“Semantic-free” is the future of Business Intelligence by Andrew Taft via @FlexItAnalytics

 Metrics and universal semantic layers enable semantic-free BI.

I found this very interesting and worth reading so you can think about the future.

8 Essential Python Techniques for Data Engineers and Analysts (with code samples) by @camwarrenm via @TDataScience

These are the Python code snippets he re-uses the most.

Something to bookmark for sure. I'm sure we all have a basic toolset of code scripts in various languages that we use and edit every time we need to do something.

A Guide to 14 Different Data Science Jobs by Nate Rosidi via @kdnuggets

The field of data science is growing into one that features a variety of job titles This guide reviews different positions available for you to consider if you have a data science background.

Definitely worth a read as there are some great jobs out there that are NOT a data scientist but probably suit you and your skillset much better. I think I am closer to a data engineer a lot of the time, but not exclusively.

Data science isn’t your only career option by Natassha Selvaraj via @TDataScience

A breakdown of high paying data related careers in 2021.

I think many of us can think about our own jobs and realise that we actually fit into one of the jobs outlined at a high level by Natassha - probably a Data Engineer for me (although I was mostly known as a Data Architect). Don't be blinkered into thinking you need the sexy Data Scientist job title.

Try these more detailed definitions: 

Data Engineer

Data Architect

Data Scientist

Machine Learning Engineer

9 Free Programming Courses by Harvard, MIT, IBM, Google, and Microsoft by/via @dottedSquirrel

 And get optionally certified for the price of your groceries. 

This is definitely something worth investigating if this is the career path you want to take.

Organizations gaining new benefits by automating data engineering by Jelani Harper via @infomgmt

A number of advancements have now decreased data preparation time while increasing the time available for exploration and applications.

I think there are several possible tools that enable users to do their own querying and this article talks about the one that the author is most familiar with.  Some organisations use Tableau, Pentaho or Power BI. I'm sure there are others I have not listed.

Don't Underestimate Your Data Engineer by @IE_James via @iegroup

The flood of data-related roles unleashed in recent years has the potential to cause untold confusion, particularly for senior executives inexperienced in the field.

Nice to have an article about an often overlooked role which is just as vital as a data scientist.

The Difference between Data Scientists, Data Engineers, Statisticians, and Software Engineers by @ronald_vanloon via @Datafloq

What is the difference between the different big data jobs, as it can be confusing and complicated to find out.

Interesting definitions.  I have noticed several things - first companies do not work to the same definition so a data scientist in one is a data engineer in another, and the second is that many people do hybrid roles that comprise of parts of each of these roles. Either way it is confusing to compare and contrast across organisations.

What is a productive data engineering team? by @jessetanderson via @OReillyMedia

Jesse Anderson explains how to merge the gaps between data science and engineering and what each side can learn from the other.

I love this article and the diagram Figure 2 in the article is something I think we all can learn from and use to analyse our own organisation.

5 Career Paths in Big Data and Data Science, Explained by Matthew Mayo via @kdnuggets

Sexiest job... massive shortage... blah blah blah. Are you looking to get a real handle on the career paths available in "Data Science" and "Big Data?" Read this article for insight on where to look to sharpen the required entry-level skills.

I LOVE this article, it also have some great articles off the links in it.  I recommend reading this so that you can work out which role you are more like and what you need to do in order to improve your skills.

The Rise of the Data Engineer by @mistercrunch via @freeCodeCamp

This great article shows how the transition from business intelligence engineer to data engineer. This is a great article and makes so much sense.  Definitely a must read article.

On a personal note I feel I am probably closer to a data engineer then to a data scientist.

Data Engineers vs. Data Scientists: The Difference According to LinkedIn Data by @jakestein via @stitch_data

In 2012, Harvard Business Review named data scientist the "sexiest job of the 21st century." In 2017, it is expected for demand to continue for data scientists, but the talent gap will be framed in terms of data engineers (more than data scientists).

I found this really interesting. From my own point of view I'm in the middle of the two roles with certain skills missing which means I can use this as a indicator of what skills I need to gain in order to go in either direction - something that you can do too.