Taking full advantage of in-database analytics

Posted by Andy R.
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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.