I would like to share the highlights of the topic for which I was selected as a Speaker at OAUG COLLABORATE 15 at Las Vegas. I strongly believe that shifting from ETL to ELT may not look as attractive but can make a great difference in Data Warehouse Environment.

1. REMINDER
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COLLABORATE mobile app
Hadoop - the rising star on the horizon
that can make ETL a history
Prepared by:
Vishal Sinha
Big Data Architect
With Hadoop, data can be aggregated,
sorted, transformed and analyzed and the
best part is that the data latency is reduced
to minutes instead of hours as in the case of
traditional ETL.
Session ID#:

2. Hadoop is not an Extract-Transform-
Load (ETL) tool. It is a platform that
supports running ETL processes in
parallel.

3. The traditional ETL architecture has served
enterprises well for past 20 years and many
deployments still use it.

4. ETL to die!!
■ According to Gartner BI Summit 75% of current warehouse
will not scale to meet the new velocity and complexity of data
demands.
■ ELT drives up to 80% of database capacity
■ Moving all the big data to an ETL server becomes infeasible
with big data volumes.
▪ Moving the data over network may lead to network congestion
which eventually hits the performance.
▪ Estimates from multiple sources indicate managing data with
traditional system is $20,000 to $100,000 per terabyte for high-
end data warehouses
Consuming lot of time

5. Can we think of a viable and practical
alternative to the expensive ETL process?

6. Can We Shift from ETL to ELT ?
Can we store first, analyze later ?

7. Hadoop can make ETL a history !!
■ Systems generate data, just as they always have.
▪ As near to real-time as possible, data is loaded into Hadoop -
yes, this is still "E" from traditional Extract, Transform, Load
(ETL).
■ That is where the similarity ends.
▪ With Hadoop, data can be aggregated, sorted, transformed
and analyzed.
— The best part is that the data latency is reduced to minutes instead
of hours as in the traditional ETL.
▪ There is no network copying time, no license requirements for
ETL software and no requirement of additional ETL hardware.

8. Offload ETL with Hadoop !!