In this video, complete the architecture by adding the identified technologies to the cloud data archive architecture template.
- [Instructor] We have decided on the technologies to use, … so let's lay out the architecture … for our data archival use case. … First, we will use cloud storage … as the GCP file store for chat transcripts. … We will create one storage bucket, … but have folders under it by date. … We will build a script that will periodically … upload transcript files from … the Enterprise Data Store into cloud storage. … This will use the REST interface … provided by cloud storage to upload files. … Next, we will use BigQuery as the eCommerce cloud database. … In order to upload data into this database, … we will use a two phase approach. … First, we will create a temporary cloud storage bucket. … We will convert sales data in CSV files. … Files can then be created per table, per day. … The CSV files will be uploaded into the temporary … cloud storage bucket using REST API. … Then we will create BigQuery load jobs … that will periodically upload data … from the temporary bucket into BigQuery. … This approach saves on bandwidth and cost …
- Benefits and shortcomings of GCP
- Enterprise and multicloud integrations
- Comparing GCP technology options
- Outlining solutions for various problems
- Analyzing use cases and best fits
Skill Level Intermediate
1. Architecting in GCP
2. UC1: Cloud Data Archive
3. UC2: Log Analytics
4. UC3: Customer Analytics
5. UC4: Real-Time Mobile Couponing
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.