Quicken the Pace of Data Discovery and Deployment with Back Office Outsourcing Services

by John Martine Author

According to a survey done on 70 IT leaders by IDG, it has been found that 92% of the respondents want to enhance the quality of analytics used in their companies. Through the same survey, it has been discovered that more than half of the respondents saw improvement in their decision-making capabilities after employing data mining solutions. Benefits of data mining have been found across most operations carried out by IT companies, however, 78% of the respondents still believe that they are yet to find the right data mining solution or service.

The Current State of Data Mining Operations

Come to think of it, the same belief is shared by many other companies plying their trade in different industries. Data mining as a business tool is still not utilized fully and the primary reason for that is the lack of resources available for non-core processes. Most companies are either too busy taking care of their core processes or do not have enough manpower for performing data mining tasks. Another major challenge faced by companies stem from the diversity of tools (Python, R, excel, Azure ML Studio etc.) used for performing mining operations. Hence, it becomes harder to train the back office staff in necessary skills. A great way to overcome this burden of data mining tasks is by employing back office outsourcing services.

Major Advantage of Data Mining Back Office Outsourcing Services

Quick discovery and deployment of data mining findings – The problem with in-house (limited workforce) data mining is that you are never quite able to implement your data mining findings at the right time. The act of discovering the right data, feeding it to the mining tools and then getting useful results, generally, takes a lot of time. So, by the time you get the answers to your business queries, the appropriate time to use them has already passed you by. Hence, more often than not, you are left with useless insights that cannot be implemented in the present. On the other hand, data mining services that you receive from an accomplished back office support service provider can be scaled and managed as per the requirement of your business. If you want insights quickly, then you can increase the size of your outsourced team. By using this approach, you will definitely get forecasts and insights for your business that can be used at the right time.

There are many other benefits of outsourcing data mining services, which are listed below:

1.      As there are many data mining software solutions available in the market and it is very hard to procure them all, back office support service outsourcing can serve as a better investment than buying all tools. There is also no need to train the workforce on these software solutions as you will get access to well-trained employees. 

2.      If you manage to outsource your data mining tasks to a back office outsourcing services provider in a country with an inferior currency value, then you will make a direct profit from an exchange rate that works in your favor.

3.      With data mining tasks outsourced, you will be able to focus more on your core processes.

Back Office Support Service and Data Mining Tasks

Data mining is a process that deals with finding useful patterns in data. The discovered patterns are used for answering complex business questions and forecasting the future of a business venture. Data mining can be of different types depending on the field in which they are employed:

1.      Web data mining

2.      Social media data mining

3.      Business data mining

4.      Resume information mining

The scope of data mining is not restricted to the aforementioned fields; however, the above mentioned fields are generally in focus. Depending on your business requirements, you can employ a back office support service that helps you accomplish your data mining tasks in any one or all of the aforementioned fields.

Sponsor Ads

• Ad Space Available - Rent it Now!

Created on Feb 5th 2019 05:37. Viewed 570 times.

Comments