Digital transformation touches all areas of business, including product innovation, operations, go-to-market strategy, customer service, marketing, and finance. However, digitization is not only about the acceleration of business processes and leveraging new opportunities. It is also about the need to outpace digital disruption and solidify one’s position in a rapidly evolving business environment. To identify which areas need to be transformed and how, to eliminate the possible risks and avoid the unnecessary drain on resources, modern organizations adopt the data-driven approach to digital transformation. They use data science, big data, machine learning, BI to collect, process, and analyze their business data, which they can then turn into actionable insights.

Latest surveys indicate that data connectivity and integration are considered as critical components for digital transformation by most businesses. The number of job postings for data scientists is growing by 29% year-over-year (with a total 344% growth since 2013). Related search queries for ‘data science’ have increased four times over the past five years. As a result, a lot of companies that want to unlock the power of their data lack the necessary expertise or resources. In this case, data science as a service can play a crucial role in helping to digitally transform your business and increase ROI.

We provide data science services on a wide range of projects in different industries, and we’ve seen its transformative effect many times. In this article, we share some of the insights we’ve gained and the tangible benefits DSaaS brought to our clients.

data science as a service

Enabling data-driven decision making

Since the digital transformation is a complex process, data about your customers and business operations can help you make informed decisions while preventing unnecessary risks. With data science capabilities, you may identify how to digitally transform your business and which business areas require transformation. At the same time, data science as a service allows companies to hire a professional provider that has the necessary resources and can help you implement this transformation faster keeping you ahead of the competition.

No wonder why more and more organizations are embracing data science as a service to access a huge pool of data experts to enhance their decision making. A research from MIT’s Sloan School of Business indicates that companies that are engaged in data-driven decision-making experience a 5 to 6% increase in output and productivity. Thus they are able to generate an impact in their digital strategy and operations, whether it is in a form of increased revenue, reduced costs, or improved efficiencies. With DSaaS, customer intelligence is now as optimized and accessible at all levels of the organization as possible. So embedding and ingraining data science as a service into decision-making processes is essential to obtain the desired results and benefits from digital technologies.

Identifying threats and opportunities

The volume of available information is growing rapidly along with opportunities it opens up. Data science as a service enables organizations to cope with a shortage of data scientists and leverage data science for a more panoramic and more detailed view of their business environment. Data science is enabling the next generation of solutions that may predict what is going to happen and how to avoid this. For instance, imagine having a CRM application with the ability to forecast which customers are most likely to make the next purchase, which products will be part of that purchase, and which customers are at risk for attrition.

The solutions enabled by data science allow businesses in various industries to have real-time visibility of their customers, helping decision makers to optimize the internal operations for greater agility, increased flexibility, and lower costs. For instance, our client Gogo, delivering reliable Internet connectivity and entertainment to aircrafts worldwide, has already enhanced the passenger experience and prevented faults in aircraft equipment with data science as a service. The company is cooperating with a team of data scientists who identify, analyze, and interpret trends and patterns in complex data sets as well as analyze results using statistical techniques. Moreover, they make predictions of maintenance of different units on aircraft and analyze the correlations and dependencies of different factors and indicators on a flight. So data science as a service enables the company to take the necessary steps to mitigate risks and facilitate quick and continuous service improvements.

Driving even more value with machine learning

Being a part of the data science ecosystem, machine learning can accelerate your digital transformation in banking and other industries. It helps to crunch massive amounts of data to identify patterns and anomalies. As one of the major approaches to artificial intelligence that uses algorithms, it can surface insights without being explicitly programmed where to look for them. Data experts are leveraging the machine learning opportunities to model timelines and anticipate where disruptions may occur. For instance, Medecision has developed a machine learning algorithm that was able to identify 8 variables to predict avoidable hospitalizations in diabetes patients.

Another solution called Additive Analytics is leveraging machine learning to identify which patients are at high risk of readmission. With the help of its proprietary predictive model, hospitals can predict emergency room admissions before they happen thus improving care outcomes and reducing costs. So, with data science and machine learning capabilities, crunching massive amounts of data and providing answers to questions you have never thought of before is now possible. This speed to insight allows companies to do more with their data and see the whole picture of the customer journey.

AI funding by category: Machine Learning, Machine Learning Platforms, Machine Learning applications, etc.


Harnessing the full potential of innovative technologies and data requires developing an effective data science strategy.Data science as a service presents enormous opportunities by enabling businesses to easily leverage data science to make better decisions, operate more efficiently and profitably, offer more personalized experiences, and improve the overall quality of services. N ow businesses do not have to depend on guesswork anymore since data science can help to make more concrete predictions when both human intuition and experience fail. The key to seizing these opportunities lies in our ability to seamlessly introduce data science into the digital transformation processes within your company.