The Data Economist - Blog (ENG) | Establishing sustainable "Data Inspired & Digital Culture"

Why Digital AI-Driven Ecosystems of modern companies are superior to traditional companies with one-dimensional products

The limits of one-dimensional products

Traditional companies, especially those from classic industries, often develop products that solve specific, isolated problems. These one-dimensional products usually offer solutions that are tailored to a specific requirement without providing a broader perspective or integration into other areas. These products follow a linear development and an isolated data flow that offers little opportunity for feedback and improvement.

As a result, such companies are often rigid and inflexible when it comes to adapting to constantly changing market conditions and customer needs.

Automation, AI and blind spots: Why data quality is more important than ever

In an age when customers expect more than just a product or service, data-driven customer service is at the heart of a successful business. Data governance plays a crucial role in this. It is the foundation on which 360-degree customer service is built, ensuring that the various departments of the company – sales, marketing, customer service – all access the same high-quality and consistent data.

How strategic synergies of data products contribute to value enhancement

In today's digital economy, data products play a crucial role in creating added value for companies and their partners. Complementary data products offer a strategic approach to improving the value creation process within a company and in its relationship with customers and suppliers. The advantages of these complementary data products are explained in more detail below.

How artificial intelligence drastically reduces the effort required for data preparation and creates new scope for strategic decisions

Artificial intelligence (AI) has made tremendous strides in recent years and is increasingly influencing all areas of technology and business. One of the most important areas of application in which AI will bring about major changes is data preparation – an often underestimated but critical process in the work of data engineers and data analysts.

Why the hub & spoke model is a good idea to transform an organization into a data-inspired culture.

In the digital transformation, data management is becoming increasingly important as a prerequisite for the successful use of data analytics and AI. But how does an organization become truly “data inspired”? A promising approach is the Hub & Spoke Model, which helps companies to act in a data-inspired way while gradually developing the maturity of the organization without overwhelming people and organization. In this article, I will discuss how the Hub & Spoke Model can help you become a Data Inspired Company and how it can support you on your way to becoming a cross-functional and agile data-inspired organization.

Data as a foundation: Why the success of AI relies on a solid data strategy

In recent years, artificial intelligence (AI), particularly generative AI (GenAI), has gained a lot of attention. The promises of autonomous vehicles, intelligent assistants, and machine learning have sparked a wave of enthusiasm and interest in the business world. However, while AI is often celebrated as the future of technology, there is one crucial aspect that is often overlooked: the data that powers these technologies.