If credit card fraud detection is bothering you then you can
easily remedy the problem with the help of in-database analytics. Just so you
know this type of analytics is also commonly referred to as in-database
processing. Anyways, if you make use of the aforesaid analytics then you can
also have your way with investment bank risk management. If you are wondering
that why instead of using some of the traditional methods you should make use
of the aforesaid analytics then you must realize that the latter offers a
considerably improved performance. Furthermore, unlike the traditional methods,
it can help you in bringing about an improvement in the data warehousing
performance.
However, to be able to take full advantage of in-database
analytics you must be aware of what it is and what it can do for you.
To begin with, this type of analytics or processing will require you to
integrate analytics into warehousing functionality. Once you have done the
integration successfully, rest assured that you'd now be able to undertake
activities like fraud detection and risk management without any difficulty.
This is because the integration will help you make sure that data analysis
becomes a lot more accessible than before and that the aforesaid activities can
be undertaken with exemplary ease.
Meanwhile, it is worth mentioning that if you learn to make the most of the
in-database processing then you can also use it for the purpose of credit scoring
as well as transaction processing. In fact, in-database processing has also
been used by several companies for pricing and margin analysis. So, if the
aforesaid activities have been giving you a tough time then you now know how to
deal with the problem. Nevertheless, it is also important for you to understand
that the need for you to focus on in-database processing can grow if you are
dealing with big data analytics.
Anyways, if you are not sure how to go about enabling big data analytics then
you may want to begin by ensuring that you are being allowed to take advantage
of 100% embedded processing. For this, you have to find out whether or not you
require sampling while trying to collocate analytic processing. Furthermore, it
is imperative for you to make the necessary arrangements for automating the
parallelization process. Just so you know this requires to be done for all the
applications that are running in your database. Last but not least, if your
business analysts are not able to proceed with the analytics then you may have
to make the things easy for them.
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