This article was originally posted on LinkedIn Pulse by Jigsaw Academy’s Vice President – Academic Sales, Gaurav Baidyasen. This is an attempt to draw an analogy between Games of Thrones and Business Analytics to understand a few key questions on the table for organizations.
A wise man once said that you should never believe a thing simply because you want to believe it – Tyrion Lannister
Use “Data – Smart” Culture to believe it
In today’s competitive era, every organization is thriving to build a robust and sustainable business model. Apparently, these establishments have realized that they need to build a data driven culture to make efficient decisions. Gone are the days when experts made decisions purely based on gut feeling or guesswork. Becoming “Data Smart” is the new normal and this culture is becoming the keyword for success, especially for new-age companies. When it comes to competitive positioning, organizations these days are either structuring it based on the ‘economics of scale’ or based on the ‘economics of scope’. Does it still hold true? Companies, big or small, have become more ambitious than ever – Why not achieve both? – is the question they’ve started asking themselves. The advent of data science and machine learning has added a new, third dimension – the ‘economics of speed’. The diversity in the application of analytics has proved to be a catalyst for different businesses.
The world is now watching the 8th and final session of the epic fantasy series – Game of Thrones and, needless to say, there has been a sensational wave of excitement and joy across the planet. It would be a crime NOT to talk about it, right? Hence, Let’s take a scenario from Game of Thrones.
How about an attempt to draw an analogy between Games of Thrones and Business Analytics to understand a few key questions on the table for organizations?
- Are companies relentlessly searching for people with characteristics like that of Jamie Lannister, Tyrion Lannister or Lord Varys to build a data smart culture?
- Do organizations want to be a warden of the north or look for that iron throne (Strategy to build data smart culture for a function or for the entire group)
- What am I looking at? – Breath-taking warrior skills like that of Jon Snow (core machine learning) or those crafty political skills that Tyrion Lannister (business knowledge) possess or, is it both?
- Can Jon Snow singlehandedly protect the north from the army of the dead? (solve all complex problem on its own)
- What should be the hiring strategy for Daenerys Targaryen (system) to prepare the army to win the seven kingdoms? (data-smart culture) ?
Similarly, there is a lot of anxiety too among aspiring data scientists. They have been exposed to multiple learning platforms, skill building channels and MOOCs to develop business analytics skills which would help them exploit the gargantuan demand in analytics. But the million-dollar question is – HOW?
The current talent pool is smart to choose the right choices for them. Nevertheless, there still are a few apprehensions professionals have while thinking about transitioning into a career in data science.
- How can a BI professional make that transition to analytics?
- Is analytics only about programming?
- Is analytics all about building models?
- What are the must-have skillsets to have to my dream job in analytics?
- There are so many options for upskilling – What to consider or what not to?
- I am an IT professional with minimal/zero programming skills. Can I be a successful data scientist?
- Who are the kind of companies that hire professionals from the analytics space?
- What is the growth in terms of career progression and compensation that I can look forward to?
If you carefully analyze the two sets of questions above, you will be convinced that there is a mammoth demand which actually triggered the seed of thought to exploit the available opportunities for aspiring data scientists. So, the problem is solved!
Hold on to that thought – We still have to answer the ‘HOW’ of it all!
There is a very common myth that analytics is all about programming and modelling. Let’s go back to GOT analogy. Jamie Lannister is arguably the best knight in the seven kingdoms. He is considered to be the most ruthless knight who possesses Valyrian steel sword with amazing sword skills, movements and reflections. Apparently, he lost one hand in a battle which could have ended his reign as a Knight. However, he trained himself to use the sword with the other hand. But what if he had lost his sword forever? Would he still be one of the greatest fighters in the seven kingdoms?
We can certainly learn from this analogy to understand the integration of business acumen and data science skills. There has been a hoard of MOOCs, online/offline programs floating around to teach data science, predictive modelling, machine learning, AI, deep learning and so on.
The question to ask – Is it good enough to crack an interview for data science roles? And the answer, evidently, is a resounding NO!
Just like Jamie Lannister who owns a Valyrian Steel along with a stunning sword and movement skills, an individual needs the knowledge of both business insight and cutting-edge business analytics and machine learning skills to make an impression on their prospective employers.
Now, let’s take a look at another perception – Would Jamie Lannister be as great as he is, had he not been part of the “House of Lannisters”? Apparently, it is extremely important to belong to a house to earn respect and pride. This anecdote can infer to the “brand” behind you to make a mark on your career. Out of the endless upskilling options for learning business analytics, the wiser option to learn would be to get associated with a brand. Brand carries its own aura and it is an authentication of competency and skills, just like in Game of Thrones.
So, the optimal approach to learn business analytics would be summarized as – integration of business acumen, data science skills and a brand association which can build a compelling case for one’s future employer.
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The Integrated Program in Business Analytics (IPBA) curriculum is designed to be a comprehensive program covering technical and business aspects of the application of analytics and data science. It starts by laying a strong foundation of essential tools and techniques including descriptive and inferential statistics, data extraction and manipulation with SQL, data manipulation and processing with Python & R, and data visualization with Tableau.