Big Data: new skills for new professions

Did you know that 2.5 quintillion bytes of data bytes are created every day?  But what happens to all this information? We talked about this with Carlotta Orsenigo, co-director of the International Master in Business Analytics and Big Data.

That’s a staggering number. Where does all this data come from and how is it used?

When it comes to Big Data, there are two areas we think about right away.

On the one hand, there is the Internet of People – the data that users generate as a result of the digitisation of personal relationships. I’m referring to texts, messages, comments, videos, images, and so on.
This information, left by users on blogs, social networks or e-commerce sites, can be collected and used, for example, for sentiment analysis and therefore, to deduce the emotional inclination of users towards a given topic.

On the other hand, we then think of the Internet of Things, or all the data generated by sensors, such as those relating to the location or operation of a particular device. This data is collected and used in various fields, such as that of industry. An example would be the designing of predictive maintenance systems, capable of predicting the onset of a malfunction on a machine or production line in advance, with the aim of reducing risks and costs, and guaranteeing greater safety of the production process.

There is also a third category, that of data collected by corporate transactional systems. This can be exploited for a variety of applications, such as the construction of recommendation engines, which generate suggestions for products and services which can be customised on the basis not only of past purchases, but also of users’ interests.

To extract all this information from the data collected, you need someone who is able do this. What are the professional profiles that are emerging in response to companies’ growing interest in Big Data?

Today, the most sought-after figure on the market is that of the Data Scientist.
The skills required are of different types: modelling, analytical, skills related to the field of artificial intelligence and machine learning. Alongside hard skills related to data management technologies, machine learning, artificial intelligence, and coding – algorithms must be built and implemented  – the Data Scientist should also have management and governance skills. This is essential in order to be able to relate effectively to those within the organisation who deal with the company’s activities and so that the analytical activities they carry out can be translated into actual value.

To summarise, the Data Scientist is the expert in data analysis methodologies, and is the most sought-after figure.

But there is not only the Data Scientist. The Data Science Architect, for example, is responsible for managing and developing analytical pipelines, therefore the entire analytical process, and the technologies to support analysis, management, and data collection. This is a person who takes on the technological responsibility for the analytical process.

There is also the Data Analyst, who uses their analytical skills to monitor the company’s performance. In this case, the skills sought are more those like statistics, reporting and data visualisation, so maybe the more “traditional” skills, but which are just as valued as those relating to machine learning and AI.

In conclusion, data analysis experts can take on positions with many facets and play a role of primary importance in the business world, which is increasingly realising the hidden value of the data it collects. However, this value only emerges if the methods of analysis are used appropriately. This is why experts are needed who are able to process data and carry out analyses using appropriate techniques in a considered way.

According to research by NewVantage Partners, over 91% of executives surveyed report increased investment in Big Data. Which sectors are most affected by this growth?

There are certainly some sectors which are more inclined in this direction, although in reality demand is developing  ̶  albeit with different intensities  ̶  across all sectors.

According to the latest data from the Big Data & Business Analytics Observatory of the Politecnico di Milano, the sector that records the most substantial growth is banking, followed by retail and telecommunications.
However, other sectors are also experiencing significant growth  ̶  not least, public administration, health and manufacturing.
Recent months have led to a slight decline in investment due to the pandemic, but forecasts for the next few years are for a recovery, even a substantial one.

The data collected by a bank is presumably very different from that generated by a hospital. How does this affect the training of the people who will work in these areas and how has MIP responded to such diverse market needs?

As I said before, demand for data analysis experts is growing, and their role is increasingly multifaceted. It is precisely in order to meet this constant and growing demand that our Business School has decided to expand its range of specialised courses.
In addition to the Master in Business Analytics and Big Data (BABD), which will reach its sixth edition next year, two new programmes have been introduced – one in the field of Supply Chain and another in Healthcare – two verticalisations in two areas that we envisage will increasingly be needing these skills in the near future.

