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Data Collection & Analysis

We make your data work for you

Data acquisition optimization

We understand that not every data is (equally) relevant for every company. It is more important than ever to focus on individuality and relevance in close coordination with the company’s own business processes.

Metrics & performance indicators

We love numbers and figures - that is why we love metrics and indicators as well. There is nothing better for showing and understanding the dimension of accomplished success ... or failure.

Data thinking vs. big data

The more data the better? Most companies drown in the sheer amount of data they collected missing out potentially usefull data.

Master data modelling

Master data maintenance and revision can provide meaningful and impactful insights for improving. An outside view helps to put data into perspective.

4 steps to boost your data

With datapoints not being always equally relevant for each business, the focus has to be on individuality and relevance of data. When it comes to data collection and its analysis - especially in times of Big Data - this data acquisition has to take place in close coordination with the company’s own business processes. The best data acquisition models therefore consist of 4 steps:
Data Transparency

Getting an overview of which data should be collected at all

Data Collection

The process and method of how and when specific data is collected

Data Analytics

Actions and methods performed on data that help describe facts, detect patterns, develop explanations and test hypotheses. This includes data quality assurance, statistical data analysis, modeling, and interpretation of results

Databased Predictions

Enhance your business intelligence to better predict your future sales and supply needs. Identify your opportunities and your risks better and earlier with top down visualization and verify your findings by drilling into your data for details

How we can help boosting your data-related processes

abstract iamge as background tools for data collection and data analytics
Provide know-how about
proper tools
for collecting and
analysing data

How we can help boosting your data-related processes

abstract iamge as background for data driven processes
Automise and implement
data driven processes
and models
abstract iamge as background for data related process like monitoring and predictive maintenance
Establish better
transpar­ency
of data and information (monitoring, predictive maintenance)
abstract iamge as background for building key performance indicators
Creating metrics,
perfor­mance indicators,
visualization and
history & statistics
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Become the master of your data

Why you should take care of master data at regular intervals.

The advantages of master data management increases with the increasing number and variety of organizational departments, employee roles and IT applications within a company.

But because of its complexity, master data tends to be a very sensitive topic among most companies.

Its existence is considered good and necessary but its maintenance, or even worse, its remodelling causes cold sweat. Wrongly, in our opinion.

The process of revision can provide meaningful and important insights and in the end your master data is more accurate than ever. Not only the quality of master data will improve, but the data exchange between employees and departments simultaneously optimizes as well. In addition, master data management can facilitate data processing in various system architectures, platforms and applications.

How we can help you becoming the master of your data

Support in master data management
Maximization and long-term assurance of data quality
Ensure cross-system / cross-application data consistency
Support in database management
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The more data the better?

Most companies drown in the sheer amount of data they collected missing out potentially usefull data. Data Thinking puts business relevant use cases in front of the datamining process and defines afterwards in which way and quality they are collected.

This approach can help break down outdated data-silos, question their relevance and reprioritize them. In this way, not only can newly collected data be classified more qualitatively, but also existing data in the company. However, this process needs know-how, the right tools for execution and documentation and an excellent sense for data in general.

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Creating metrics & performance indicators

Today almost everything that is happening in the business world, no matter if offline or online, is measureable. But what is really relevant to your business in order to find out how it performs or how to improve?
With extensive experience in datamodeling metrics and the knowledge of the right tools we feel confident to be of value to your business. Because - as stated earlier - there is nothing better than verifiable and valid statistics for showing and understanding the dimension of accomplished success ... or failure.
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