Summary of ENEB Masters in Big Data and Business Intelligence

[Pinko64]

@Anyone who did the Master in Big Data and Business Intelligence from ENEB

Can anyone summarize what they have learned pursuing the degree, i.e. which tools, processes (SQL for example)?

[Kalas]

On the tech side of things it is VERY light. You'll get introduced to basic SQL queries, a little data analysis, community management (i.e. being the douche corporate stooge on a Discord server, forum, etc.), data cleaning, using customers' data to more effectively extract money from them in the future, standing out on the web, ETL, stuff like that. If you come in with no knowledge you'll learn a little bit about each topic not covered in the MBA, but not enough to be employable in any of the technical areas it touches. As with all ENEB programs, how much you get out of it is determined by how much effort you put into finding additional resources to fill in the gaps. Technical know-how is essentially non-existent.

In a way it's similar to Eastern University's Data Science MS. It's accessible so people with no prior knowledge can complete it, but you're not going to have more detailed knowledge that would come from a program that assumes you already know the basics. As I said in the big ENEB thread, it falls into a weird middle ground where none of the business stuff goes into enough depth for it to be a business degree and the technical stuff isn't technical enough for it to pass for a tech degree. You won't be worse off for having it, but you'd have to be beyond delusional to think it would get you into a data career.

[Pinko64]

On the tech side of things it is VERY light. You'll get introduced to basic SQL queries, a little data analysis, community management (i.e. being the douche corporate stooge on a Discord server, forum, etc.), data cleaning, using customers' data to more effectively extract money from them in the future, standing out on the web, ETL, stuff like that. If you come in with no knowledge you'll learn a little bit about each topic not covered in the MBA, but not enough to be employable in any of the technical areas it touches. As with all ENEB programs, how much you get out of it is determined by how much effort you put into finding additional resources to fill in the gaps. Technical know-how is essentially non-existent.

In a way it's similar to Eastern University's Data Science MS. It's accessible so people with no prior knowledge can complete it, but you're not going to have more detailed knowledge that would come from a program that assumes you already know the basics. As I said in the big ENEB thread, it falls into a weird middle ground where none of the business stuff goes into enough depth for it to be a business degree and the technical stuff isn't technical enough for it to pass for a tech degree. You won't be worse off for having it, but you'd have to be beyond delusional to think it would get into a data career.

Not even Python/R basics or even Data visualization ? That's a shame

[bjcheung77]

Basically, each and every one of the ENEB options are geared towards the "busines, leadership, management, strategy" side of things, you're only introduced to "subject matter" and not really taught anything else in those Masters/MBA. You really need to decide if it's for you or not, I use it for filling in knowledge or learning gaps, as well as to retain/review information. You most likely either have lots of experience already, or you can gain that experience by supplementing extra certs such as the ones on Coursera/EDX or other cheap or freebies on the WIKI...

[housecat]

Basically, each and every one of the ENEB options are geared towards the "busines, leadership, management, strategy" side of things, you're only introduced to "subject matter" and not really taught anything else in those Masters/MBA.  You really need to decide if it's for you or not, I use it for filling in knowledge or learning gaps, as well as to retain/review information.  You most likely either have lots of experience already, or you can gain that experience by supplementing extra certs such as the ones on Coursera/EDX or other cheap or freebies on the WIKI...

I second this, but from my other experience, I would say by the time you get to a masters in data anything you already have training in at least SQL, Python, perhaps AI techniques, and running various standard datasets for analysis. The quality of third party courses in these areas is actually quite refined these days, making Coursera and Udemy solid options if you don't like what is on YouTube. There may even be stuff on StackSkills from stacksocial. Another one that has a special place for me is Eduonix, the most economical way with them is to buy their lifetime deal in their E-mail marketing, then you always have access to everything whenever you want it for later.

On YouTube a popular ones are Programming with Mosh, freecodecamp, Bro Code, Caleb Curry, Naresh, CPP Explorer, and Derek Banas. Importantly though, not one of these are complete and some are absurdly long, so you need to mix and match. Derek's been going for years, and as he recommends, pause the videos when you need to, he doesn't really stop and smell the roses. When learning your first language, ALWAYS GO FOR COMPLETENESS. Do not mess around. It gives you a full on understanding of what programming actually is and isn't and allows you to build a modern base of understanding and everything else becomes a lot more trivial, because the foundation is there and you're like oh a dictionary does this, and a linked-list does that, is stored in memory this way, it will perform this way or that way on linux versus windows, can be optimised this way or that way, takes O time, blah blah blah, you are a champ. I unfortunately did not take C++ as my first language, but if I had to do anything like this again, starting with C++ and not C# or C or pascal or Delphi, or Basic, or (insert language here), it would have been a lot better. Oh also never mind about Assembler for the beginning language, I've heard the logic behind this, but practically today, C++ is the middle sweet spot of everything.
 
