Nowadays outsourcing big data analytics helps organizations to take advantage of the new generation of analytical solutions and ultimately make more predictable data-driven decisions. This comes as no surprise that some of the largest and most successful companies in the world such as Starbucks, T-Mobile, Capital One, and Walmart rely on big data analytics. According to IDC Worldwide Semiannual Big Data and Analytics Spending Guide, the sales of big data and business analytics applications, tools, and services will increase from around $122 billion in 2015 to more than $187 billion in 2019. Additionally, Gartner survey revealed that more than 75% of companies are investing or planning to invest in big data during the next two years.
Naturally, the demand for big data specialists is extremely high since it enables companies to make smarter business moves, increase the efficiency of operations, and gain higher profits. In recent years, numerous companies started extending their teams with professional big data developers and analysts to follow the global digital transformation boom. This, in turn, has drastically increased the interest for the outsourcing of this expertise to bridge over the labor market’s skill gap. We’ve prepared 5 important points to be considered before outsourcing big data analytics.
Source: Statista 2015
Prepare a strategy before Big Data outsourcing execution
Big data analytics is a business-driven process thus with the right infrastructure and execution it can have a powerful impact on customer engagement and business operations. That is why it is essential to develop your own strategy before outsourcing big data analytics to your offshore partner. This includes the design and planning around analytics initiatives and discussion of future steps to be taken before the beginning of the partnership. The company may also consider involving external consultants to develop an initial strategy and build some foundational analytics processes. In such case, you know how everything is integrated with other applications and which methods are being used. So having your own long-term analytic strategy is essential even though you are planning to delegate it to your outsourcing partner.
Consider Big Data analysts with domain expertise
Nowadays such industries as banking, insurance, logistics, digital media and ecommerce, retail, fintech, healthcare are leveraging big data analytics. However, big data insights will be useless if they cannot be applied to a business setting. Professional big data analysts have a strong understanding of the business and the domain they operate in. Outsourcing may help you find the specialists who have built a solid domain expertise while working with customers from numerous industries.
Without the deep knowledge of domain operations, big data analysts are not able to provide custom solutions tailored for highly specific business goals. Furthermore, domain expertise is even more critical in terms of validating whether the specific data can be transformed into something that will actually support the desired analyses. So domain knowledge can significantly magnify the impact of big data specialists’ insights and help identify relevant opportunities and threats based on their business expertise.
Invest in scalable Big Data analytics tools
At organizations where day-to-day decisions are driven by data, big data developers and analysts need the proper tools to extract maximum input from the gathered information. Scalable big data tools provide the most efficient framework for analyzing data, discovering patterns and proposing analytical models. In such case, big data specialists may identify and react to the elucidated patterns, and enhance the performance of business processes by integrating analytical models with the corresponding operational applications. However, many traditional companies underestimate the value of investing in the right data management tools such as SAS business analytics, SPSS, Cognos, MATLAB and others. Nevertheless, such one-time investment may not only help businesses cut costs but produce a dramatic ROI much earlier than anticipated.
Opt for Big Data specialists with solid tech skills
Outsourcing big data analytics can create substantial value for your business by providing your access to the greatest analysts. In order to achieve major big data analytics goals, the company should consider specialists with a solid analytical skill set. These professionals should have the fundamental mathematical knowledge for understanding various algorithms and models as well as a technical background. Such hard skills as numerical and statistical analysis are essential for any qualified big data analyst. With the help of this knowledge, they are able to work with neural networks and machine learning. Moreover, having solid experience in open source big data technologies such as Hadoop, Spark, Kafka, Kinesis, Hive, Pig is essential for providing valuable insights to help you translate your data into action.
Follow stringent security measures when outsourcing Big Data analytics
Data is a huge asset of a company and its protection and privacy is of utmost importance. Establishing solid legal agreements between your organization and your remote big data analytics team for securing your data and complying with all local privacy laws and regulations is essential for any organization. Privacy should be one of the vital considerations in terms of providing access to significant amounts of data including information about internal business operations and customers. So before entering an outsourcing agreement, it’s good to understand what processes your vendor is using to protect your sensitive data.
All in all, it’s not surprising that such market leaders as Google, eBay, LinkedIn, and Facebook are built around big data. More and more companies take advantage of big data analytics as it aids them in finding valuable insights to outperform their competitors and reduce costs. Outsourcing big data analytics helps organizations leverage their data to identify new opportunities and adapt to disruptive changes in their markets. In addition, it allows them to access a huge talent pool of skilled analysts. Ultimately, they are able to scale their business and their software products faster thus gaining the competitive edge on the highly unpredictable global market.
