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==Review of Google Cloud and Data Engineering==
==Review of Google Cloud and Data Engineering==


Review in preparation for interview:
<s>Review in preparation for interview:
* Components of workflow in cloud, analogies
* Components of workflow in cloud, analogies
* Open source tools used at each "step"
* Open source tools used at each "step"
* Highlighting different workflows using repositories
* Highlighting different workflows using repositories
* Quick/easy example: why so many database solutions? How to do basics?
* Quick/easy example: why so many database solutions? How to do basics?
* Specific challenges, software, workflow for genomics research
* Specific challenges, software, workflow for genomics research</s>
 
==Review Notes Pages==
 
[[Google Cloud/Scientific Data Processing]] - doing the scientific data processing qwiklab
 
 


==Procedure==
==Procedure==
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* Apply style of later points to earlier points
* Apply style of later points to earlier points
* Clear out lorem ipsum (7-10)
* Clear out lorem ipsum (7-10)
===Links to Notes===


Notes review: GCDEC
Notes review: GCDEC
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* 4c - [[GCDEC/Engineering_Tensorflow/Notes]]
* 4c - [[GCDEC/Engineering_Tensorflow/Notes]]
* 5 - [[GCDEC/Streaming/Notes]]
* 5 - [[GCDEC/Streaming/Notes]]
===Links to Code Labs===


Google Codelabs:
Google Codelabs:
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* Scientific data processing - https://google.qwiklabs.com/quests/28?locale=en
* Scientific data processing - https://google.qwiklabs.com/quests/28?locale=en
* Data engineering - https://google.qwiklabs.com/quests/25?locale=en
* Data engineering - https://google.qwiklabs.com/quests/25?locale=en
==Review Notes Pages==
[[Google Cloud/Scientific Data Processing]] - doing the scientific data processing qwiklab




==Flags==


[[Category:Google Cloud]]
[[Category:Google Cloud]]
[[Category:Data Engineering]]
[[Category:Data Engineering]]

Revision as of 22:29, 8 January 2018

Review of Google Cloud and Data Engineering

Review in preparation for interview:

  • Components of workflow in cloud, analogies
  • Open source tools used at each "step"
  • Highlighting different workflows using repositories
  • Quick/easy example: why so many database solutions? How to do basics?
  • Specific challenges, software, workflow for genomics research

Review Notes Pages

Google Cloud/Scientific Data Processing - doing the scientific data processing qwiklab


Procedure

Software tools list, (abstract) example for each: Google Cloud

  • Storage/database/computation/GPUs vs CPUs/containerization

Software quality assurance:

  • Github page - 10 things
  • Apply style of later points to earlier points
  • Clear out lorem ipsum (7-10)

Links to Notes

Notes review: GCDEC

Links to Code Labs

Google Codelabs:

Google Qwiklabs:


Flags