As far as tools go, yeah "okay do R" but don't start with R, you'll loose your mind. DO NOT START WITH R.
If you have TIME become a full on developer with AI with Data curriculum and you'll be an absolute unstoppable beast, learn C++ (Really well) --> SQL --> C (much easier after learning C++) --> C# (much easier after learning C++/C) --> HTML/CSS (Trivial) --> PHP --> Python 3 (NOT version 2) for data analysis which includes at least matplotlib, numpy + pandas, seaborn, tensorflow+keras, scipy, beautifulsoup, pytorch (for fun), and others fro fun.
The story here is if you want to be a developer + AI/Data person learn C++. I know, I know, people are impatient but learning C++ and not other languages first essentially make you unstoppable and can learn other languages in a few hours and expert in a few weeks after learning C++ because everything else after C++ is syntactical sugars. Google Go and RUST are in these categories. C++ is and old but continually updated language (along with C) and have modern levels the compilers can be put into no problem. Learning C++ will also introduce you to programmatic user interfaces (GUIs) which helps with creating excellent GUIs in Python, but creates an amazing foundation in Python for what happens under the hood in Python. Toss in Linux for good measure, desktop and terminal use. Look after C++, you can easily addon in a few days of study, GO, RUST, C, etc. And every programmer must also learn SQL, handling clients and their customers, interviewing, overcoming objections, marketing, and all the business end, but that's the difference between a programmer and a software developer.

Learn Project Management as a supplement to your other instructions so you know how to manage a project manager, but never do this as a profession unless you do it with authority and technical competency, or no one above or below you in the org chart will take you seriously.
You will hear the techs groan as soon as they see you and say "...not now, I have to do my own job, we are behind schedule..." or literally book off 3 hours of time to go over everything with you in a meeting then use that as a cudgel when management asks questions. If you have an impeccable personality, can manage people with a range of social acuity, and timing, along with your ingrained technological prowess, you can be a successful PM. Otherwise your title better be Operations Manager who is conducting PM duties. A bare qualified PM will be openly mocked mercilessly. Quite frankly when I saw it, I was like yep that was qualified, because of the sheer time wasting and client hanging over their head and other obligations.

Learn Tableau, and everything BI from Microsoft. I swear everything from Microsoft in their offerings is a golden goose in data and automation, you can never go wrong with Microsoft. Very beautiful and  

I cannot recommend learning and mastering SQL and its related concepts such as normalisation, database selection, optimisation, applications, and triggers enough. Jobs in North America pay AMAZINGLY WELL for those well versed in SQL, even at entry level. Also some of these jobs are unionised so you're further protected by unions. Job security is amazing in SQL-centric jobs.

I went whole-hog and went to Centennial College in Toronto, Canada and did their 3-year Software Engineering Technology - Artificial Intelligence Program which is neither cheap nor quick but it was quite detailed. Too bad ENEB doesn't have the Master in Marketing and Analytics in English (I checked out the lists on eneb.es versus eneb.com.)

So now I really rough this out in this post, look at the curriculums in the "E-Degrees" curriculums on Eduonix, the E-Degrees which correspond to AI and Machine Learning really display what I'm talking about. Their direct competitor is Edureaka who also does good work but is a lot more expensive, and I am a price-sensitive person. The Eduonix covers a lot of what I did at Centennial College academically. Their E-mail marketing list has some hot deals, I used to but the E-Degrees indepentantly, but then I was like wth I'll go for the all-in package and at the time it was 149USD, one-time fee. They also had an interest-free payment plan at the time but I was like I'm either all-in or nothing.

The highest quality of education is in-person and over-priced, but costs the most in resources (time and resources) so YouTube/Eduonix with a portfolio and ENEB Degree is a good mix.

Being good with Data and acceptable to the good jobs, you need to show mastery of some stats, story telling, business, and how to use the tools to analyse data sets.

Sorry this reply post is a hot mess, but I wanted to get my thoughts down and tbh I read a lot more forum posts than I ever reply to. Hope this helps!