ETL is the underlying driver of data processing today, as companies increasingly rely on data insights. Because the daily data requirements are complex and varied—in type and amount—companies need ETL systems that are efficient and powerful to avoid onslaughts of underutilized data and a loss of time and resources. The challenges of long-term maintenance, managing scalability, and implementing data governance persist, however. This paper discusses how the right ETL data pipeline tools and measures can help companies meet these challenges.
The 3 Challenges of ETL
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