Data Warehouse or Data Lake, Which Do I Choose?

Data Warehouse or Data Lake, Which Do I Choose?
Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pro’s and con’s for each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.
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OTHER ON-DEMAND WEBINARS

How to Strengthen Enterprise Data Governance with Data Quality

DATAVERSITY

If your organization is in a highly-regulated industry or relies on data for competitive advantage data governance is undoubtedly a top priority. Whether you’re focused on “defensive” data governance (supporting regulatory compliance and risk management) or “offensive” data governance (extracting the maximum value from your data assets, and minimizing the cost of bad data), data quality plays a critical role in ensuring success.
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DataEd Webinar: Essential Reference and Master Data Management

Data tends to pile up and can be rendered unusable or obsolete without careful maintenance processes. Reference and Master Data Management (MDM) has been a popular Data Management approach to effectively gain mastery over not just the data but the supporting architecture for processing it. This webinar presents MDM as a strategic approach to improving and formalizing practices around those data items that provide context for many organizational transactions: its master data. Too often, MDM has been implemented technology-first and achieved the same very poor track record (one-third succeeding on-time, within budget, and achieving planned functionality). MDM success depends on a coordinated approach typically involving Data Governance and Data Quality activities.
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Everything Data Scientists Should Know About Organizing Data Lakes

simplilearn.com

The recent GDPR regulations have changed the way companies handle the data they collect and store, making it imperative for data scientists to explore innovative ways to crunch and catalog data while ensuring that the company adheres to these new rulings that seek to establish complete data security.Join Big Data Expert Ronald Van Loon, and Simplilearns Chief Product Officer Anand Narayanan in a live video chat to understand.
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Data Science for Spreadsheet Users

DataCamp

In this webinar, DataCamp Account Executive Chris Cardillo will challenge anyone spending their days in and out of spreadsheets to pick up a coding language. He’ll cover the tangible benefits of incorporating coding into an everyday workflow, as well as examples of where coding enhances or replaces work done in spreadsheets. Finally, he’ll cover some R language equivalents for spreadsheet techniques, and where to get started when you’re ready to take the first step.
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