learning is an process where an algorithm can develop data models by exposing itself to new data. Capabilities of Cloud processing and large volumes of data are aiding machine learning in the development of new algorithms where proven algorithms were previously used.

Natural language processing allows an application to read and interpret human language. It allows an application to interpret a question, spoken or written, get the requested data and speak or write the answer to the user in their language.

These technologies in Augmented Analytics help remove some of the barriers that SMB may have when approaching analytics. The machine learning provides continued analysis of the data without the need to hire a consultant or dedicated data scientist. Natural language processing allows users to ask a question and have the application answer without the skills needed to interpret the data. Augmented Analytics also would have the ability to present insights that it found in the data.

Technical users, like data scientists, can also benefit from Augmented Analytics. Basic queries and reports are can be handled automatically by the application. This gives the data scientist the ability to put their time into more advance problems or development making better use of the company’s investment.

Now two years after Gartner’s prediction we are seeing signs of Augmented Analytics. In a recent article about 2019 trends, Gartner predicts that 40% of data science tasks will be automated by 2020. This can include regularly generated reports but also pattern and data set identification.

Companies are starting to include Augmented Analytics in their data analysis platforms they publish. Microsoft’s Power BI has been rated the top leader in Gartner’s 2019 Magic Quadrant for Analytics and BI platforms. One of the features in Power BI is the “Quick Insight” function. It can analyze a data set and apply an algorithm to automatically generate insights. Microsoft’s voice assistant, Cortana, can also be used to get information from reports and dashboards.

Tableau and Qlik are following behind Microsoft but are still leaders in the market. Their platforms are showing features of Augmented Analytics by incorporating machine learning and natural language processing.

Augmented Analytics is developing now and will begin to make its way to other platforms in the future. It’s ability to process large amounts of data and present it in a format the users of all different technical abilities can understand make it valuable tool for any business looking to analyze their data.


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Disruptive Trends in Digital Marketing: Virtual Reality

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Disruptive Trends in Digital Marketing: Virtual Reality

By: Lea Hoegsted

Organizations strive to engage their customers in unique ways through various marketing attempts.  Marketers are always looking for creative ways to reach out to the various population segments.  The future marketing scenario gets complicated due to the many channels that are available. Creative marketing will move away from agencies and move toward the platform. (Beer) The next upcoming platform to disrupt marketing is virtual/augmented reality.  The technology and the interest is definitely there.  By 2020, the economic impact of virtual and augmented reality is predicted to reach $29.5 billion. By the end of 2017, the number of shipped units of VR software and hardware from Sony, Oculus, HTC and others totaled $2.4 million.  VR headsets sold by 2020 is predicted to reach 82 million. (Becker)               

              Disruptive marketing technologies need to be approachable, not easily duplicated and have a common touchpoint. (Patel)  Consumers have come to expect more innovative engagement techniques and virtual/augmented reality platforms deliver.  Augmented reality marketing occurs when the customer can see the product. Content is placed in the user’s environment using a headset. It is a fully digital 3-D event where users walk through, experience and learn.  The virtual reality marketing experience is much more immersive.  Users can interact within the virtual space to not only obtain useful information but to actually use the product. (Drissel) This is where the transformational experience occurs.  The customer is no longer a passive receptacle of an organization’s branding.  It is a high end user experience that will change the perception of the product to an actual life event.  The virtual reality experience is rich in content and engagement capabilities.  Companies literally have 100% of the consumers attention offering high sensory impact. (Rogers)

                There are specific industries that should jump on board virtual reality train, specifically real estate, retail, tourism, sports and education. (Brown)  Realtors should be utilizing virtual reality technology.  Houses and business properties could be shown in real time.  Interior designing and home improvements can be done within the virtual space.  (Athwal) Customers will not have to travel from home to home in order to ‘see’ them.  Real estate agents will increase productivity and customers will not waste time.  Clothing makers could make it possible for users to try on clothing within the virtual space so that satisfaction is instantaneous. Another fascinating area to watch is tourism.  The applications for virtual reality technologies is endless. Destinations and experiences could be reviewed before buying tickets and making reservations.  Hotels could be scoped out for views and cleanliness.  For the handicapped and elderly, VT travel could actually replace actual travel. (Beck) 