The three masters are structured in such a way as to share the core part of the training path, which is dedicated to technologies for the management of big data and, above all, methodologies for data analysis, with particular reference to machine learning, artificial intelligence and data science.

The three programmes then diversify: the BABD master remains transversal to the themes of data science and artificial intelligence, supported by case studies and applications in different fields.
The other two masters, on the other hand, offer specific verticalisations.
So, for example, the Master in Big Data for Healthcare & Biotech aims to train data scientists who understand and know how to govern the complexities of this sector, who can interact with various parties: doctors, healthcare workers and decision makers. They also know how to put forward innovative solutions through data analysis. This always in compliance with the rules and ethical principles governing the collection and analysis of data in this particular context.

By contrast, the Master in Big Data for Supply Chain Analytics aims to provide expertise specifically directed at supply chain management and the use of IoT technologies for the collection and real-time monitoring of supply chain activities, with the ultimate goal of optimising decision-making processes in this area.

«Data science and business analytics: today companies can’t do without them»

Professor Carlo Vercellis, director of the executive programme in data science and business analytics, tells about the latest trends in the market of big data and makes an appeal: «External consultants are no longer enough. Organizations now need to integrate these positions internally»


Growth which for the last five years has been constantly in double digits, around 20%, investments that in Italy reached the value of 1.7 billion euros. The market of analytics, in other words the analysis of data, has come to a turning point. «But now it’s time to grow», says Professor Carlo Vercellis, professor of machine learning at Politecnico di Milano, director of its executive programme in data science and business analytics and scientific head of the Big Data & Business Analytics Observatory. «Large companies have gained familiarity with these tools, although up to now they have mainly relied on external consultants. It’s time to incorporate these figures within companies, even in SMEs. There are many challenges to be faced, just as many professional figures required and therefore job opportunities for those who want to work in this field».


Organization, management, process automation: the latest trends

There are two particular trends identified by Vercellis. «The first challenges are of an organizational and managerial nature, and involve the governance of the supply chain of data driven projects, that is those based on data: moving from experiments, which have become increasingly numerous and complex, to the pilot project, and then to the start of production and to deployment. The second challenge concerns business processes, that must be changed in a data driven perspective. We’re thinking about process automation, that is an automation of processes that substitute human activities with little value added through algorithms that allow software and robots to carry out a series of repetitive tasks. This allows to free up resources, human and material».


Lots of data, lots of algorithms: the need for functional awareness

However, data alone is not enough. You need to know how to question, read and interpret it, and for this there’s a need for specific skills: «We are submerged with data. The two main sources are social activities, that provide unstructured data, which cannot be reduced to tables of numbers; and the Internet of Things, or that network of objects, household appliances included, with smart features, which collect large amounts of more structured data», explains Vercellis. «To read them you need to know which analytical tools to use: we’re talking about algorithms, obviously, which while sharing basic settings are not all the same. According to the task to be carried out, one can be more suitable than another. For this reason, there’s the need for a professional with “functional awareness: experts capable of using data and business analytics tools, without having to be technicians. These are the professional roles that companies are starting to look for today, because little by little they are realizing that external consultants are not enough».


The job opportunities in the world of analytics

The professional profiles that fit this requirement are varied. «They go from business users, able to understand the logic and limits of these tools, to the translator, a bridge figure who knows the language of data science and business, and is able to facilitate communication between these two worlds. Professional roles today are increasingly technical: the data scientist, data engineer, business analytics data scientist solution architect».


The executive programme in data science and business analytics of MIP Politecnico di Milano aims to train professionals in the different areas needed: «It’s a course that begins in October, requires a commitment of two days a month and touches on all the issues tied to this subject», explains Vercellis. «It involves hands-on sessions and final project work in which students must apply notions learned to a problem, proposed by themselves or professors of the MIP faculty. The course is for individuals, who perhaps are looking to reskill, but I expect that above all it will be companies that take advantage of this opportunity: a great opportunity to train an internal resource able to manage the company’s needs, a task that an external consultant would never be able to carry out».

