Humanized big data, insight engines & the future trajectory of technology: Six trends that will make business more intelligent in 2017

The business world is in the midst of a digital transformation that is quickly separating the wheat from the chaff. The following article unveils the technology trends that will allow you to successfully and confidently navigate the digital era in the coming year, and considers how conversational systems, humanized big data, and augmented information will benefit everyday business.

1. Conversational systems: In human dialogue with artificial intelligence

Recommender systems on sales platforms or so-called chatbots that carry on a dialogue with the user in order to guide him through a business process are no longer a rarity. However, the recommendations are usually so vague and the intelligence of the chatbots so limited that the effectiveness of the process suffers – and with it the user motivation.

This is about to change. Companies are increasingly investing in technologies like natural language processing and natural language question answering that make their systems smarter and thus more efficient. For example, in conventional systems to date, the user types in a search query and receives a hit list that is no more than a bunch of documents from which he must extract an answer; a question-answering system responds with a concrete answer, so that the exchange is very much like an (ideal-typical) conversation between two people.

To achieve this goal, a great deal of artificial intelligence is required in the background. The system has to be able to extract from the context both the intention and the mood of the person asking the question. The progress in this area is so great that soon we are going to see dialogue systems that make it almost impossible for the user to figure out whether he is talking to a human being or a machine – this is the meaning of the catchphrase "turing test" (

2. Humanized big data: Real answers that stress quality over quantity

The trends Internet of Things (IoT) and Industry 4.0 bring intelligence to components and everyday appliances, resulting in a flood of data that is increasing exponentially. For instance, in today’s production environment, technically advanced machines are already continuously sending data about the current status, and sending alerts when maintenance is required.

Big data is a technology that collects and analyzes the kind of data created by those processes. Big data’s greatest strength, however - the quantitative foundation – is also its greatest weakness, as Jayson DeMers in Forbes magazine explains: ( It is difficult to derive concrete action guidelines or actionable meaning from an analysis of current solutions, if the point is to make business decisions based on the collected data.

Hence, the current trend is pointed squarely towards "humanized big data": Information should be processed in such a way that non-data scientists can also derive clear answers  ̶ "actionable insights" ̶  from big data analyses and use them as a basis for decision making.

This requires an approach that is more qualitative than quantitative, as well as a high degree of visualization of the data.

3. Augmented Information: A 360-degree view of subjects and customers

Augmented reality is already a major issue in the consumer sector. In principle, the aim of augmented reality is to enrich the physical world with digital information. The business sector is following the same principle by linking areas that were previously strictly separated from each other. In 2017, we’ll see an increased trend towards combining data from a variety of sources to provide employees with a 360-degree view of the customers and of subjects relevant for them. For this purpose, systems need to be able to make data available automatically across all applications, and all departmental and company boundaries. The coming year will bring forth appropriate systems for augmented information that, for the most part, will be based on enterprise search technology.

4. Proactive information management: The digital assistant is just around the corner

Important information inevitably gets lost in the daily flood of information. For this reason, the business world will increasingly see systems in 2017 that provide users with the right information at the right time  ̶  just like a personal assistant who keeps an eye on the appointment calendar and lets you know in good time when an important meeting is pending. This is exactly the principal on which the so-called proactive information management systems work: By permanently observing a person’s working methods and the type of information that he finds relevant, the system learns to differentiate between important and unimportant information and provide the former in a way that is proactive and timely. This system is also referred to as information alerting, information on demand, and push information.

5. Insight Engines: The competitive advantage of clever search

If you combine the first four trends, you end up with insight engines − a term coined by the market research company Gartner ( Insight engines are company-wide knowledge centers that link all information from various internal and external sources and communicate it in natural language, and thus proactively provide relevant, contextual information with results that provide deeper insights.

Since the knowledge distributed throughout the company is increasingly becoming a competitive factor (, in the coming year, more companies will be investing in enterprise search technology to implement insight engines. Once a knowledge center is established, the system will either provide the answer to business-relevant questions itself, or  lead you to the employee who has the appropriate know-how, whatever the case may be. The automatic side effect is that insight engines end up producing the basis for corporate-wide skill management and the promise that the company will finally "know what it knows."

6. Artificial intelligence: An essential prerequisite for digital transformation

The term "artificial intelligence" (AI) has been a part of technological development for quite some time. In contrast to earlier, where AI’s success was patchy at best, tools and technologies −such as enterprise search − are available today that are capable of letting systems constantly learn and independently improve – which is what is meant by machine learning and deep learning.

Among other things, artificial intelligence will be used in the coming year to take over the so-called "monkey jobs", the mental assembly line work. AI frees up ​​resources that are necessary to keep the company on course through the digital transformation. Hence, AI indirectly, and ideally directly, helps develop new business ideas and models.