More and more companies are adopting big data to become and remain competitive. The big data market is predicted to reach $103B by 2027, according to Statista.
How to take full advantage of big data? Where to look for a big data outsourcing partner? How to choose a reliable big data analytics outsourcing provider? Find the answers to these and many other questions.
Benefit from big data analytics outsourcing:
1. Save costs
Amid the Covid-19 outbreak, big data analytics outsourcing has gotten even more popular than ever. Gartner estimates that the financial impact on the global economy, caused by the pandemic, will amount to $2T-$4.5T. Thus, optimizing operations and saving costs became top priorities for businesses.
Hiring experts from locations, where the cost of living is lower, is more cost-effective than looking for specialists locally, in the USA and UK, for example. What’s more, these experts are hard to retain as they are often allured by tech giants.
As a result, many businesses hire offshore and nearshore experts rather than work with local specialists. For example, one of N-iX clients, a Fortune 500 industrial supply company initially hired on-site consultants to develop and support their data management solution. That, however, caused significant overhead costs. To reduce the operational costs and migrate the solution to the cloud, the client chose to outsource big data development services and selected N-iX as their offshore development partner.
2. Tap into varied tech and domain expertise
Well-established IT outsourcing companies have robust expertise in big data engineering, cloud (multi-cloud, hybrid cloud), DevOps, security, microservices, etc. and they can help you with a variety of tasks.
What’s more, if you choose a partner with a large portfolio of big data outsourcing projects, they usually are familiar with different cases and can find the best and most efficient solution to your business problems. The company can conduct an audit of your processes and help you with business and product discovery. The product discovery phase will help you choose the right tech stack and get all the deliverables needed to start the implementation phase, as well as mitigate risks and save costs.
3. Find the best experts easily
The demand for big data grows rapidly and the labor market fails to keep up with it. According to McKinsey, the retail industry alone is expected to increase big data adoption by 60%. As a result, we witness an acute talent shortage in the field. As of January 2021, USA-based companies struggle to fill in 35K big data-related positions, according to LinkedIn.
Big data outsourcing helps to solve the problem. At the time of remote, finding experts gets easier. Moreover, if you choose to partner with a big data outsourcing company, you can both access the internal talent pool and entrust all recruitment to your partner.
Although the benefits of big data analytics outsourcing are tempting, selecting a big data outsourcing destination is no easy task. To help you, we have reviewed the three most popular big data analytics outsourcing destinations in Eastern Europe - Ukraine, Poland, and Romania.
Which location to choose for big data analytics outsourcing?
Big data outsourcing to Ukraine
Ukraine boasts a strong tech education heritage. What’s more, many local universities have new STEM-based educational programs. For example, Ukrainian Catholic University offers a Data Science Master’s program. The curriculum includes applied statistics, probabilistic analysis, data science, machine learning, and many other subjects.
The Ivan Franko National University of Lviv has also launched the Statistics and Data Science program. The curriculum covers data collection, business intelligence, machine learning, computer vision, artificial neural networks, etc.
Many businesses have already benefited from big data outsourcing to Ukraine. The country is home to 88 big data outsourcing companies (according to Clutch). Linkedin lists around 8,000 big data experts in Ukraine.
Big data analytics outsourcing to Poland
Poland has a talent pool of 19,000 big data specialists, according to Linkedin. Clutch lists 108 big data vendors in the country. However, some of them are product companies, so they are not available for big data analytics outsourcing.
Big data outsourcing to Romania
The country is known for the extensive talent pool of developers. Romania is home to the third most extensive pool of tech experts in Eastern Europe.
LinkedIn lists around 8,000 big data professionals that are currently engaged in the Romanian IT market.
These were three Eastern European countries with the most developed big data outsourcing market. However, the question remains: how to select the best big data outsourcing partner? Let’s find out.
How to choose a partner for big data outsourcing?
1. Make sure your potential big data outsourcing partner can help you with scaling your product
Choose a vendor with expertise in big data, cloud, DevOps, etc., to cover different needs. Look for a partner that can help you to both launch your big data project and scale it efficiently, while helping to optimize costs.
The inability to scale up a big data solution is often one of the biggest big data challenges. Thus, it is critical that the solution and its architecture are fit for scaling in the cloud.
Our big data engineers are often contacted by companies that have on-premise big data solutions. The solutions are not fit for scaling and need moving to AWS, GCP, or Azure. For instance, N-iX big data engineers helped an in-flight internet provider migrate from their on-premise big data solutions based on Cloudera to the AWS cloud.
Also, we help companies refactor monolithic architecture to microservices to make their big data solutions more scalable and migrate them to the cloud.
Look for a partner that can help you to both launch your big data project and scale it efficiently, while helping to optimize costs.
2. Choose a partner with an established security policy
There are critical international security standards a trusted provider of big data outsourcing must comply with.
