pmOne Analytics GmbH

WE ARE BIG IN DATA

The team of pmOne Analytics GmbH is specialized in gaining precise forecasts from future business data for future events and for making these findings available to customers (Advanced Analytics). The basis is scientifically based, innovative and practice-tested methods and algorithms. In this way, companies can streamline and manage their business processes, such as sales planning, pricing, or production optimization, consolidate customer relationships and lay the foundations for new business models.

In addition to pure consulting business, pmOne Analytics GmbH will also market preconfigured algorithms for various applications such as customer analyzes, predictive maintenance and churn rate prevention.

Reference customers for Customer Analytics are Runtastic or TUIfly; And Novartis or ThyssenKrupp on the topics Machine and Manufacturing Analytics.


Customer Analytics and Product Analytics

Customer Analytics and Product Analytics

Customer Analytics is about analyzing and forecasting customer behavior, while Product Analytics deals with the accurate analysis of product data and derives predictions from it.

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Manufacturing Analytics and Machine Analytics

Manufacturing Analytics and Machine Analytics

Manufacturing Analytics is about analyzing data from production. For Machine Analytics, production data and, in particular, data from individual machines or production systems are analyzed.

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Wundermailing

A data-driven secret weapon for e-mailing campaigns

 

Tailor-made marketing campaigns without explicit knowledge in data analysis? "Wundermailing" makes it possible. In the cloud-based, digital service, which is already successfully used at TUIfly, for example, the concentrated data-science know-how of the pmOne Analytics experts lies. Their first product helps marketing departments achieve a successful, data-driven customer approach.

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Vienna, Austria – April 18, 2017 - The IoT Starter Package is the first step of four in pmOne Analytics’ approach to enterprise digitization – the overall process ultimately resulting in the customer’s custom Manufacturing Analytics Hub. The topics of IoT and enterprise digitization are both broad and novel concepts to many C-levels today. The lack of knowledge or fear of error, cost, and complexity sometimes lead to no enterprise digitization measures being taken at all, leaving companies at a critical risk of being completely surpassed by faster-adapting competitors. The IoT Starter Package is aimed at removing these barriers by breaking down the steps to digitization into smaller-scale, less intimidating procedures. No such Manufacturing Analytics solution is currently offered on the market and companies with no in-house IoT expert are looking for better ways to approach the digitization topic. This observation prompted Gernot Molin, Managing Director of pmOne Analytics GmbH, to develop such a solution.

For many of our customers, starting IoT projects is like dealing with the ‘chicken or the egg’ conundrum. There has been a lot of ‘well, we know we need to digitize, but where and how do we start?’ The answer is the IoT Starter Package.” – Gernot Molin, Managing Director of pmOne Analytics GmbH.

Before the Starter Package, customers considering IoT and manufacturing analytics projects were typically obligated to invest high-level modifications to their infrastructure from the get-go without the veritable understanding of the implications of the work involved. By its nature, the first of the four modules making up the path to the Manufacturing Analytics Hub allows customers to have a more comfortable grasp of what requires such mammoth up-front financial and infrastructure investments. This is an excellent opportunity both for pmOne Analytics to access customers who have been inadequately approached by other data science consultancies and for companies looking for a low-liability chance to start their digitization process.

The Manufacturing Analytics Hub makes use of a variety of Microsoft Azure services such as Azure Blob storage for storing data in full resolution (e.g., raw machine data); Azure Machine Learning as an environment for Python, Azure IoT Hub for device control; Power BI for dashboarding, Azure Data Factory for execution, and the Spark environment on Azure for large- scale computing power.

 

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Markus Nemeth
Managing Director
pmOne Analytics GmbH

Technologiepark 21
33100 Paderborn
Germany

T: +49 89 416 17 61-0
F: +49 89 416 17 61-99
markus.nemeth@pmone.com

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