Last updated on October 23rd, 2024 at 04:40 pm
Much has been said about the word ‘Scope of Data analytics. Some are true, and most are just unsubstantiated marketing. Data analytics is not a new kid in the town, but quite the opposite. What is new is data analytics courses.
I’ll also show you why these courses have come up and will present you with the data for you to decide. So let’s start this exploration.
Top 10 Scope Of Data Analytics
So, I was writing this may 14 years back I would be possibly be giving you very basic scope of data analytics. But within the last three years especially after covid, there has been an eruption of applications.
Home Based Electronics
Yes. I would have never though nor planned to see the use such electronics at home. My first experience was with buying Alexa from amazon, since it solved my major problem which is get music without typing.
Now over the years since the time I bought this machine its use increased multifold. Where in it has learned the following things
- My song preferences
- Sleeping time
- Connects to other devices at home.
- Also reminds me to purchase certain items which might be getting over from amazon.
Recommendation & Search Engines
Has it ever happened that after watching or reading certain article. You reached out to search again, and the whole sentence was already there in the recommended list of google search? Now won’t it be so stressful, if these recommendations didn’t exist? The world without an efficient google search seems to be very frustrating.
So coming to my main point, the scope of data analytics on anything that can be searched. And this is not just going to be or happening in google search but across the board.All kinds of applications which have library of content, will have a recommendation engine.
Fraud Prevention
Again nothing out of the world, but just what I have experienced it myself. My credit card has been blocked more automatically than me instructing it to. And I am not complaining because, it’s much better to be blocked than it getting mis used. However this algorithm has also become better overtime, with reinforcement learning. For example; when I was travelling to Hong Kong in 2023, even if I used the card for uber it would immediately block it. But then when I spoke to customer care and told them to unblock it. Then this signal was the reenforcement learning, which stopped it from blocking me in Hong Kong.
The same principle now you can also see in simple things like you MacBook. When I open my MacBook on a different location, from where I usually open. Then it disables the finger print recognition and tells me to fill the password manually. You might have seen this happening also with Instagram or Facebook accounts.So fraud prevention is one of the scope of data analytics.
Scope of data analytics in Online Marketing
Facebook Advertising
This is a big one, because I saw the pain it costed me for ignoring it. So if you remember from 2023 onwards, there was a big theme on privacy and data.So for example; the main contention was that socialmedia platforms have un interrupted access to personal data of large number of people. Now whether such a question makes sense or not is out for debate. But in my opinion the government ought to stay away from things which they don’t understand. Think about expecting your government to provide an alternative to google search? The solution would never come.
Also considering the data breach which is done by governments themselves illegally, this out roar of Facebook and google just seems like a cover up. But wait that was not my point. How did Facebook handle this issue? Because targeting the right customers took a serious hit, where the Facebook marketers lost seeing results. While spending millions.
While in a small corner, the Zuckerberg fraction was proposing and promoting Conversion API. Now this is where the scope of data analytics becomes amazing. So where the government had a problem with Facebook storing the data of customers. But they didn’t have a problem with the business’s storing the data of their customers. I mean how could you legally tell me not to store data or analyze data of my own customers? So now the storing is done by individual businesses in their servers, and then we push this back to Facebook. But this is where data analytics has become even more accurate than before. Because Now the customer is getting tracked at every stage of sales.
Apple & Facebook War
Now, as all of this was not enough. We also have to deal with the catfights between Tim Cook and Zuckerberg. Where apple now keeps updating their operating system to attack Facebook. For example in 2021, apple OS update forced the developers to ask for tracking permissions. So you see that scope of data analytics is so important and precious to everyone that they can go on an all out war on it. In my humble opinion what apple seems to be propagating is very populist and driven by their marketing theme “Privacy”. But marketing cannot happen unless data is used and it’s much better to see ads which are relevant to me. Isn’t that the case with even organic content?, you see organic content which is relevant to you. And how did it become relevant? By analysing your behaviour.
Medicine & Drug Development
Here again, what we are trying to do is to take lots of actual patients’ data. Also, in the process, identifying which chemical works on what kind of disease trait. Combined with whether a patient will react positively to the medicine. Instead of doing this life on actual patients, we could simulate a drug on a computer. In the process, saving a lot of time.
So, I hope you are getting the point here. We solve problems now more efficiently by using data. That is also possible because we now actually have data.
