Business Analyst, Big Data Specialist, Data Mining Engineer, Data Scientist, Data Engineer.
Why is this field so prone to hype and repeating the same things with a new coat of paint. I mean what ever happened to OLAP, data cubes, Big Data, and whatever other super big next thing that has happened in the past 2 decades?
Methinks the problem with Business Intelligence solving problems is the firdt part of the term and not the second.
I think the real interesting point is slapping the title of engineer/scientiest on to anything and everything regardless of the accreditation actual handed out. soon coming up.."cafeteria engineer", "janitorial engineer"...
The difference of course being that other types of engineers have to take a PE. The idea of requiring a PE to have that title is protectionism no different than limiting the number of graduating doctors to keep salaries high. No one will ask a software engineer to build a bridge - relax. Your protection racket is safe. Software engineer is a title conferred on someone who builds systems. It is fitting. And, if we're being honest, the average "job threat level" of a so-called "real" engineer is about the same as a software engineer these days anyway. With the exception of some niche jobs every engineer I know is just a CADIA/SW/etc jocky and the real work is gatekept by greybeards.
No one will call someone a cafeteria engineer or janitorial engineer. The premise is ridiculous. There is a title called "operations engineer" that uses math to optimize processes. Does this one bother you too?
> Why is this field so prone to hype and repeating the same things with a new coat of paint.
Money and Marketing. It's no different from how Hadoop was a big deal around 2010, or how Functional Programming became the new thing from 2015 onwards.
Personally I think this is a failure of regulatory agencies.
I dunno, I have to first put my data somewhere though. But where.. In a warehouse? Silo? Data lake? Lake house? (I really despise that last one, who could coin that phase with a straight face..)
Data warehouse: bundles compute & storage and comes at a comparatively high price point. Great option for certain workflows. Not as great for scaling & non-SQL workflows.
Data lake: typically refers to Parquet files / CSV files in some storage system (cloud or HDFS). Data lakes are better for non-SQL workflows compared to data warehouses, but have a number of disadvantages.
Lakehouse storage formats: Based on OSS files and solve a number of data lake limitations. Options are Delta Lake, Iceberg, and Hudi. Lakehouse storage formats offer a ton of advantages and basically no downsides compared to Parquet tables for example.
Can you explain why do you find the above explanation amusing? I honestly don't see the absurdity of it, although, my livelihood may depend on me not seeing it :)
That's why my company is looking for investors who are interested in being at the forefront of the data revolution, using our data rowboat that will allow you to proactively leverage your data synergies to break down organizational data silos and use analytics to address your core competencies in order to leverage a strategic advantage to become the platform of choice in a holistic environment.
Tell me if this sounds familiar, your company has tons of data but it is spread out all over the place and you can't seem to get good info, you end up hounding engineers to get your reports and provide you information so you can look like you are making data driven decisions. Maybe you've implemented a data lake but now have no idea how to use it. We've got you covered with our patent pending data rowboat solution.
This will allow you to impressive everyone else in the mid level staff meetings by allowing you to say you are doing something around the "data revolution" in your org. The best part is that every implementation will come with a team of our in house consultants that will allow the project to drag on forever so that you always have something to report on in staff meetings and make you look good to your higher ups.
Now you may be an engineer looking to revolutionize your career and get involved in the next step of the glorious October data revolution. Well we've got you covered for a very reasonable price you can enroll in our "data rowboat boot camp", where you will spend hours locked in a room where someone who barely speaks English will read documentation to you.
But act quick otherwise you'll end up as one of the data kulaks as the new data rowboat revolution proceeds into a glorious future with our 5 year plan.
Brb, running to trademark every nautical data metaphor I can get my hands on.
What happens when your data rowboat runs ashore? Introducing Data Tugboat™, your single pane of glass solution for shoring up undocumented ETLs and reeling your data lineage safely into harbor.
Sir, I'm sorry, but a rowboat just won't scale, my needs are too vast. What I'm proposing is the next level of data extraction. You've heard of data mining? Well meet the aquatic equivalent, the Data Trawler. To find out more, contact our solution consultants today!
Why is this field so prone to hype and repeating the same things with a new coat of paint. I mean what ever happened to OLAP, data cubes, Big Data, and whatever other super big next thing that has happened in the past 2 decades?
Methinks the problem with Business Intelligence solving problems is the firdt part of the term and not the second.