Desperately wanted: Big Data Analysts

From your smartphone connection to the GPS on your company car via social media, your supermarket loyalty card and cookies on your PC: you’ve surely realised that in every moment of our lives we’re being observed by a great IT eye in the sky which tracks every aspect of our daily routines.

Our buying, consumption and lifestyle habits are constantly being monitored by the companies that accompany us through our day. This monitoring produces an enormous amount of information on us, on our desires and on our movements.

So where does this data end up and what’s its purpose?

The glut of information companies gather on the habits of their customers or users is known as Big Data in business jargon.
It represents a wealth of knowledge that could be used to accurately predict the future and help companies to improve the quality of the products and services they offer on a daily basis.

Could be used, if it weren’t for the lack of professionals on the labour market with the necessary training to analyse the data and turn the numbers into facts, thus painting a truer picture of customers who – unknowingly – have left vital clues along the way.
Is all this really possible?
Absolutely. Let’s take a look at the stats:

Accenture calculates that in the US alone, there are over 30,000 Big Data Analysts available;
Mckinsey estimates that in 2018 there’ll be a 50/60% disparity between supply and demand when it comes to experts in the analysis and evaluation of Big Data;
The European Data Science Academy states that by 2020, demand for Big Data Analysts in Europe will increase by 160%.

But which companies are looking for Big Data professionals?

The first thing you need to know is that the analysis of data and information is a cross-market priority. Indeed, the sectors looking to become masters of the Big Data universe range from telecommunications – which uses the information to locate client and better interact with them – to healthcare, which uses Big Data to deploy ad-hoc services designed to fit client needs.

The search for these so-called data sciences isn’t confined to a particular size of company either. For SMEs, Big Data represents an extraordinary opportunity to take a leap forward and become more competitive, while colossuses like LinkedIn, Google, Amazon and Boston Consulting Group are always on the look-out for talented professionals in the field.

So what do you do?

A great way to ride the wave of the trend and successfully launch yourself onto the work market is undoubtedly to invest in specialized training such as MIP International Master in Business Analytics and Big Data or to undertake the MBA program with an ad-hoc Big Data Management Bootcamp.

Honing your skills in the area means you’ll become a sought-after resource – and a very precious one at that.

Someone who can vouch for that is MIP MBA student Pradeep Bhat, who – thanks to the Big Data Analytics courses offered by the Italian business school – landed a summer internship at IBM Business Analytics, supporting financial services companies trying to increase sales.

It’s an example of an innovative experience designed to prepare you for future challenges and direct your professional career towards fertile ground, as Pradeep Bhat himself confirms:

“It was exciting for me to be a part of a new era of computing systems […] It helped me shift the direction of my career”.

An incredible opportunity you can’t afford to miss out on!

CleanTech Challenge Italy, new edition ready to go

For the seventh consecutive year, MIP is the Business School, with exclusivity for Italy, appointed to organise the CleanTech Challenge Italy, the Italian stage of this international competition dedicated to the world of green and clean technologies overseen by the London Business School (LBS) and University College London (UCL).

Apart from the Italian chapter headed by MIP Politecnico di Milano, the international competition consists of several national rounds organised, among others, by INSEAD for France and Vlerick Business School for Belgium.

The challenge is to develop innovative ideas for clean technology, from the design stage to obtaining the funding to realise the project.

The deadline for students to present their ideas is 11 March 2018. The finalists’ projects will be presented at MIP’s main building on the 23 and 24 March 2018.

Further information and the competition’s regulations are available at

At the end of the Italian round, the winning team will receive € 5,000 provided by the Gianluca Spina Association, a not-for-profit association created for the advancement of the innovative educational projects championed by MIP’s past president and dean, who died prematurely in 2015.

The winners will also represent Italy at the CleanTech Challenge finals, held at London Business School on 26 and 27 April 2018, where the prize is £ 10,000.