What are self-service analytical models?

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In an increasingly digital and data-driven world, having self-service analytical models should be a priority for any company. What is this technology all about? Find out in this article.

Do it yourself: what are self-service analytical models?
When we talk about self-service analytical models, we are referring to self-service analytics whose most notable feature is its ability to provide all users with the possibility of obtaining information from their data , even if they have no experience.

In this way, today's companies, which are growing and accumulating data at an unprecedented rate, can rely on intelligent platforms that boost the use of information by all company users.

Teams are easily and quickly empowered to access, visualize and explore cameroon phone number lead data, design dashboards and run reports, allowing IT teams, analysts and data scientists to focus on more critical strategic projects.

Ultimately, self-service analytics models foster a data-driven culture by providing users with non-technical insights at the exact moment they need them, along with guidance in the form of recommendations.

Benefits of self-service analytics
Research shows that the more informed a company is, the greater its competitive advantage.

Self-service analytical models play a key role in properly managing data and, above all, democratising it in all areas of an organisation.

While the primary driver for enabling self-service analytics is often to gain insights quickly, the benefits go beyond improved efficiency: democratization and self-service improve the relationship between users and IT teams.

Let's see what are the biggest advantages that self-service analytical models offer to the companies that promote them:

You get a wide range of benefits that can help you easily build a data-driven culture .
There is less dependence on IT teams, since any user can obtain the information themselves.
Promotes greater IT development and productivity, as teams can spend valuable time working on relevant projects instead of answering data queries or report requests.
It allows any type of user to generate their own knowledge , which encourages greater technical innovation and productivity in each area.
Business users can spend more time exploring data , weighing insights, and taking decisive action.
Unlimited data discovery is achieved as each business user has unique needs and is able to slice and dice their data in any way they see fit.
There is increased data literacy which helps employees develop their analytical skills.
In conclusion, the fundamental goal of self-service analytical models is to promote autonomy so that any member of a company, with the appropriate permissions and without depending on third parties, can access answers to their questions with agile and reliable data.

These platforms tend to eliminate the complexity of data analysis and offer users an intuitive work environment, without the need for extensive technical knowledge. In a short time, users are able to obtain data visualizations in a simple and agile way to extract maximum value and relevance.

Self-service analytics is undoubtedly here to boost digital transformation and become a key asset for any type of business.