A few years ago, the world of computers and technology entered a new cognitive era – an era that emphasizes artificial intelligence, or the ability of computers and programs to make decisions, learn, and thereby gain experience for future cases. At many panels, it was evident that participants were unsure whether artificial intelligence is possible with current resources, but also heard the question of why cognitive technology is so important for the present world. The answer lies in the fact that expectations from technology are growing every day, that expectations from technology have never been higher, and that the world is actually changing at the speed at which technology is changing. Looking from the perspective of the individual user, it can be seen that at work, but also at home, the user expects quick access to the information they need. The option where users have completely separate business and private lives is becoming increasingly rare, and it can be said that these two concepts are merging when looking at the life of an IT professional. An individual must know more, understand more, and be able to do more in order to advance as a worker, but also as a person. And for all of this to be possible, technology must provide us with such opportunities, rather than being a brake.
Only your Jarvis
Until now, end users have depended on their IT department or company to provide them with ready-made reports according to their wishes. Data preparation and research are unstructured and thankless processes. It is easy to see which factor affects which result and thus filter the data to obtain the most accurate solution. However, this does not necessarily mean that it is the best solution. The best solution is when absolutely all data is taken into account in the analysis and when the solution arises as a product of all data for one. And for that, the help of a program is needed because for most it is simply not possible to grasp all the connections within the vast amounts of data of a company. This is where the importance of programs like Watson Analytics comes in.
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The business advantage of Watson Analytics and similar tools is that they accelerate the time needed to start analysis and allow the user to use that time for real analysis instead of spending it on data preparation, finding connections, and so on.
In addition to offering a complete set of self-service analytics tools, Watson Analytics helps in preparing data for analysis, answers possible user questions before the user even thinks to ask them, and also answers questions that the user did not even know they could extract an answer to. The business advantage of such tools is primarily that Watson Analytics accelerates the time needed to start analysis and allows the user to use that time for real analysis instead of spending it on data preparation, finding connections, and so on. Now the user has more time to focus on understanding certain data and connections and understanding the entire business and the factors that affect the business.
The main part that gives the user an advantage over other tools is that Watson Analytics operates on the principle of the Watson supercomputer. The user poses queries in natural language, and Watson Analytics responds with visual representations and suggestions on what to do next. And what could be better than when, during a difficult task, your best friend can become a computer program like Iron Man’s Jarvis was in many cases.
It is important to know how to ask a question
This enables the much-needed analysis for the end user who has no experience in working with analyses but wants to conduct them themselves because they do not have the time or money for analysts. There is no need to program or code; the user just needs to know how to ask a question. An advantage for the business user is also the navigation in the interface, which helps new users (especially those who do not come from the field of analytics) to navigate and guides the entire process of creating analyses and visualizations. In fact, the only part where internal IT help is needed is connecting to data sources such as the Cognos server or various databases for security and data that the user usually does not have outside the system group. For tasks after the initial connection, the user should not seek any help because everything is very simple. They can download data, format column names, or depersonalize data according to privacy rules, immediately during the formation of a new data set or later if a specific change is needed on the data set they are working with. The simplicity of shaping and preparing data in Watson Analytics is a significant difference compared to other tools where data preparation for business analytics takes more time than any other process.
Ready for analysis
And after a few mentioned steps, everything is actually ready for analysis. The user opens the Discovery Tab on the portal where all the data sets they have available are visible and begins to analyze either by clicking on the data set or by posing a query in the question space. Questions do not have to be semantically completely accurate because the tool itself reviews the entered terms and searches for an answer that satisfies the specified terms. Regardless of whether one types, for example, ‘What is the amount of sales in year 2016 by region and product type’ or ‘sales amount 2016 region product type’, they usually receive the same templates for starting analyses, so the logic in the questions is not crucial for the tool’s natural language recognition. After we have received the suggested answers and initiated analyses, the Discovery space opens on the right side where Watson Analytics suggests new questions related to the initial question or those that offer deeper analysis, linking to one or more attributes according to which the initial analysis was conducted. This allows for quick switching from one analysis to another and discovering new information that the user had not even considered before.
And finally – visualization
Finally, we come to visualizations, increasingly popular in the world of analytics, especially for new business users who want to dive into analytical waters. Creating visualizations is actually similar to any presentation tool; templates and colors are very easily changed to find the best visualization for the user. Filtering analyses on the dashboard is divided into sections (the entire dashboard and/or a specific visualization), so there is no need to create a filter as in other analytical tools, but only to mark the attributes by which the dashboard should be filtered. This is a product that can fulfill the desires of business users who are interested in self-analysis because they do not want to wait for their analysts to do everything. However, Watson Analytics is neither intended as a replacement for real analytical tools nor should it be – it is exactly as it is presented – a self-service analytical tool for every business user. This should be well remembered before starting to design huge projects with it.
written by FRAN KARLO STRAJHER business solutions consultant, Megatrend business solutions
