Abstract
Efficient data archiving is crucial for organizations aiming to derive valuable insights from historical data for trend analysis and decision-making. This paper explores various approaches and strategies for optimizing data archiving processes to facilitate historical analysis. It delves into the challenges associated with managing large volumes of historical data and proposes solutions to address these challenges. Additionally, the paper highlights the importance of efficient data retrieval techniques and discusses emerging trends and technologies shaping the future of data archiving for historical analysis n 2023, Throughout my tenure up to 2023 as a Senior Big Data Engineer at Wells Fargo, I have been at the forefront of navigating and resolving complex data challenges. This paper reflects the culmination of insights and experiences gained during this period, focusing on optimizing data archiving processes for historical analysis. The financial sector, known for its stringent regulatory requirements and the critical importance of data integrity and security, offered a unique set of challenges, particularly in the realm of data archiving and historical data analysis.
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