What are advanced business analytics skills

Business Science: The Democratization of Data Science Skills

Just last week we gave you a little introduction to Tableau. Tableau is the leading analytics platform and now wants to further reduce the entry barrier for users with “Business Science”. Even people without data science skills can use programs like Tableau to the full extent without having to rely on data scientists. These specialized employees apply statistical methods and machine learning algorithms to solve real business problems. However, many companies only have small data science teams that deal with time-consuming, critical problems and do not correspond to the agility in everyday business.

Elevate the Human Judgment

A business problem requires domain knowledge in order to understand the dynamics in the respective area. However, data science teams do not have enough resources or time to understand these challenges in detail. With Tableau Business Science, the trade-off between “precision and control” versus “time to insights” and the implementation of measures is reduced. Business professionals can use predictions from ready-made machine learning algorithms for their scenarios without having to learn Python or statistical methods.

Business science is AI-powered analytics, through which users with specialist knowledge can quickly make decisions and take action. With artificial intelligence and predictive analytics solutions, people on the business side can find out which data they need for their use cases: For example, with variable selection, threshold settings and the selection of input data. Thanks to the simplified creation of machine learning models, “what-if” scenarios and other analytical methods, technical experts can identify the key drivers and carry out advanced analyzes. All of this can be done without programming knowledge.

Tableau Business Science vs. Data Science

What exactly is the difference? Both business professionals and data scientists have different goals and users who they want to address. Business science uses the same statistical and computational techniques as data science, but the output of data scientists is usually the answer to a “yes / no” question or whether the result exceeds a threshold. So data scientists want to develop accurate, perfect models. Fraud detection is a good example. This is about the precise analysis of large amounts of data in order to be able to identify suspicious transactions. The goal is therefore to develop the most accurate algorithm, because only the smallest inaccuracy could mean a loss of millions.

Business science, on the other hand, wants to iteratively improve KPIs and monitor processes. Here you need fast analyzes that enable smart decisions. For example, a retailer wants to find out which product to add to his store in order to increase profit in a certain region. The retailer has the specialist knowledge of his value chain and knows supplier relationships and trends very well. In contrast, a machine would not take such qualitative factors into account. Therefore, the combination of technical input and context knowledge for evaluating machine learning insights is extremely important.

Feature release: Business Science for Tableau CRM

There is also good news for all Tableau CRM users, because Business Science will be available with the Einstein Discovery Update 2021.1 update. Tableau and Salesforce have jointly developed the AI ​​algorithm in order to incorporate it into business workflows and to make transparency about key drivers and possible distortions visible. You can find more information about the new release here.

Einstein Discovery in Action. Source: tableau.com

Want to learn more about Tableau? Or would you like to find out about alternative technologies for data analytics? Then contact our motivated team today to talk about your starting options in a non-binding initial meeting!

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