Executive Summary and Main Points
The evolution of big data management systems is significantly influenced by the growth of real-time, streaming, and cloud-generated data. Adoption of the public cloud is propelling the transition from traditional data warehouses to innovative data lakehouses, coupled with advanced analytics and artificial intelligence (AI) applications. As IT democratization takes precedence, the focus is on self-service data access to meet business intelligence needs and innovation efforts.
Potential Impact in the Education Sector
In Further Education and Higher Education, cloud-based big data systems like data lakehouses can enable the analysis of educational trends and tailor student experiences, while strategic partnerships may enrich learning with real-world data scenarios. Micro-credentialing platforms could benefit from self-service analytics, making data-driven decisions more accessible to educational administrators and learners alike. The democratization of IT in education through user-friendly platforms will likely encourage wider adoption and integration across disciplines.
Potential Applicability in the Education Sector
The big data management systems’ evolution towards data lakehouses opens various avenues for AI and digital tool integration in global education systems. AI can be utilized to personalize learning experiences and predict student success, while self-service data access empowers educators and learners to conduct innovative research, align curriculum with market demands and improve operational efficiency. Data lakehouses in education could become central repositories for diverse educational data, supporting cross-institutional analysis and fostering collaborative learning environments.
Criticism and Potential Shortfalls
While big data and AI offer transformative potential, concerns about privacy, data security, and ethical use of student information might arise. Varying international data regulations and cultural norms could also impact the implementation of such technologies. Moreover, reliance on large cloud providers may lead to vendor lock-in, and the skills gap in IT could hinder the adoption of self-service models in less technologically developed institutions.
Actionable Recommendations
Education leadership should consider phased adoption of cloud-based data management solutions, emphasizing on professional development in data literacy and AI. Forming strategic partnerships with technology providers can facilitate access to advanced analytics while ensuring compliance with global data privacy standards. Additionally, leaders should also foster an institutional culture that values data-driven decision-making, with an aim to ethically leverage big data for the betterment of the educational landscape globally
Source article: https://www.cio.com/article/1296654/big-data-ecco-come-orientarsi-tra-data-warehouse-data-lake-e-data-lakehouse.html