As discussed in my previous post, Data Governance is a mandatory framework to manage and maintain a data-driven organization. Data governance is the beating heart of all your data management processes
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Data governance is at the heart of data management. It concerns all agreements and rules of the game of data management with which you determine, among other things, how you want to use all data, what your objectives are with it, how you guarantee its quality, and how you arrange data security.
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Chaos Engineering intentionally introduces failures into a system to test its resilience and identify weaknesses. Chaos Engineering aims to build confidence in the system’s ability to withstand unexpected events and improve its reliability. You do this by running “chaos experiments” that simulate failures or disruptions in the system and observe how the system responds. By proactively testing for failures, organizations can identify and fix vulnerabilities before they cause significant issues in production.
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Agile ICT uses Agile development methodologies in Information and Communication Technology (ICT). Agile is a set development principle emphasizing flexibility, collaboration, and rapid iteration.
Agile ICT practices aim to deliver high-quality ICT-oriented business solutions and services quickly and efficiently. They involve close collaboration between cross-functional teams, frequent delivery of working software, and a focus on meeting customer needs and continuously improving the development process.
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As mentioned in my post about Data Warehouses, a Data Warehouse is a centralized archive for storing and managing large amounts of data from various sources. Organizations design Data Warehouses to support the efficient querying and analysis of data, typically for business intelligence and decision-making purposes. The power of a Data Warehouse is that you can easily merge data from databases from different applications into management information based on one source of truth: the Data Warehouse.
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In the 1980s, researchers introduced the first proposals of using quantum-mechanical phenomena to perform computational tasks, and since then, researchers have been working to develop practical quantum computers. In the early days, these efforts were largely theoretical. Still, in the past few decades, quantum computers have become more functional, and researchers have built prototype quantum computers that can perform specific tasks faster than classical computers.
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In a previous post , I discussed the importance of a Data Warehouse in a data-driven organization. An organization’s Data Warehouse is essential because it provides a central repository for all data. A Data Warehouse allows data to be stored and accessed consistently and organized, making it easier for the organization to analyze and gain insights from its data, which can help to make better decisions and improve operations.
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