The unbelievable Machine Company
Comprehensive Consulting Services for the Data World

Several organizations have long relied on data—both structured and unstructured—for making strategic business decisions. Big data analytics plays a major role in helping businesses unveil useful business information, making them smarter, productive, and better at making predictions. “The competitive market is experiencing a major challenge in combining the traditional systems with the new data science and advanced analytics world— combining enterprise IT and BI solution with Hadoop and the new technology paradigm,” begins Klaas Bollhoefer, Chief Data Scientist, The unbelievable Machine Company (*um). Well positioned to address the issues related to interconnection of business and IT, *um addresses these challenges with its full service tailor made solutions from “idea to cable.”

*um provides services for companies from a single source as they plan and implement their innovative ideas. The firm offers companies orientation and guides them through the whole process—from fundamental mindset/thinking to custom Data Enterprise solutions, which integrates this thinking and process into companies in a tailor-made fashion. “We have four data operations teams, two data engineering teams, two data science teams, and a very new data thinking team—a contemporary consulting unit offering expertise on data, algorithms, compute and mindset,” informs Bollhoefer. The new unit helps companies to understand the extent of the roles of their internal and external data. Data Thinking also enables its customers to gain visibility about their existing information.

“Organizations are required to build a new way of thinking,” says Bollhoefer. The technology industry has experienced a disruptive change and a sheer rise in the usage of several buzzwords like that of big data, Industry 4.0, Internet of Things, among others. Many companies are disoriented about the implementation of these trends in their enterprise and infrastructure. *um’s unique Data Leadership Process Model leads clients through the whole process of thinking, planning, implementing and operating successful data projects and guides companies’ individual digital development.

Our Data Thinking team is a contemporary consulting unit on data, algorithms, compute, and mindset kickstarting our new Data Leadership Process Model

It is kind of a mechanical model, where Data Thinking is the first step, and companies spread out sensors to collect and internalize factors related to developments, demands, trends from outside the organization. This is followed by individual development steps and cycles leading to the Data Solution. In these stages, data cases are developed from ideas and business cases via proofs of concepts, which validate that a case works, to real data products and integrated services. The next stages lead to the implementation and operation of the Data Solution inside the organization, whereby *um guides companies to implement important skills, capabilities, the right toolkit and/or routines. *um then accompanies companies to the Data Enterprise stage, which propels them to take the lead in their digital future, rather than just simply react to the market and the competition.

“In Data Science we mainly focus on machine learning, deep learning, and other advanced analytic topics,” says Bollhoefer. The firm also does operational intelligence like monitoring streaming solutions based on Splunk, elastic search among others. “We don't stick to any defined software tools, we always have to look for better solutions, the solution that fits the need of the project.”

The firm aims to stay a pioneer in the big data space. “We want to establish Data Thinking and the Data Leadership Process Model in all of its facets, stages and teams as a highest priority for the next few years.” One central idea is to empower every company out there to create an interconnected fabric of everything that includes data—not just infrastructure, engineering, analytics and algorithms, but also cultural, procedural and design layers that considerably uplift existing capabilities and create a data mindset.