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Big Data technologies and practices have been evolving and continue to be a significant part of the data landscape. Organizations across various industries leverage Big Data solutions to process and analyze large volumes of data to extract valuable insights.
It's important to note that the perception of technology trends can vary, and the assessment of whether a technology is "dying" often depends on specific contexts and perspectives. Big Data technologies, including distributed computing frameworks like Hadoop and Spark, NoSQL databases, and data lakes, have been instrumental in handling the challenges posed by massive datasets.
However, the field of data management and analytics is dynamic, and new technologies and trends emerge over time. Cloud computing, machine learning, and real-time analytics have become increasingly prominent, influencing how organizations approach data processing and analysis.
To get the most up-to-date information on the state of Big Data in 2017 or any subsequent years, you may want to refer to industry reports, articles, or analyses from that time period. Keep in mind that the landscape of technology is ever-changing, and what might be considered a trend at one point in time may evolve or be succeeded by new approaches and technologies.
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