How Data Science Is Turning into a Commodity for the Non-expert and Dexda’s Role in This
Date: July 10, 2017
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Introduction

Few can argue that Data Science is an evolving field. Ever since its inception it has been changing, adopting new methods and technologies, while expanding its solution spectrum to address more and more industry problems. Through this journey, its existence became more well-known, and it gained a following of dedicated enthusiasts who flocked to learn more about this or the other tech data science encompasses. A couple of the things that remained relatively obscure, however, was the consumer of data science and the hows and whys of the machine learning methods used.

Who Is the Consumer of Data Science?

This may seem like an easy question and you may be tempted to say “the business, of course!” However, this answer is only partly correct. Although the end-user is usually someone in the organization the data science is applied, the primary consumer of the data science itself is the data scientist (or a team of data scientists in many cases). This is because all the methods and technologies related to this field are quite sophisticated, at least for the untrained professional, and as such they require a certain cross-domain expertise. Up until now this expertise has been the domain of the data science experts, particularly the senior-level professionals in the field, as well as some technical program managers with data science experience.

How Data Science’s Relationship to Its Consumer Is Shifting

Lately, especially since the introduction of A.I. techniques in the data science toolbox and the advent of new all-in-one platforms, data science is becoming more automated. As such, it is now more and more geared towards the non-expert as its primary consumer. Companies still need data science, of course, and the role of the data scientist remains relevant for R&D work. However, a lot of the complexity and sophistication of data science pipeline is abstracted. This means that whoever uses data science in their work doesn’t need to be an expert or have advanced programming skills in order to include data science in their work-flow. This not only facilitates the incorporation of data science in an organization but also allows for a more transparent communication of the methods involved.

Dexda’s Unique Approach to Data Science Services

So, what about more sophisticated problems that require real-time solutions, such as those involving IT event-management? That’s where Dexda comes in. Dexda is a data science company that has developed a platform for handling event-based data science as a service (DSaaS), focusing on the consumer of these services than merely on the technological aspects.

This promising London startup aims to deliver not just actionable and interactive insights to help you make better decisions using real-time data flows, but also enables you to integrate these insights into your work-flow through a clever priority system that is easy to interpret.

Their application of data science to the field of IT event management is both in-depth, intuitive, and functional, empowering the consumer to harness the power of data science without being a data scientist.

Charles Burnham, Product Manager for Dexda, added, “The consumerisation of data science – turning complex mathematics into an intelligible call to action – is key to Dexda. Our machine learning algorithms identify anomalies in the stream of IT events flowing from monitoring systems, log and management data. We correlate related events into a single insight alert, compute an importance score reflecting the insight’s unusualness and generate an explanation summarising the results of the machine learning in non-scientific jargon.”

This service is particularly useful if you are dealing with time-critical pipelines, have a strong interest in anomaly detection, or if your budget doesn’t allow for an in-house data science team for this kind of problem.

Final Words

Even though data science’s consumer approach is changing, Data Science Partnership is always on the lookout for new ways data science can help an organization’s data realize its potential through the use of the latest and greatest the field has to offer. This is why it joins forces with companies like Dexda, to be able to offer the world the data science services it deserves, services that go beyond the traditional statistical and machine learning approaches. You can find more about Dexda by contacting the Data Science Partnership team and arranging a free one hour video consultation.

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Zacharias Voulgaris

Zach is the Chief Technical Officer at Data Science Partnership. He studied Production Engineering and Management at the Technical University of Crete, shifted to Computer Science through a Masters in Information Systems & Technology (City University of London), and then to Data Science through a PhD on Machine Learning (University of London). He has worked at Georgia Tech as a Research Fellow, at an e-marketing startup in Cyprus as an SEO manager, and as a Data Scientist in both Elavon (GA) and G2 (WA). He also was a Program Manager at Microsoft, on a data analytics pipeline for Bing.

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