From our BI partner
Forum last week in London focusing on Big Data Analytics, I think the messages coming
through from the discussions with partners and clients can be distilled into a
1. Find Value = Organisations are
more successful in finding value from potential Big Data Analytics projects
when they combine data from “Hadoopable” sources with their traditional Oracle
databases: for example merging social sentiment information with existing
customer loyalty and product revenue data. Hadoop projects in isolation are struggling to complete the business
2. Oracle+Hadoop = Open source Hadoop
and “R”-analytics are very complimentary to the Oracle stack, and indeed are
greatly strengthened by Oracle’s software distribution and connectivity options
– notably with OBI, Endeca, ODI, SQL, and the Oracle Big-data-Connectors for
3. Interconnect = Any Oracle partner
can get going with this by downloading the software onto a relatively modest
server, where they can interconnect the complete platform, and quickly get to
grips with it: see below.
can directly access data from Hadoop to analyse, visualise, and assess its’
value, and join it to Oracle DB data within OBI and Endeca and R.
and as needed, data in Hadoop can be economically selected, processed, and enriched
with familiar tools like ODI, and then moved with the Connectors into an Oracle
database at very high speed transfer rates, within your data governance model (e.g.
see the Oracle's Information Management Masterclass Tutorials).
= Of course, an Oracle Big Data Appliance plus the Exalytics and Exadata
engineered systems are the ultimate solution for this, but all of the software
platform from Oracle runs very well with Hadoop on smaller commodity servers. The choice of scale depends on your client’s
needs – this is not a constraint on getting value from the integrated software
stack. Projects can start relatively “small”; with one commentator suggesting
the median deployment is around 10 Tb, and only very few are in the Petabyte
5. Enterprise-grade = For the successful
Enterprise-grade projects, the Oracle tooling that connects with Hadoop and R
provide the security, speed and reliability needed to de-risk the project and
surface the value. These familiar tools
(OBI, ODI, SQL, Big-data-Connectors) also minimise the skills gap and cost
otherwise needed for extensive Java and MapReduce programming.
6. Hadoop is
not Big Data =
The key to value is using the right set of tools for the job: this may or may not include Hadoop.
a recent customer story where the full architecture is being put to broad use:
deploys new big data infrastructure on Oracle - Enables the Spanish Bank to
Develop Better Customer Services, Integrating Data Created Across All Its
Interconnect the complete platform
Partners can assemble
a complete platform from these VMs. These pull together a large set of tools, and so I recommend you put
this on a server with 32Gb RAM. You can also get some hints @ Oracle BI Partners Get to Grips with Big Data Analytics
Find out more @ Oracle's Information Management Masterclass Tutorials
and White-paper @ “Information Management and Big Data Reference Architecture”