Today we understand our customers better than ever. The data we gather and analyze determines the success of our business. Business Intelligence, big data, data science, and data analytics provide companies with illuminating insights. Those who adopt these technologies early, gain huge competitive advantages.

Therefore, the demand for professional data analysts is far exceeding the supply. To deal with the scarcity of specialists and soaring prices for their services, many business leaders consider data analysis outsourcing . But how to make it right? Our article will highlight the most important aspects of data analysis outsourcing and tips on choosing the best data analysts.

Data analysis outsourcing vs. in-house

According to job-market trackers, the online ads for data analysis mavens have shot up 246% since April 2009. What’s more, IBM states that the annual demand for data scientists, data developers, and big data engineers is expected to reach nearly 700,000 openings by 2020.

However, keeping an in-house data analytics team can be quite difficult since the market for analytics specialists is tight and many companies still lack required knowledge or skills. In fact, a huge number of data analysis-related positions (approximately 190,000) in 2018 will be unfilled due to the lack of applicants with expertise, according to McKinsey report.

Analysts expect he global data analytics outsourcing market to grow at a CAGR of 30.25% during the period of 2017-2021.

The shortage of in-house experts that are capable of deriving actionable insights from the company’s data is a major challenge. Outsourcing offers flexibility and access to world-class data science, big data and analytics experts. This allows companies to implement innovative solutions with the right infrastructure, skill set, and mindset to get everything done on time. Moreover, it allows management and an executive team to focus on their core business operations. Whereas an in-house team of data analysis experts is hard to find and hire and requires substantial financial expenditure.

That’s why business executives rethink their sourcing strategies to meet the demand for a faster innovation based on data analysis. And that’s where data analysis outsourcing comes into play.

data analysis outsourcing market

Source: Technavio

Leading data analysis outsourcing destinations

The US, the UK, and Western Europe are some of the key players on the data analytics market. Nevertheless, even these technologically mature markets are still struggling to develop enough talent for building fully staffed on-site data analytics teams. finding qualified data analysts becomes a matter of urgency and thus leads them to outsourcing.

Leading international data analysis outsourcing markets such as India (with more than 50% of the data analytics projects being outsourced) and Eastern Europe become an instant choice for cooperation. India remains the undisputed leader due to its vast availability of resources. However, despite the extensive workforce within the country, it still struggles to compete with the majority of the European outsourcing markets in terms of quality consulting and digital skills. Whereas Eastern Europe offers quality analytics services with destinations such as Ukraine and Poland taking the lead. So what do they have to offer?


According to Linkedin, over 22,724 data analysis experts are already engaged in the IT sector in Ukraine including BI, data science and big data experts and this number grows day by day. Local IT companies offer a great variety of data-driven services including real-time data science, big data analytics, machine learning, custom ERP development, etc. For instance, such IT players as N-iX, SoftServe, Ciklum, EPAM Systems and Infopulse can boast availability of expertise in BI, data science, and related fields.

Furthermore, numerous tech events for BI, Big Data and Data Science professionals take place in Ukraine including such massive conferences as AI & Big Data Day 2018, Data Science UA Conference, Big Data Conference Ukraine, etc. Also, such organizations as Power BI Ukraine community, Ukrainian Data Community Kyiv, and others are aimed at spreading knowledge of leading European and Ukrainian experts. They organize various events, discussions, and conferences on the latest data analytics practices. What’s more, various Ukrainian universities such like UCU and others are launching innovative educational programs in data science and other technological fields.


Local tech communities organize various data-related events such as Big Data Technology Summit, Big Data Tech Warsaw, and Devoxx Poland, which generate interest in this sphere in Poland.

Around 75,102 data analysts are employed in the IT sector in Poland, according to Linkedin. Despite the vast availability of resources, finding data analytics talents who are eager to work in the outsourcing sector is a challenge. The country has a developed R&D sector with offices of numerous global companies such as Accenture, Atos Consulting, Amazon, Google, and many others. Thus they create fierce competition for talent, and the majority of local data experts are employed in these international corporations.

Want to discover more about talent distribution of data experts in Eastern Europe? Read our article.

How to choose the right data analysis specialists?

A properly built data analysis team with cross-functional expertise and the necessary skill set will become an integral part of any business setting. While many responsibilities and goals of data scientists, BI consultants and big data analysts closely match, there are major differences between the required skill sets for each of these positions. So how to choose the right data analysis experts to help you identify the hidden growth opportunities? Let’s explore the most important requirements for key data experts.

  • Data scientist

Experienced data science specialists should understand data processing frameworks and platforms such as Hadoop, Spark, Flink, etc. Their tech stack should include analytical tools such as SAS and/or R and technologies like Python (the most common one), SQL, Java, Perl, or C/C++.

Moreover, professional data scientists should be well-versed in multivariate statistics (including regression, principal components analysis and clustering), and data-driven predictive model development. Also, experience with Hive or Pig would be a strong selling point along with cloud tools such as Amazon S3. This will enable your data science expert to perform market basket analysis, sentiment, behaviour and predictive analysis to turn your data into valuable information.

  • BI consultant

Any qualified BI expert should be well-versed in data extraction, data aggregation, data grouping, data modeling, data visualization techniques to produce comprehensive reports and actionable insights for your business. Their BI tech stack should include such data warehousing technologies as MS SQL, Redshift, etc. as well as data visualization tools such as Tableau, Pentaho, Excel, QlikView, QlikSense, Cognos, and MicroStrategy.

Moreover, warehouse design skills, expertise in SQL, Python, and Java are a must for any qualified BI expert. If your project entails big data storage, a professional BI consultant should have a good command of big data tools such as Hadoop, Spark, AWS Kinesis, Hive, Pig, and Kafka. What’s more, experience with Microsoft BI Stack (MS SQL, SSIS, SSRS, SSAS, Tabular models, Power BI, etc.) may be also beneficial for your business success.

  • Big data analyst

Solid mathematical background and profound knowledge of an array of algorithms and mathematical models are a must for big data professionals. Strong big data specialists should be able to work with machine learning and deep learning algorithms as well as robust big data software. This will enable them to perform efficient client analysis, price optimization, risk detection, market segmentation, demand forecasting and much more.

Additionally, experience in working with Hadoop and a number of open source big data technologies such as Spark, Hive, Flume, Pig, Impala, Oozie, etc. is a huge plus. Whereas experience with Amazon Web Services (Kinesis, EMR, Lambda) and Azure is necessary for efficient data processing and analysis.

If you want to find out more information on how to choose a reliable data analysis provider, read our article.


Over the past few years, many businesses have embraced data analysis technologies to better understand their clients’ preferences and maximize their ROI. This has significantly boosted the demand for data analytics services along with the interest towards data analysis outsourcing. Offshore software development vendors help companies save valuable time & costs and focus on core competencies. We hope our overview of the data analysis outsourcing market will help unlock and power of your data and you move your business forward. For more information, contact our experts.