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Data lakes on Hadoop have come on strong in recent years because they help many types of user organizations capture Big Data at scale and analyze or otherwise process it for business value. While Hadoop-based data lakes have proven valuable in mission-critical use cases, data lake early adopters have hit a ceiling due to weaknesses in key areas such as developer tools and flexible storage. Watch this TDWI webinar to learn about platform and tool options that can both fill the holes in Hadoop and extend …