Expanded analytics of Augmented analytics the Added analytics

In interpretation of Gartner the expanded analytics means use of such advanced technologies as the machine learning (ML) and the artificial intelligence (AI), for the purpose of data preparation, generation of insights and their treatment. In other words, it expands possibilities of people in studying and data analysis in analytical and BI platforms.

The expanded analytics is not specific technology or the product is rather combination of such technologies as the machine learning (ML) and analytics to automate all pipeline of data management — from their preparation before obtaining analytical results and also to help since creation of models and finishing them with implementation in operation.

The data science and MO are extraordinary difficult. For this reason of all a few years ago a set of the organizations in every way tried to employ highly qualified specialists in data processing who have work experience in three different spheres: statistics, coding and certain areas of business. Realizing the capacity of MO, they also aimed to start pilot projects as soon as possible in this area that then them it was possible to transfer to commercial operation. The expanded analytics, or expanded intelligence, apply MO and automation in order that the enterprises could deal with difficult nuances of analytics, MO and other types of AI^[1].

Advantage of expanded analytics is that it allows analysts of data, to data processing and other specialists data engineers to save time spent for accomplishment of the repeating manual procedures.

2020

The vice president for innovations and design of Qlik Elif Tutuk explained that the technology of analytics considerably promoted from the moment of emergence of the passive systems of first generation which issued to users static reports on data and quickly became outdated. "The most effective expanded analytics is a combination of the best aspects of machine intelligence and also creativity and experience of the person to help users to react, increase quicker productivity and also to get the ideas promoting adoption of the correct solutions" — she told. The expert gives actions of the head of a command of sales who can use search analytics (search-based analytics) for efficiency evaluation of work of certain sales representatives^[2] as an example^[3].

According to her to enter a question into the analytical platform, the head applies natural languag processing. The put mechanism of data processing and AI immediately start the analysis as structured, and unstructured data with the help of search terms to display the most relevant results, including visual representations. Then the user can study interpretations of earlier unavailable data which will act as help for acceptance of business solutions. The expanded analytics turns analytics into public discipline, and "the companies which make investments in these simple tools in use, will gain clear visual representation about hidden in these particles of valuable information. These ompaniya at all levels will advance literacy of data that will promote success of their business" — added Tutuk.

The director of the strategy of AI of Dataiku Alexis Fournier is sure that implementation of expanded analytics allows modern business to accelerate and automate modeling of AI considerably. At the same time it began to change a role of specialists in data. "Implementation of expanded analytics in business does not mean that the need for specialists in data disappeared. Here the speech that it democratizes data, making them available to a bigger circle of employees. Together with it there are new business needs and duties which include training of all employees in work with data, turning them into civil data specialists. Implement expanded analytics does not mean to create new instruments of data processing and to leave employees with them in private. That they could connect any work connected with data with business questions on which look for answers, proper training and understanding is necessary" — the expert considers.

According to Fournier, the enterprises lay great hopes on the fact that finally the expanded analytics will lead to full automation, but meanwhile they place emphasis on the accelerated creation of more exact MO-products. In turn, it opens a way for improvement of business processes, increase in accuracy of transactions and acceleration of new product development.

Fournier continues: "Involvement of expanded analytics is impossible without absolute data transparency. To eliminate possible barriers between personnel, tools of data and business objectives, it is necessary to carry out explanatory work on the subject of how the analytics and the AI related technologies will change labor power, business processes and the modes of work. Having necessary knowledge, employees will be able successfully to be guided in the technologies based on data, such as the automated MO for creation of models, carrying out comparisons and increase in business performance. Eventually, the transparency inherent to expanded analytics will integrate a data science with practicians of a business intelligence, providing the new and centralized access level to earlier separated sources of the business ideas".

The CEO and the founder of orgvue Rupert Morrison warns that the enterprises using analytics should be beyond historically saved up data, "which are a starting point for determination of the future in the past". He advises heads of the enterprises at decision making and development of plans to take into account much more nuances, than data for the last periods. The expert explains: "Opportunities which promise to business of MO and AI should not blind him. Of course, these new and intellectual technologies already occupied the niche, but business leaders should be convinced that the data which are available for them are efficient. Create the future on the basis of a retrospective — madness. These technologies cannot just foretell, what will be farther, therefore the organizations should undertake and simulate different scenarios on the future".

According to him, an exit for limits of the data which are saved up by the enterprises will help them to understand how work of the future will be constructed and what labor power will be required that it to execute. "Covid-19 resulted in uncertainty and violation of a usual order of things, and in these conditions the importance of expanded analytics increases. At the enterprises it will hardly turn out to make the efficient plan for the future, based on the analysis of historical data. Eventually in category of the lead those companies which apply the best solutions in the field of AI and MO will get and combine them with the continuous analysis, modeling, planning and implementation" — Morrison says.

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