Graduated with my MBA, walking in December. I want to go into BIG DATA

I think you should try to bring back BIG DADA

 

First off, congratulations on finishing your mba.

Secondly, to be completely frank with you, a big subset of data science might be out of reach for you currently as it is reserved for people who have a graduate level education in math, physics, statistics, or computer science. Or (in rare cases) alternatively those who have a ton of hands on experience already in the domain. These people usually tend to be programmers though.

That being said, there are still related jobs for people with your background.

The question for you is: what do you want to do?

“Big data” is a blanket term encompassing a variety of roles. You could for example go for a role like: data analyst, data visualization (tableau/power BI/ etc...), business intelligence, etc...

 

Cryptos bruh.

 

Look for operations or production analyst positions in the O&G/E&P field. A lot of these positions are becoming more and more data driven. Also, learn SQL, Python, and whatever else it is that data people use.

E&P companies capture a lot of data that they don’t have the time or resources to analyze and use. I think there will be a lot of opportunity in this arena soon.

 

Dang, woulda been so much cooler if you had said it was from Devry.

Either way, congrats on your major accomplishment! From your not so major university.

Spoiler

http://bbs.clutchfans.net/index.php?threads/i-got-accepted-to-devry-university.189075/

 

Here's my thing. Learning all these things aimlessly will be pointless. Sure, you could go out and learn python, but why? Because the Job description says so? That's a bad reason.

Data Science is split into a few different categories. I'll give you a breakdown:

Data Scientists: These guys are the ones using Machine Learning, Deep Learning, and advanced statistics to do all sorts of complicated analysis (imagine what most people think that Morey's team does). These are the ones I mentioned who generally have one or more advanced degrees in Math, Statistics, Computer Science, or Physics. You need to have A LOT of knowledge to do this.

Data Engineers: They're the ones who handle the "BIG DATA" database type stuff (ETL, data warehousing, and some modeling) involving Hadoop, Hive, Pig, Spark, Cassandra, etc... These are almost always programmers. For example: Hadoop itself is based on this concept of map reduce. Most people don't even know what that is unless they're a programmer. Data Engineers often time incorporate things like Amazon Web Services and Google Cloud into the company's data pipeline. I'd argue that you need traditional programming skills such as Java, C++, as well as python (maybe scala) and a knowledge of databases, along with both SQL (hive is pretty much SQL) and NoSQL (such as MongoDB).

Data Analysts: This is what I think someone from your background (business) would be best suited for. Why? Well because it is the least dependent on hardcore math or programming knowledge. You still do analytics. Even sometimes "predictive analytics." But it's at a much less intense level and frankly a good way to break into the industry. You need to be very good at Excel/VBA and SQL. You need to be really good at data visualization in things like Tableau and PowerBI. Companies have a hard on for those two. Furthermore, learning R or SAS if possible (Industry still loves SAS but it's not free so it's harder to learn) would probably give you a leg up, but it's less necessary than the other things I mentioned already. Some Data Analyst job titles are: data analyst, business analyst, data visualization, business intelligence, business data analyst.


Anyway, my main point is that don't just go out and try to learn things for the sake of having them to list on your resume. You'll find that ends up being a huge waste of time. Learn tangible skills for specific purposes. Get really good at Excel (like actually good, not "I did regression in excel once for a finance class so now i'm listing proficient at excel under the technologies section of my resume"), SQL, and visualization platforms. If you want to be in the industry it's imperative to know those.

 

This is perfect and I was about to post something similar. A couple of notes:

Data Scientists have a triumvirate of knowledge, which makes good ones EXTREMELY rare.

1. Some kind of coding skillset: usually python, R, or SQL (or all three). SQL skills are becoming more relevant as more and more appliances have SQL on Hadoop (like Vertica)
2. Statistical Analysis: the level of statistical analysis is often overblown. Many companies want people with advanced degrees, but really, having intermediate level statistics will usually do it. Being able to read and interpret Monte Carlo type stuff. The super advanced stuff is being done more and more by the programs and packages sitting on top of the appliance, so being able to interpret is the key.
3. here is the big one, and why some many Big Data projects fail: Subject Matter Expertise. That's right. Being a true data scientist you have to UNDERSTAND the business you're in. If you work for an Oil and Gas company as a data scientist, and you do a bunch of correlation data to show something...being able to translate to actual business value is hard. Example: Palantir is a Data Science/Big Data company that was born out of the federal government and the CIA chasing down threats to the USA. They got REALLY good at looking at mass amounts of data, finding correlations, and being able to stop bad things from happening. Basically they could track down terrorists really well. The company has commercialized and I know if three projects in the energy industry they've failed spectacularly at because they don't have any expertise. They don't know anything about spudding wells, or operating a field, or anything.

If you really want to work in Big Data (again, that's like saying you want to work as an engineer...it means many different things) I'd look at a few options.

1. Take some basic data modeling courses. Understand how to create and read Conceptual and Logical models. Understand how these relate to the business processes.
2. Work in a job that exposes you a lot to the business you are working in. Business Analysts are a great place to start. People that work in a business function, but closely work with IT to deliver things like reporting, analytics, or even system design. This helps you understand the actual business and how those requirements affect the underlying applications and systems.
3. Understand and learn enterprise architecture. How do the overall platforms in my enterprise connect, and using number 1 and 2, how does the data look logically, and how does the data affect my business.
4. Learn your stats and coding along the way.
5. Boom Big Data.

Also along the way: be involved in your entrprises' data stewardship council. If one doesn't exist, propose to start and facilitate one. This should be business driven and IT facilitated. Understand concepts like Master Data Management, the difference between BI and Analytics, the rate of change of data and how different data is treated differently architecturally. The successful people in Big Data (or any Data Management function for that matter) are the ones that are well versed in the business side.

 

You duchamp of this thread bro.

 

Great information here. I am hoping to dive deeper into this as well so the information provided here has been appreciated

 

I started out in analytics. I think someone of your background will be well suited there. You can learn SQL, Python, and Excel fairly easily on the job. You need to have a strategic sense of how to attack optimization problems and a willingness to learn the technical skills. Happy to answer any questions you have on this.

 

Congrats breh. Welcome the club

 

Congrats friend

 

Checkout Microsoft's free training (and degree program through edX) at https://academy.microsoft.com.

Big Data - https://academy.microsoft.com/en-us/professional-program/tracks/big-data/

Data Science - https://academy.microsoft.com/en-us/professional-program/tracks/data-science/

AI - https://academy.microsoft.com/en-us/professional-program/tracks/artificial-intelligence/

I'm about half way through the Data Science track and loving it. Most of the tracks have various routes you can take, like Python vs. R or Excel vs Power BI. If you pay $99 to edX for each course verification you can get an actual degree when completed, otherwise you can audit all of the courses and each degree plan for free.

All courses are work at your own pace, and start and end every quarter (so four a year). If you don't finish one you signed up for, it isn't a big deal. You just resign up the next quarter.

NOTE: They have far more degree plans and tracks available and they continue to add more - https://academy.microsoft.com/en-us/professional-program/tracks/

 

Learn SAP

 

That's a very broad statement. Learn SAP functionality? Learn SAP HANA design? Learn SAP coding? Learn SAP architecture? Which version? Which module?