Data

Latest

• What Are Network Graphs? - Introduction and Examples

  Network (knowledge) graphs represent a collection of interlinked entities organized into contexts via linking and semantic metadata. They build a framework for data integration and analysis. Having the ability to do this can provide more context around metrics recorded from a network system. By leveraging these graphs, you can enhance your understanding of the data.

  Data•Virtualitics - smarter decision through multi-dimension data visualizations and easy to use AI•2 Nov 2021•5 minutes

  

• Better customer service through digital information provision for service technicians

  The shortage of skilled workers, increasingly complex products and demanding customers make the work of many industrial companies more difficult. This article explains how digital solutions can make life much easier for commissioning engineers or service technicians on site with customers.

  Customer Service•Bastian Maiworm•29 Oct 2021•4 minutes

  

• Understanding Consumer Behavior Patterns Through 3D Data Visualization

  Any business wants to spend its marketing dollars wisely. Creating campaigns that are general in nature likely won’t deliver high revenue. Instead, you want to target as precisely as possible based on your customers’ buying activities. We can all agree that consumer behavior patterns are shifting and changing. Many things impact these patterns, both internally and externally. The last year-plus shifted the consumer base tremendously. For example, 75 percent of consumers tried new brands and different ways of shopping since the beginning of the pandemic. Consumer behavior is a “live” data set, and deriving insights from it needs to happen quickly, so you can pivot to align with current motivations.

  Data•Virtualitics - smarter decision through multi-dimension data visualizations and easy to use AI•24 Sept 2021•4 minutes

  

• Industrial AI Applications - Beyond the PoC

  The advancements of AI in various areas of our life make it one of the most appreciated technologies today. Impressive successes have been achieved, and the expectations are constantly rising. A tendency to transfer technology from the consumer space to industrial applications is also observed in this area. However, according to several analysts papers, industrial AI projects never get beyond a PoC in approximately 75% of the cases. Why is that the case? Enthusiastically building on AI’s success in the consumer space often leave some important properties of industrial applications overlooked. In this article we list a few industrial challenges that have to be addressed to make an AI project successful.

  AI & Machine Learning•Christopher Ganz•20 Sept 2021•7 minutes

  

• Data Science - We must hurry up!

  Data Science and the question of looking into the future. How can data be used to make predictions and what are the possible applications?

  Digital Marketing•DIGITAL BREAKFAST•3 Sept 2021•5 minutes

  

• How companies master their digital transformation

  For digital transformation to succeed and companies to achieve digital excellence, products, processes and technology must be addressed and improved simultaneously.

  Strategy / Vision•Jan Webering•30 Jun 2021•6 minutes

  

• How companies personalize (without being a tech company)

  What really matters to customers today is a personalized customer experience. Tech companies like Netflix are leading the way, but traditional companies shouldn't let that scare them away. Every company has the opportunity to personalize and start where it is conceptually, communicatively and technically. Because at the core of personalization are three information characteristics.

  E-Commerce•Britta Daffner•15 Feb 2021•4 minutes

  

• MarTech and data sovereignty: Know your customers, own your data - control your business.

  MarTech is changing the game and the rules in marketing and communications. We talk about the necessary analytical skills for dealing with data, the right tools for data sovereignty, and a new mindset in many places to learn from customer data as a customer-facing area and to incorporate it strategically.

  Digital Marketing•Sarah Seyr•30 Jan 2021•6 minutes

  

• Scaling Artificial Intelligence (AI) - 4 Reasons for People and Enablement

  Data has been called the most valuable resource of the new world. Ultimately, however, people are essential to derive value from data and apply it in innovative ways. Leaders recognize that advances in intelligent automation and artificial intelligence will have a significant impact on the workforce. And that they need to invest in talent that understands the intersection of data and algorithms and their impact on workflows. This article highlights strategies that will have the greatest impact on closing organizational skills gaps.

  Human Ressources•Britta Daffner•30 Jan 2021•5 minutes