We hear the words “data analytics”, “data science”, “AI” and “machine learning” more often than ever, especially as businesses are seeking to outsource data science solutions. Accedia and the whole IT industry are experiencing a shift in customer inquiries that involve solutions developed with smart technologies. With the increasing amount of raw and unstructured data that businesses are gathering, the dynamic turn of events across industries, and changing political and economic environments, it seems that intelligent technology solutions are the new future.

In this blog post, we would like to share with you the forecasted growth of the data analytics and data science field, its importance, and our experience with developing solutions to address such customer pain points.  

The future of data analytics and data science (a.k.a global enterprise buyers’ preferences)

Regional overview of the market 

North America definitely holds the top position for a country which chooses to outsource data science and data analytics is growing. However, Europe is not far behind on that. According to Statista report, revenue from the segment of general IT outsourcing is projected to reach US$2.69bn in 2022. In the period 2022-2027, revenue is expected to show an annual growth rate of 17.17% which would bring a market volume of $5.94bn by 2027.

Bulgaria is ranked as a capable country as well, together with Slovenia and Romania (GBS World Competitiveness Index). It reaches a rank of 3 (out of 8) for global buyers’ preferences to outsource to the country. The forecasts are that the score will increase in the next 12 months and Accedia can attest to that as we are recording higher number of our clients located over 20 countries enquiring about intelligent solutions.

5 Factors to Choose Bulgaria to Outsource Data Science And Data Analytics

Accedia’s experience with data science and data analytics

Over the years, Accedia has gained expertise in developing intelligent technology solutions for diverse industries. Our culture of sharing know-how and freely exchanging ideas, as well as the increasing clients’ project cases backed the development of a company-wide initiative – Accedia AI Capability Center, mentioned above. We use a proprietary AI solution implementation methodology (plug and play) for our existing clients. As a part of it, in the first step, we analyze business needs, challenges, and opportunities, as well as the technology landscape. Based on these findings, we identify so-called quick wins. 

We use proprietary models from our pre-existing AI repository that are applicable to the client’s case. These models address common client pain points and through them, we can quickly deliver value to businesses looking to adopt AI and data science. The models majorly cover areas such as voice assistance, sentiment analysis, predictive regression and classification, propaganda detection analysis, credit scoring, forecasting, automated marketing, and else.

There are of course cases in which we need to dive in the untouched AI area and use different data analytics tools, frameworks, and methodologies. In these cases we ramp up a team and the ideation process begins. Below we share a few major projects, in which we have helped clients mainly in the predictive analytics fields.

For a client, a French international banking group operating in over 72 countries, we developed and integrated a Machine Learning algorithm that allows marketers to run different models for direct marketing campaigns. The teams input clients’ transactions data and retargeting list and the model generates in response a direct marketing strategy with special offers and certain conditions to offer to the said clients, as well as the most efficient marketing channels to target them through. This saved our client essential time and reduced budget considerably.

Another client, an international full railway engineering service provider, used IoT devices with sensors provided by a range of suppliers to collect data from different railway machinery owned by the group. Accedia partnered with them to develop an Azure-hosted web application that consumes data gathered by the IoT devices (telemetry, the status of the machines, location, speed, etc.) and renders it in comprehensive dashboards in the forms of tables, graphs, and charts. Through the solution our client could easily point out data trends and anticipate any future machine failures, thus scheduling timely repairs and reducing business costs further.

Software Development Outsourcing Case Study: From a Vendor to a Strategic Partner

Final words

As the Data Science and Data Analytics market continues to surge, companies need to find innovative ways to keep up with the demand and the competition. One viable option is to look for external vendors and outsource data science services. This strategy is based on the observation that more and more businesses are becoming aware of the benefits that intelligent solutions can provide, which in turn translates into improved productivity. As a result, outsourcing data science is increasingly seen as a smart move for companies seeking to leverage the power of data-driven insights to gain a competitive edge.

What we have noticed so far is that businesses need support in taking practical advantage of intelligent technologies to their benefit. Only a numbered few of the big tech giants are doing real data science and data analytics and we’d like to change that by making AI accessible to businesses from all scales. Is your organization ready to embrace an intelligent future? We can help you evaluate the feasibility of your ideas and the benefits  you can reap. Just get on a quick call and take advantage of a free AI consultation with our team.

Congrats on taking the first step of this smart journey!