Risk Management
Another scope of data analytics is financial risk management. Remember the movie, margin call? Where this analyst manually figures out the exposure of the bank into MBS and CDS’s. Now what this analyst did in finding out the limits and sounding the alarm. Today this is done using data analytics. And there are programs and systems which are developed which does this on a firm wide basis.
Scope of Data Analytics in Sales
Yes you heard it right and I am not just saying this is an academic concept but we use it ourselves. The scope of data analytics is so immense in sales that a customer relationship management system, can actually save your time prospecting. For example with the CRM that I use there is sales prediction model called as ZIA. Now this is absolutely uncoded drag and drop system. We enabled this 3 to 4 years back. Intilly the model was inaccurate but today when I see all my converted clients, I am sure to find that the zip prediction was positive.
Is Data Scientist a Glorified Coder?
Believe it or not, I wouldn’t wholly disagree with the notion. See for yourself below; this is a job description for a data scientist in the Pharma sector.
The pharma company doesn’t do the data analytics but outsources to companies like these to get the job done. So if I asked you a question, Is the pharma scientist influential or the data scientist? Then what would be your answer?
In a similar way, is a company which develops and uses software more critical or an IT services company? I’ll leave that answer to you.
The Real Start in Data Science- The Truth
Having a little background on how the data science industry works, don’t get all pumped up. A chef he doesn’t start his career as a chef but as an assistant who has to cut a hundred kgs of onion daily. Also, in data science, you don’t start your career with big projects where you test models but the onion, in this case, is (Just structuring data).
I don’t want to say anything more; look at the amount of time spent on “Cleaning & Organising data”. While building the actual algorithm is just 7%. So, 80% of the time, a data science team ensures the data is there. Now, do you think you need more data cleaners and organisers or data scientists? I could comfortably assume that we need more data organisers, and that’s where the jobs are.
The sad truth, though, is that freshers expect the 7% glorious work and most likely quit the industry. Similarly, most of you would be fascinated with what the data scientist earns but leave the salary earned by the cleaners.
Here is a job description for a data analyst whose job is to clean.
The Real Salary in Data Science
Now, I know those big salaries are given by courses online and offline. Also, the ultimate tagline, which makes me laugh, is “Data science is the sexiest Job of the century”.
Really? What’s so sexy about it?
The question to ask is, how are these salaries any different compared to an IT Professional or finance professional?
So, to conclude, there is nothing different about salaries on an average level in any of the industries. Unless you are some genius, who gets hired for his algorithm creation by google, Facebook or linked in. Just like any other field where outliers exist.
The Real Education Required in Data science, or is it a hoax?
The last myth to break, and then I am gone. Do you need a fancy degree or a course which costs almost as expensive as a home loan down payment?
To break the myth again, the answer is no.
Let’s look at some actual data again on how companies hire and what they require.
To conclude the above data, as a data scientist, you should know how to. No matter what education you do, the main deciding factor is experience. Look at the MBA from the top tier with 0-3 years experience; he earns around 10-12 Lacs. Similarly, look at a non-tier 1 MBA with 3-6 years of experience who ends up making the same salary.
Also, an interesting observation is all types of education with more than 12 years of experience earn above 30 lacs.
The Real Skills Required( Not a course)
As a data science entrant, no one course can help. For a straightforward reason, data understanding requires much more than a data science course. First things first, let’s start with some data.
Expanding Horizons with Data Analytics Tools
The advent of sophisticated data analytics tools has revolutionized the field, making it accessible to a wider range of professionals. These tools enable data analytics professionals to handle large volumes of data and perform real-time analysis, significantly improving decision-making processes. Applications of data analytics now span across various industries, from business analytics to social media, highlighting its growing importance in the digital age.
Programming
You have to learn to code, which language? Well, for now, python or maybe R. However, you must keep learning new languages as they come and become famous in this field. However, learning python and learning python for data science are two different things.
You need to learn python for data science and be able to do that easily. Just like a language, it’s not fun when you struggle to pronounce the words.
Linear Algebra or mathematics
All the algorithms are readily available to deploy in python. Seldom can people understand how that algorithm works. So take up a maths book or course which digs deep inside mathematics.
Basic Machine Learning
Please don’t go overboard with machine learning algorithms; you will hardly use them. However, have a basic understanding of actually using it with cases.
Problem Identification and Solution
Practice with cases on identifying newer problems and, first, without coding them solve them on paper. The more you practice this, the more you become better.
Conclusion
You should not spend more than INR 5000 or $100 to train for these skills, no matter what education you come from. The rest needs to be learned while you earn.