Compliance with ISO 27001 is implementing administrative and physical controls that ensure confidentiality, integrity, and information assets availability.
Companies that accept card payments and store, process, and transmit cardholder data must comply with PCI DSS.
Compliance with HIPAA law is required if you work with medical data.
Also, your big data analytics outsourcing partner should follow these best practices to ensure data security on big data business process outsourcing projects:
- Implement static code analyzers;
- Implement vulnerability scans for third-party libraries;
- Check whether traffic is encrypted and whether sensitive data is cached.
3. Choose a vendor with a proven track record of big analytics data outsourcing projects
A trusted big data outsourcing vendor should have a proven track record of successfully delivered projects and diverse expertise with cloud platforms, technologies, and tools.
For instance, N-iX offers a wide array of big data services. They are big data architecture design, cloud-based big data solutions, platforms for data-driven decision making, etc. We cooperate with North American and European clients in healthcare, fintech, manufacturing, telecom, etc. Our partnerships include:
- Gogo: a global provider of in-flight broadband Internet: the company has established a long-term (4 years +), strategic partnership with N-iX.
First, we helped Gogo migrate their on-premise data solutions to the cloud in order to collect and process a considerable amount of data from more than 20 sources. Migration to AWS helped Gogo both increase the data processing capacity and cut costs on on-premise infrastructure and licenses. Then, we built a cloud-based unified data platform that collects and aggregates both structured (i.e. systems uptime, latency) and unstructured data (i.e. the number of concurrent Wi-Fi sessions and video views during a flight). N-iX big data engineers built an end-to-end delivery pipeline: from the moment when the logs come from the equipment to the moment when they are processed and stored in the data lake on AWS.
To predict and prevent the antenna equipment failure and decrease the no-fault-found rate (NFF), we used the data science models, such as Gaussian Mixture Model and Regression Analysis. As a result of the big data solution development, the no-fault-found rate was reduced by 75%, thus saving costs on unnecessary removal of equipment for servicing.
Here is their review on the cooperation with N-iX:
Fortune 500 industrial supply company (under NDA): The company was looking to reduce big data development costs and outsource their big data engineering to a reliable vendor. Also, our client wanted to migrate the solution to the cloud to make it more scalable and cost-efficient. To migrate from on-premise Hadoop Hortonworks cluster to AWS and allow processing additional data in AWS, the N-iX team built an AWS-based big data platform from scratch. Also, we have been involved in extending and supporting the existing Teradata solution. To choose the data warehouse design and the tech stack that fit our client’s business needs, our specialists created a proof of concept. We compared Amazon Redshift with Snowflake and preferred Snowflake as it met the client’s approach of cloud neutrality: it can easily scale up and down any amount of computing power for any number of workloads and across any combination of clouds.
The whole development process is cloud-agnostic and is designed to ensure that the client can easily change the cloud provider in the future. For example, we use Terraform as it is compatible with all cloud vendors - AWS, Azure, and Google Cloud. N-iX big data experts helped the client enhance data management due to the unified data platform and enable predictive analytics.
How to choose big data outsourcing specialists?
Your big data outsourcing developers should have expertise in:
- Hadoop ecosystem and Apache Spark: these tools allow extensive data storing and processing;
- Cloud-based tools, including Snowflake, EMR, Dataprots, BigQuery, DataFactory, Cloud Composer, Synapse Analytics, DataBricks;
- SQL/NoSQL databases;
- RedShift, Hive, Athena: these big data tools are used for querying data;
- Your big data analytics outsourcing developers should be able to maintain old MapReduce Java code and rewrite it using a more recent Spark technology;
- Scala, Python, and Java.
- Kubernetes constructs: they are used to build big data CI/CD pipelines.
- Kafka, AWS Kinesis, or Apache Pulsar: they are needed for real-time big data streaming.
Why partner with N-iX for big data outsourcing?
- N-iX has over eight years of experience with data science and big data analytics;
- N-iX has 80+ data analytics professionals;
- N-iX has been recognized by ISG as a Rising Star in data engineering services for the UK market and positioned in the Product Challengers Quadrant both in the data science and data Infrastructure & cloud integration services.
- N-iX experts can help you with big data architecture design, cloud-based big data solutions, data science software, machine learning algorithms, as well as customized data science applications and reports;
- Our professionals have experience with Apache Spark and Hadoop and the Hadoop ecosystem’s key components, such as Hive, Flume, Pig, Impala, Oozie, etc. Also, they use Apache Airflow and AWS cloud computing products such as Lambda, EC2, S3, and SQS. Also, we are skilled in working with AWS analytical tools, including EMR and Kinesis;
- We have delivered big data solutions for such industry leaders as Gogo, a multinational MVNO Lebara, a British fintech company, and Fortune 500 companies.