Our Data Welding methodology is developed from experience. We employ the best data talent the market has to offer to carefully craft them into Data Welders. Our Data Welders are broadly educated, equipped to break through any barrier on the path to become data-driven. They are focussed on problem solving and tangible output. Welding the gaps between People, Technology and Strategy to create a seamless data experience.
Data Welders from Chapter Data are trained on five fundamental pillars of digital disruption:
1. Data Strategy
We take an agile approach to Data Strategy. Through an iterative and collaborative process of four sprints, we design a Data Strategy that makes sure Data is embedded in every decision, interaction and process.
Sprint 1: Exploration – Value Delivery
Sprint 2: Agile Development process – Business Collaboration
Sprint 3: Solution Development – Team Dynamics and Culture
Sprint 4: Hand-over – Retrospectives and Continuous Learning
Without the proper technology in place, you will never be able to leverage your Data at scale. Over time you will lose to others who did invest in professional structure. Data Welders from Chapter Data advise the right tool for the job within data management, machine learning or artificial intelligence. This enables you to drive innovation and transformation at scale.
3. Data Engineering and Analytics
Engineering is an important component of a Data Welder’s skills set. It involves the development of professional cloud and database infrastructure, as well as the creation of efficient data pipelines. When formulating strategies and plans, we consider scale, reliability and accessibility.
Our Data Welders gather, organize and summarize historical data to provide key insights into what has happened in the past. We create insightful, easy to understand Dashboards, enabling stakeholders to make the right decisions. Analytics is typically used to answer questions such as:
- What happened?
- Why did it happen?
4. Data Science and Machine learning
Data Welders create state-of-the-art predictive- and prescriptive models implementing Machine Learning into your business to stay competitive for years to come. With Data Science and Machine Learning, we typically answer questions such as:
- What is going to happen?
- How do we make it happen?
5. Culture and Leadership
To successfully ride the wave of digital disruption, fostering a culture of innovation and experimentation is key. This starts with the tone at the top. You need Strong leadership with a clear vision on how technology can be used to transform the business and stay ahead of the curve. Being part of the Top of Minds group means we can fall back on numerous C-suite and senior management engagements. Therefore, we’ve seen what defines successful digital leadership.
It is equally important to improve your data capability by developing data literacy among tech- and non-tech people. You need to gather the right skills in your data teams to continuously fuel your data-driven ambitions. Moreover, establishing trust in the output and products your tech team produces is crucial. When business user can rely on and understand these outputs, it cultivates a data-driven mindset that permeates far deeper within the organization, ultimately driving the data culture forward.
“Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years” – Andrew NG, founder DeepLearning.AI
Feel free to contact Sander Klinkenberg to discuss your data challenges.