How to Overcome the Top Data Workflow Challenges

How to Overcome the Top Data Workflow Challenges
As the demand for data has grown, data workflows and processes have become increasingly complex. Consequently, the need for an efficient, modern data supply chain has never been more pressing. Yet, 451 Research’s latest survey shows that imbalances in the data supply chain could pose risks to data initiatives in today’s DataOps-driven world.
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Spotlight

OTHER ON-DEMAND WEBINARS

Why Data Vault 2.0 is the best data model for automation

Many data teams worry that automation won’t work on their specific data and technology stack. They’ve learned the hard way that automation doesn’t always stand up to the complexity of different source data models, taxonomies and tech stack components. Join this webinar to understand how Data Vault 2.0 is designed to focus on models and logic, not complex code, so that it’s rapidly becoming the DWH standard. We’ll explain how Data Vault has taken the best of the more traditional modeling approaches, such as Inmon or Kimball, to provide the level of abstraction, quality and agility that automation requires.
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Accelerating Data Insights with Cloud BI

Data volumes are growing faster every day. Fortunately, a move to the cloud can make real-time business intelligence accessible and affordable.
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Faster AI Deployment on Hadoop and Spark with RapidMiner and Microsoft Azure HDInsight

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Rapid Miner and Azure HDInsight work together to deliver a complete data science and machine learning platform for massive amounts of data using popular open source frameworks such as Hadoop, Hive, MapReduce, and Spark.Hear from RapidMiner Product Manager, Jesus Puente and Cloud Software Engineer Beth Zeranski, Cloud at Microsoft for this 60-minute webinar where they will discuss.
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6 Steps for a Successful Data Migration

Did you know that most migrations fail in some way, either missing project deadlines, overshooting budgets, or running into complications in the new environment? A lack of visibility into data can seriously jeopardize—and sometimes even ruin—a migration project.
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