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Company Overview

b.telligent is a technology-independent consultancy specializing in business intelligence, customer relationship management, data warehouse, big data, data science and cloud technologies.

With over 200 employees at six locations in Germany and Switzerland, b.telligent supports companies in all phases, starting with strategy, proceeding through analysis, design and implementation, right up to operations and solution advancement. The focus here is on optimizing digital and data-driven business processes as well as customer and supplier relations.

More than 300 customers here include leaders from the sectors comprising telecommunications, financial services, retail and industry. brandeins Wissen has once again distinguished b.telligent as one of the best consultants in Germany in 2019 in the category "Data Analytics & Big Data".

Marketing Automation

Customer Communication with Marketing Automation

Adress your customers at the right time with the content via the right channel with Marketing Automation - b.telligent will be happy to support you!

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Corporate Management through Reporting

The objective of an efficient Reporting is the comprehensive presentation of the relevant business data - get here more information from the specialists!

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Predictive Analytics

Prepare for the Future with Data Science

Get your large amounts of data under control and derive reliable forecasts for the future - with Data Science and b.telligent. More information here!

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b.telligent Blog: Data Warehouse & Business Intelligence

From DWH to high-performance cloud platform

More performant, more flexible, faster loading – just some of the powerful arguments for a data warehouse in the cloud. Pity about the migration!

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b.telligent Blog: Data Science

Child´s game "Guess Who": for Data Science enthusiasts

Read part 2 of the article to find out how Data Science can be used to develop the perfect winning strategy for the children's game "Guess Who?".

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b.telligent Blog: Data Science

Recommender systems 3: Personalized recommender systems

Part 3 shows the capabilities of personalized recommender systems, the advantages of machine learning methods, and outlines ways to measure the success.

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