You already have a Machine Learning model, in addition, you created the running scenario all by yourself in just a few minutes. So… let's take it to the next level. What will you do to categorize customers based on performance?

Imagine that you want to predict, for example, the creditworthiness of customers - ideally in real time. Moreover, you already have a predictive model written in Python, R, or Groovy. However, the last question remains - how to deploy a Machine Learning model?

Microsoft Azure customers worldwide now gain access to Automatic Business Modeler (ABM) to take advantage of the scalability, reliability, and agility of Azure to drive application development and shape business strategies.

In previous articles, we discussed how to maximize the benefits of using high-quality databases. However, if you don't have your own address or location data, but you still want to develop your business by conducting spatial analyses and making accurate business decisions based on geographical criteria - nothing lost!

Business Intelligence technology (and in particular Location Intelligence) is key in the context of making the right business decisions. If in your company you determine, for example, the target group of marketing activities, study purchasing trends, or want to increase the predictive power of scoring models - consider enriching the already existing database with additional data.

Previous publications have covered the topics of geocoding and ‘golden record’ in databases. It is then high time for Location Intelligence in the context of customer experience – considering as the recipient of a package, as the user of a website or application.

When discussing the process of data standardization and validation, it's hard not to mention the savings (time and money) that a properly cleaned database - such as CRM - brings.

Recently, alongside the well-known term Business Intelligence (BI), the term Location Intelligence has started to gain popularity. Analogous to BI, the term Location Intelligence (LI) refers to extracting knowledge from data, but that data should have a geographic/spatial dimension.

Over 3.000 people on the virtual hall. Over 1.000 registered participants, and 1st such event in the CEE region dedicated entirely to Machine Learning. Algolytics Technologies became the partner of Data Science Summit (ML edition) – the event that took place June 18th, 2021.

How to increase sales in your online store? A lot of articles have already been written about SEO strategy or UX best practices - so today we are not talking about that.

In every campaign you run, each customer you gain, any optimization you make - data is the new oil. Accordingly, to boost your business engine you have to ingeniously assure data integrity, data quality, data access, and data safety.

A real-time application based on predictive Data Mining algorithms, supporting the selection of offers, products and/or additional services, as well as the selection of channels of communication with customers.