5 Top Tips for Outsourcing Big Data Analytics

Big Data analytics presents a lot of scope for enterprises to improve their business. But, to deal with the gigantic amount of data involved in Big Data analytics enterprises must possess appropriate resources, technology and manpower.

While some very large enterprises may possess all such resources and manpower, many other big and small enterprises lack them. Such enterprises have the option to partner with third parties to manage their Big Data analytics.

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Outsourcing Big Data analytics is not an easy matter. Enterprises have to make sure that the outsourced firm or company is capable of delivering the desired results. Mentioned below are a few tips to outsource Big Data analytics:

Begin with small steps

The market has no dearth of analytics tools or consultants that claim to have answers for all issues related to Big Data analytics. Enterprises must start with small steps before they commit to any outsourcing company for any long term haul. They must get a feel of the process prior to deciding whether they can go ahead with the prescribed strategy or not.

Enterprises must remain cautious of any outsourcing firm that nudges them to depend on a new system in a huge manner or to commit for a period of more than 6 to 8 months. Enterprises must look for a Big Data analytics outsourcing firm that offers to develop a Big Data analytics strategy that involves the present team members and adds value to the endeavours currently being carried out.

First decide then act

Effective Big Data analytics involves a lot of things, including analytics tools, deep understanding of the business processes and proper infrastructure. Enterprises need to decide on the things that they would have to outsource. While outsourcing any job that involves analytics tools and architecture is alright, enterprises must think before they decide to outsource the requirements in areas of business knowledge.

Enterprises need to be very clear regarding outsourcing Big Data analytics issues related to business knowledge. An alternate solution can be recruitment of human resources. Enterprises can recruit experts who will be able to understand the requirements and then deliver accordingly, experts who understand the business rules and logic, instead of simply outsourcing such things.

Outsource rapid data dives

Enterprises must be ready to outsource Big Data analytics requirements that involve rapid and deep data dives. Data outsourcing consultants can be of great help in areas that require enterprises to take immediate decisions.

In most cases, enterprises cannot afford the time and resource needed to deal with the requirements of deep data dive. It is not a viable option for any enterprise to halt all other processes and get involved in such data dive endeavours.

The feasible option is to outsource the matter to an analytics firm who have the necessary expertise to deal with such matters.

Avoid data aggregators

Enterprises must select Big Data analytics outsourcing firms that are more than mere data aggregators. The main objective of Big Data analytics is to be able to derive meaningful patterns and utilize the knowledge gained for improving business. The outsourcing company or firm must be able to help company executives to interpret the analytics results and then plan strategies to use the results for business profit.

Data aggregators will only help in increasing the data. But without the proper knowledge or means to interpret the data it will be of no use to the enterprises.

Protect crucial data

Enterprises must be ready to share their data with Big Data service providers. But the process must be carried out securely for sensitive data. This means, enterprises must have clear knowledge about which data they can provide access to and which data they must keep away from the outsourcing company.

For instance, an enterprise may decide to deny access to data that provides information about the company’s clients or customers. This way the enterprise can try to protect vital data and avoid the risks of the data reaching the hands of its competitors.

Apart from being cautious, enterprises must also ensure to outsource their Big Data analytics jobs to firms or consultancies that have a reputation for being reliable.

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