https://blog.solvatio.com/en/business-targets-challenges-in-first-machine-learning-projects
In the course of technical development, data is considered the key factor for the economic success of a company. It is seen as more valuable than gold – you might say data is the mineral oil of the 21st century. This is evident from the Top 5 most valuable companies, measured by their stock exchange value: It is the data that makes them so valuable. But collecting and storing data is no warranty for growth and profit. So, what makes data powerful?
All of us generate data all the time: We communicate via digital channels such as WhatsApp, Facebook and Twitter, we do online research, we snap pictures with our smartphones. In doing so, we leave a data trail. And this data is the raw material for perpetual new applications in the digital world.
Globally, people generate an estimated 2.5 trillion bytes of data per day (a trillion is a number with 18 zeros – a billion has 9 zeros), says the US computer firm Domo. But data and information is generated not only by us humans. Also interlinked devices, the “Internet of Things”, generates data by means of production equipment, cars, fridges, and even toys. By 2025, about 75 billion objects world-wide will be connected in the “Internet of Things”, transmitting data to the computer centers 24/7.
The business models of the digital world are based on data
not have any value. High-quality structuring, analyzing and interpreting is required to make it valuable. It is only through data analysis that meaningful business and market information can be created, resulting in new options for action: new disruptive business models emerge that will be revolutionizing the industries. Digital business models are mainly applied by web giants such as Google, Facebook, AirBnB, Netflix or Amazon.But also the telecommunications industry with its thousands of data-generating users may benefit. According to the Handelsblatt , the German cell phone market in 2018 generated more than 53% of its turnover from data services. This corresponds to an impressive 14.1 billion Euros – evidently, there is huge potential.
Generating value from data
Analysis and evaluation make data valuable and powerful. Machine learning algorithms can be used to handle the vast volumes of collected data. Learning from the existing data, these algorithms generate knowledge and solutions. But a company has to invest some preparatory work to really benefit from its data: Identify use cases, define company goals and also discuss the ethical aspects of AI. This work and effort is worthwhile because it turns randomly collected and stored data into knowledge which contributes to the company’s success.
In Summary:
- People generate data permanently. Untreated, this data is of little value.
- Machine learning can be used to make the data valuable and help the company to stay competitive. With machine learning, data can be transformed into knowledge and solutions – for enhanced competitiveness.
