The world of data architecture began with applications. Next came data warehouses. Then text was organized into a data warehouse. Then one day the world discovered a whole new kind of data that was being generated by organizations. The world found that machines generated data that could be transformed into valuable insights. This was the origin of what is today called the data lakehouse. The evolution of data architecture continues today. Come listen to industry experts describe this transformation of ordinary data into a data architecture that is invaluable to business. Simply put, organizations that take data architecture seriously are going to be at the forefront of business tomorrow. This is an educational event. Several of the authors of the book Building the Data Lakehouse will be presenting at this symposium.

1. A presentation by
W H Inmon
LAKEHOUSE AND WAREHOUSE –
A COMPARISON

2. applications
ETL Data
warehouse
The data warehouse infrastructure

3. applications
Data
warehouse
Gender – m/f
Distance - inches
Gender – male/female
Distance - feet
Gender – 1/0
Distance - cms Gender – m/f
Distance - feet
A fundamental transformation of data occurs

4. Data
warehouse
Data warehouse –
subject oriented
integrated
non volatile
time variant
collection of data for management decisions
The single version of the truth

5. Data
warehouse
Historical data as well.

6. Data
warehouse
Structured, transaction based data

7. The data lakehouse

8. Machine generated data

9. A lot of data generated

10. High business value
Low business value
Some data has high business value,
much data has little business value

11. The data is put into a data lake

12. An analytical infrastructure is placed over the data
lake

13. The data lakehouse The data warehouse
How are the data lakehouse and the data warehouse
The same? How are they different?

14. The data lakehouse The data warehouse
The same -
Both exist to serve analytical processing
Both have vetted data – accurate, reliable
Both can look at data over a long period of time
Both have tame variant data
Both have data that once recorded cannot be changed

15. The data lakehouse The data warehouse
Different -
There is MUCH MORE data in the lakehouse
The data is fundamentally different –
warehouse data is transaction based data
lakehouse data is machine generated data
The data structures are very different
Relating the two types of data is difficult to do

16. The data lakehouse The data warehouse
Like cousins -
Related yet still different