The Rise of Data Lakehouses in an AI-Driven Era
A new report reveals that most organizations plan to adopt data lakehouses as their primary analytics architecture by 2027, emphasizing cost efficiency and AI readiness.
Cloud data platforms are public or private cloud software systems built and operated with the primary purpose of managing data on the cloud.
A new report reveals that most organizations plan to adopt data lakehouses as their primary analytics architecture by 2027, emphasizing cost efficiency and AI readiness.
As organizations look to reduce cloud waste, attaining a data-centric perspective has a multitude of benefits. Analysis can indicate data growth rates, hot versus cold data, compliant data, and more so that IT can make the best decisions balancing data requirements, business needs, and budget.
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By adopting a proactive Site Reliability Engineering (SRE) approach that incorporates comprehensive contingency plans, organizations can better navigate the complexities of modern technology.
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Most organizations today cannot lean on just one or two data management solutions. What’s needed is a multi-tech data platform that ensures performance, security, and more.
As data becomes more complex, the need for a multi-tech platform has never been more evident. By looking beyond single solutions like Apache Cassandra or Apache Kafka and embracing a more holistic, integrated approach, businesses can future-proof their data strategies and stay competitive in an ever-evolving landscape.