Introduction Data Warehouse With BigQuery

1. Data Warehouse
With BigQuery
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8. Without Data

10. What this is?

11. A database is an organized collection of structured information, or data, typically
stored electronically in a computer system.
https://www.oracle.com/database/what-is-database.html
Database

13. Database
1. Primary used for transaction
processing
2. Difficult to analyze data and create
report

14. Data Warehouse

15. is a system used for reporting and data analysis, and is considered a core
component of business intelligence.
https://en.wikipedia.org/wiki/Data_warehouse
Data Warehouse

16. https://www.minerra.net/business-analytics/what-data-warehouse-how-deliver-value

17. Data Warehouse
1. Collect data from wide variety of
source
2. Design for reporting and data
analysis
3. Data driven decision

20. BigQuery
BigQuery, Google's serverless, highly
scalable enterprise data warehouse, is
designed to make data analysts more
productive with unmatched price-
performance.

21. Why BigQuery
1. Google Cloud Platform’s Enterprise
data warehouse for analytics
2. Exabyte-scale storage and petabyte-
scale SQL queries
3. Encrypted, durable and high availability

22. Data warehouse Architecture

23. Compute & Storage

24. Query complete (17.2 sec elapsed,
15.1 GB processed)

25. Serverless

26. Architecture

27. Traditional Data Warehouse vs BigQuery

29. Real-time

30. Realtime BigQuery
https://medium.com/google-cloud/build-a-weather-station-using-google-cloud-iot-core-and-mongooseos-7a78b69822c5

31. Centralized Storage

32. Centralized Storage

33. Security and Trust

34. Data Sharing

35. Data Sharing

36. Predictive

37. 1
2
3
Predictive What’s happen yesterday (infinite
storage)
What’s happen now (real-time)
What’s happen tomorrow (machine
learning) BigQuery ML

38. BigQuery ML
In a nutshell, BigQuery ML (bigquery machine
learning) is a series of SQL extensions that
allow data scientists to build and deploy
machine learning models that use data stored
in the BigQuery platform.

39. Sample Model BigQuery
https://towardsdatascience.com/introduction-to-bigquery-ml-e746a3eaa28d

41. Google Data
Studio
1. Multiple Datasource
2. Data Studio is Customizable
3. Sharing & Collaboration
4. Real-time & Filtering
5. No Cost

43. Step by Step Learn
BigQuery + Data Studio
1. Learn SQL RDBMS
2. Join Free credit $300
Google Cloud Platform
3. Active Service BigQuery
4. Try Sample Public Dataset
5. Let’s Query on BigQuery
6. Enable Data Studio
7. Connect Data Studio With
BigQuery

45. 1. Machine Learning will be the next big thing.
2. New position called Chief Data Officer (CDO)
3. The demand for data scientists and analysts will increase
4. Investments in the technology will be sky high.
5. A higher number of developers will join the revolution.
https://www.agiliacenter.com/predictions-future-big-data-2/?lang=en
Future Predictions

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