It’s All about the Data, Dummy!

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Happy belated New Year!  For what it’s worth, no, I am not calling you a “dummy” or writing this just for Chris Hemedinger– just wanted to get your attention.  This blog is actually an introduction to a series that I am kicking off this year entitled:  "It's all about the data…"

Whether you be “grey and grizzled” or new to this SAS stuff, sometimes it can be helpful to see how others think about things.  In this series, I am going to cover a lot of ground, which is ultimately paramount to everything we do in SAS.  I love reading what Wendy McHenry and the other bloggers write about SAS Metadata and could never compete with their metadata mind-share!  Instead, I am going to focus on data, data, data! – none of this “data about data” stuff!

So this may be as boring as watching disks spin in a refrigerated data center, but I trust that you will keep me honest and alert with how you think about these things.

In this series, I will start with an overview of how SAS “eats” data and what SAS cares about (metaphorically speaking, of course).    Here, we will cover the fundamentals of how SAS works across all data engines. We will follow this up with subsequent articles covering topics like:

  • Understanding SAS Libraries (Physical versus metadata, native versus database, security 101, I/O and system characteristics)
  • How SAS clients see data (understanding permissions, library references, pre-assigned libraries, metadata library options, batch versus interactive and details on the how DI Studio, Enterprise Guide, Web Report Studio see data as well as  as best practice on managing library references)
  • Third-party database engines:
    • Oracle Libraries
    • SQL Server Libraries
    • ODBC
    • Testing and Debugging Connection Issues including benchmarking performance (and of course tuning)
    • Understanding database credentials (shared ids vs. dedicated)
    • Predicting Data Growth – Simple tools for estimating volumetrics and managing cleanup
    • File Systems Primer (types of storage, understanding raid, improving I/O, benchmarking your own performance)
    • Data Architecture for SAS Grid Manager

Hopefully you will find this interesting and challenge me with topics that will expand the list with the things that you care about most.

Until then, see you soon!

-greg

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About Author

Gregory Nelson

President and CEO, Thotwave Technologies, LLC.

Greg is a certified practitioner with over two decades of broad Performance Management and Analytics experience. This has been gained across several commercial, education and government, providing highly transferable skills. He has extensive experience and knowledge of research informatics and regulatory requirements and has been responsible for the delivery of numerous projects in clinical and business environments. He collaborates with stakeholders across organizations, gathering and analyzing their requirements and architecting solutions that are embody thinking data® – data which is more predictive, more accessible, more useable and more coherent. Greg has a passion for turning data into knowledge through Business Intelligence, Analytics, Data Warehousing, Master Data Management, Data Governance, Data Quality, and Research Informatics. He has developed strong partnerships with senior management within business and information technology organizations to support transparent project delivery and risk management; he manages stakeholders’ expectations of project delivery. Mr. Nelson holds a B.A. in Psychology and PhD level work in Social Psychology and Quantitative Methods and certifications in project management, Six Sigma, balanced scorecard and healthcare IT.

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2 Comments

  1. Rick Wicklin

    Welcome aboard, Greg! I look forward to reading your posts. My blog involves a lot of data, too, but from the statistical and visualization side of the analysis cycle.

  2. Chris Hemedinger
    Chris Hemedinger on

    Whew! Glad you weren't calling me out in particular.

    I'm looking forward to your posts. We can never have too much information about good data practices.

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