The most pressing question for companies in the dawning data age is usually how they can evaluate their data to create competitive products and services. The sheer growth in data alone makes it difficult for them to derive the correct knowledge.
The past few months have shown that some companies succeed in evaluating data better than others – especially those already advanced in their digital transformation and can fall back on many digital processes. Evaluating data enables you to gain valuable insights and transfer these insights into strategic measures – and thus data transforms into a real competitive advantage, for example, by improving your digital offerings and simplifying processes for customers, partners, and employees.
Evaluating Data: How Edge Systems Can Help
To catch up with these digital pioneers, companies have to learn from them and, for example, build agile and decentralized infrastructures. Edge systems allow them to collect and process data where it occurs – close to networked devices and new sensors, the number of which is snowballing. In the cloud and data centres, they merge the data from the various sources for further analysis. Agile systems at the edge and in the data centre ensure that the exchange across data centres, cloud and border works smoothly and that all applications and employees can access the data relevant to them.
Evaluating data enables companies to identify trends in the market at an early stage and understand customer behaviour. They can improve physical and digital products using the insights they gain from data and automate many processes. That makes them more efficient and more competitive. The technologies and best practices already exist, but many companies have only started looking at them in the past few months.
New Technologies Guarantee Success
In addition to cloud and edge technologies, 5G and AI and machine learning are the keys to success in the data age. 5G connects the many new devices of the IoT with edge systems, the cloud and data centres. Artificial intelligence and machine learning are essential to analyze growing amounts of data and automate business processes. In addition, companies also need thriving thought-out data management to capture, store and evaluate data.
Only when the correct information is available can they achieve their goals and make intelligent business decisions. Data scientists, who currently spend 80 percent of their time cleaning up unstructured data, face particular challenges, even though they should advance new data evaluations and develop innovative solutions.
This shows that digital transformation and the use of data are not just about technologies but also about people and the understanding of business models and markets. Only when companies put their business strategies to the test and know how to use the findings of their data evaluations can they survive in dynamic markets and react to unforeseen situations. And they shouldn’t think of data as a luxury resource like gold because data is more like the waters of the digital age. Like water, they have to be cleaned and treated before the data can be evaluated and used. They are the lifeblood of digital transformation and allow countless new business ideas to flourish.