                There are some problems inherent with VR marketing.  Customers will have to own a headset and be onboard with advertisement that could be construed as even more annoying and invasive than static ads.  Platforms will have to be compatible.  This may become an issue for some smaller businesses.  If an organization does not have the resources for virtual reality then they will not get the full exposure like bigger businesses will.  Small businesses may suffer because of it.  Competition will suffer because large organizations will be financially able to offer virtual reality experiences.  Companies that utilize virtual reality will have to have an integrated marketing and technological team.  This will be expensive.  This is another platform that executives will have to monitor for any wrong doing by employees.  There will be abuses that occur within the virtual spaces.  This is a liability for any company.  What if a crime is committed in the virtual space?  Is it really a crime if it happens within a virtual world?   Intellectual property rights are another area of concern.  Currently, there is a lot of grey area concerning laws and ownership within virtual space. (Howard)

                Within the next 5 years, consumers will see an explosion of interactive virtual reality marketing experiences.  The act of purchasing items from clothing to houses will be transformed into a personalized, customizable rich experience. Virtual reality technologies will definitely disrupt the current marketing environment.  It is exciting to see what the future brings within the virtual spaces yet to be created.


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Predictive Analytics

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Predictive Analytics

By: Emmanuel Mbanali

An important trend in analytics that seem to be a game changer because it offers a great potential in terms of return over investment , provides business intelligence and data inventory is the use predictive analytics. Organizations looking to expand and generate insights are looking at predictive analysis to gain business intelligence and competitive advantage. Predictive analytics enables the integration of technology into diverse domains by offering customized insights that lead businesses to generate new customer reports and insights (Some, 2018). With the advancement of big data, predictive analytics/intelligences has taken a much more sophisticated approach that can be used to indicate which projects to cross-sell and to which customer (Quick,2018).

Predictive analytics does not only gives organization the opportunity to predict the future through the generated and analyzed data from the past and the present (Gleason, 2018). It gives business the opportunity to plan for several scenarios that might arise in the future based on the information extracted from the analysis of data. Big data (including stored and real-time data) serve no purpose without analytics, but with predictive analytics, organization can use the data and customer insight to predict future events (Beal, 2018). Organizations can use predictive analytics to detect trends and forecast events that are likely to occur at a given point in time by using a wide range of methods which includes machine learning, mathematical process, big data and data mining (Edward, 2018).

It is important to state the difference between traditional analytics and predictive analytics and why predictive analytics is important for business intelligence. While traditional analytics is focused on insights generation that impact the present result from reports, predictive analytics provide the opportunity for users to take a good look at the near and long  future, and also pinpoint likely trends and behaviors (Edward, 2018). Predictive analytics is expected to help improve data quality that could be used to detect anomalies that could go unnoticed (Olavsrud, 2018). This is possible through automated analysis of data.

Predictive analytics uses several models to enable the generation of actionable insights and creating positive long term results by analyzing past and current data (Edward, 2018). A far as business organization is concerned, the existence of competitive pressure to acquire customers, understand the needs of this customers in order to optimize and develop long lasting relationship, it is important to adopt the use of predictive analytics not only to be proactive and anticipate needs, but also to mitigate risks and fraud.

Predictive analytics can be used by marketers to predict not only the future buying habits but make decisions based on the predictions that are likely to be accurate (Quick, 2018). There are several things a marketer can do the predictive analytics when applied to big data. Some of the possibility according to Faggella, 2018 include the predictive modeling for customers behavior, qualification and prioritization of leads.  Others, in no particular order include, prioritization of customers based on several factors, analyzing and forecasting seasonal customer behavior, development of more effective marketing and advertising strategies that will attract the audience to product and service, targeting the most profitable products to customers mostly likely to buy the products and use the best strategies to win repeat business (Quick, 2018).

Some of the vendors and service providers of predictive analytics include, Infogix, IBM Analytics, Optimove, AgileOne. Predictive analytics can be applied in different domain to provide the business intelligence and competitive advantage. By using different statistical methods, there is no doubt that predictive analytics will provide the insights that generate new customer responses or transaction and promote cross-sell opportunities. This means organization, through its marketing department that utilizes predictive analytics, can better identify potential customer, hence lead to conversions.