Kategorie: Data governance

Posted in Data governance, Data Leadership, Data Products, DataOps, Deutsch, Technical debt

Data Mesh – Wie man verhindert, dass es sich in ein geldverschlingendes Chaos verwandelt – ein Podcast

Data Mesh ist eine analytische Datenarchitektur und ein Betriebsmodell, bei dem Daten wie ein Produkt behandelt werden und den Teams gehören, die sie produzieren, d. h. den Geschäftsbereichen. Wie können sich Unternehmen auf den Weg zu Data Mesh machen, ohne ihre Budgets zu sprengen und letztlich einen großen, unübersichtlichen und teuren Datensumpf zu schaffen? Höre dir den Podcast an. Lese den Blog.

Posted in Data governance, Data Leadership, Data Products, DataOps, Technical debt

Data Mesh – How to prevent it from turning into a money draining mess – A podcast

Data Mesh is an analytical data architecture and operating model where data is treated like a product and owned by teams who produce it, i.e the busness domains. How can organizations embark on their data mesh journeys without exploding their budgets and ultimately creating a big, mess, expensive data swamp? Listen to the podcast. Read the blog.

Posted in Data governance, Data quality, DataOps

Tackling machine learning enemy #1, poor data quality –  an interview with Sahar Changuel, PhD

Data quality is a business problem, as well as a tech problem. It is the biggest enemy of data-driven business and machine learning. Bad quality data can block or render a data project or machine learning use case unusable and thus a waste of money, human resources and time. Tackling data quality needs to be a targeted, systemic and ongoing, rather than a huge, one time cathartic event.

Posted in Data governance, Data Leadership, Data politics, Data privacy, Deutsch

Die Interoperabilität von Daten als Voraussetzung für Innovation im Gesundheitswesen – Ein Gespräch mit Jörg Godau

Startups im Gesundheitswesen wie doctorly sehen die Chance, mit SaaS-Plattformen, die auf offenen Standards im Gesundheitswesen basieren, das Rad neu zu erfinden. Das etablierte Gesundheitssystem basiert auf einer fragmentierten Landschaft von Softwareanbietern und Datenlösungen. Dateninteroperabilität bietet die Chance, Innovationen im Gesundheitswesen in Deutschland und darüber hinaus zu ermöglichen.

Posted in Data governance, Data Leadership, Data politics, Data privacy

Data interoperability is a precondition for healthcare innovation – An interview with Jörg (Jack) Godau

Healthtech startups such as doctorly and others see the opportunity to reinvent the wheel with SaaS platforms based on open standards in healthcare. The incumbent healthcare system is based on a fragmented landscape of software providers and data solutions. Data interoperability presents an opportunity to unblock innovation in healthcare in Germany and beyond.

Posted in Data governance, Data Leadership, Data quality, Data strategy, Technical debt

Tech debt sloth breeds a culture of sloppy operations – An interview with Daniele Marmiroli, PhD

Tech debt is often unavoidable in most early stage startups. Not fixing the tech debt as a company gets traction and scales is more of a problem than the original creation of the tech debt. Turning a blind eye to tech debt has implications beyond the stack and creates an unstructured and sloppy culture.

Posted in Data governance, Data Leadership, Data quality, Data strategy

Data governance starts at both the C-Suite and metadata level of your organization- An interview with Laurent Dresse

Facilitating the interface between IT and business is data governance, which is filled with opportunity. There is no specific career path into data governance, but the ability to understand metadata and contextualize organizational insights to executives holds much opportunity.

Posted in Data governance, Data Leadership, Data quality, Data strategy, Strategy

The co-dependence between data governance and growth – An interview with Irina Nikiforova

Irinia Nikiforova explains what data governance is and why it is essential for any business that not only wants to survive, but use insights from data or data-driven products to drive growth.