It has been vowed the most sexiest job of the 21st century.
(Well maybe not that sexy but at the least a profession that offers great carreer opportunities for a lifetime.)
When you think about Googling on it, you're already making use of its power.
When you Tweet about it or post about it on Facebook, you're adding to it.
When you think about what it will do, then that is exactly the future what it is computing about you.
What is this super hot job I'm talking about?!?
It's called Big Data and/or Business Analytics.
Sometimes referred to as Data Science or Econometrics as well.
These and more questions I'll answer for you now.
Any I am the right person to tell you, because I work in this specialization area since my graduation in Econometrics in 2006.
Big Data Business Analytics means analysing big volumes of complex data for systematically optimizing business goals.
It's so much data, that you cannot use a regular calculator or spreadsheet program any more!
The data can be both structured and well formatted, as a complete chaotic pile of unordened mess.
And there are so many (inter)dependencies between the data, that you cannot find the connections and relations by hand any more.
How on earth are you going to analyse this big data for getting actionable insights?!?
Luckily, there are solutions for exactly that!
That is what a Big Data Business Analyst, Data Scientist or Econometrician helps you with.
Formulating an accurate problem description (often a hypothesis for a business case)
Retrieving many data sets that may contain information on the cure for the problem
Ordering and preparing the big data sets for easy scientific analysis
Modelling the hypothesis as a statistical problem description to solve
Crunching the numbers in data science software that tries to find relations between your hypothesis and the ingested data
Evaluating the accuracy of the model outcome of training set data on test and validation data sets
Presenting your findings to your stakeholders
Coming up with a general statistical approach that can be productionalized at scale
Big Data Business Analytics (or Data Science, for that matter) isn't new. Actually, this profession already exists for decades. It is also known as econometrics and management science. So Big Data Business Analytics isn't something new. It's just a long-time proven fact-based approach to structurally achieve higher business goals, with a new trending fancy name.
However, due to the massively increased computing power over the last 10 years, complex business problems can now be solved within an acceptable amount of time using scientific techniques and advanced mathematics. The smart phone you now have in your pocket or purse contains more technology and has more computing power than a space station. The same holds for enterprises, that now have access to sophisticated big databases and worldwide computing power. In other words, business now has the tools to compute the answer right when it is demanded.
At the same time, due to the digitalization of the world, the pile of data increases more and more rapidly. In essence, there's so much data worldwide, that you'll never have enough time to organize, understand and utilize all that data. And we as a society keep adding data to this stock every day, so the amount of data doesn't stop to grow. Therefore smart computer algorithms are needed to help business find the right answers within that (sometimes messy) data.
So, because nowadays more and more people are acquainted with more data and faster devices every day, we get to understand that Big Data Business Analytics is more than before needed to achieve business success.
The business goals can be in the area of corporate finance and risk management, marketing intelligence and strategy, operations and supply chain management or general macro/micro economics.
Corporate finance and risk management aims to manage company finance in a global enterprise scope. At the same time huge numbers of outstanding loans, options, bonds and other financial instruments need to be carefully analysed, valued, assessed and monitored. The main goal is to find ways to make a better return on financial investments while carefully considering risks like counter party risk, risk of default, market risk and risk of (de)valuation.
The goal of marketing intelligence and strategy is to really understand the customer and discover how products and services can be best presented to the customer 'en masse', while keeping the customer experience personal and tailored to his/her needs. The main goal is to create and keep customers for the company brand, and sell the products & services for a profitable price.
Operations and supply chain management is applied in areas such as logistic networks, transport & shipping, inventory control, route and schedule optimization. It can also be applied to make systematic processes within a company more efficient and productive. The main goal is to save money on operations and make company processes work fluidly together.
You'll find general macro/micro economics mainly in governmental and political institutions and research laboratories. Mathematical and statistical techniques are used to find relations and segments within nation wide economic topics, like demographics, geography, politics, warfare etc.
In The Netherlands (the country I live in) there are 6 universities that teach econometrics. Some of them have labelled their courses Big Data Business Analytics. Other educational institutions call it Quantitative Research or Data Science.
|City (Province)||University||Student Association|
|Amsterdam (Noord-Holland)||Universiteit van Amsterdam||VSAE|
|Amsterdam (Noord-Holland)||Vrije Universiteit Amsterdam||Kraket|
|Groningen (Groningen)||Rijksuniversiteit Groningen||VESTING|
|Maastricht (Limburg)||Maastricht University||SCOPE | Vectum|
|Rotterdam (Zuid-Holland)||Erasmus Universiteit Rotterdam||FAECTOR|
|Tilburg (Noord-Brabant)||Tilburg University||Asset | Econometrics|
Top notch education is where the areas of business administration, computer science and data analytics are combined. Preferably with the entitlement of a Masters Degree in Science and Business Administration once successfully completed. Why? Because of this simple formula:
Big Business Targets × Scalable Enterprise Technology × Fact-Based Continuous Improvement = Lasting Enterprise Success
Programmes can be followed both full-time as well as part-time. The part-time option is very interesting for people who already have a Master's Degree and a solid quantitative background and relevant work experience. Be sure to look out for education where theory and practise is combined: learn & apply.
Typical courses that are taught are:
If you're a scholar interested in obtaining an university degree in econometrics in The Netherlands, be sure to visit www.econometrie.nl as this website contains lots of information in Dutch about studying econometrics in The Netherlands. The website is maintained by Stichting Landelijk Orgaan der Econometrische Studieverenigingen (LOES), where the six student associations in econometrics are united.
Recently, I've reviewed the book Creating Value with Big Data Analytics by Peter Verhoef, Edwin Kooge, Natasha Walk for ManagementBoek.nl and my professional contacts at Platform voor Klantgericht Ondernemen. It's an excellent English book on Big Data Analytics, targeted for both managers and data specialists, written by Dutch experts.
Because Big Data Business Analytics is so hot, there are many companies that are using Big Data Business Analytics. At the same time these companies regularly have vacancies for both junior and senior positions in Data Science and/or Econometrics.
ATTENTION COMPANIES / RECRUITERS: contact me to list your company or vacancy here
For scholars, obtaining an University Degree in Big Data Business Analytics may be a very good career choice for the next 10 years. Employees with affinity in Data Science and Econometrics will become more in demand by employers, and are encouraged to get even better at data analytics skills through education and experience. If you have a true entrepreneurial spirit, consider partnering up with other professionals to set up your own Big Data consultancy firm.