Career has been a constant struggle

[Career Compromise]

I've used Python, R and Matlab. I've also used Tableau and Power BI.

Well you can do "proper" programming in VBA/VB but most places don't. You can access it through other "proper" frameworks.
The issue is, even though MS still support it, they stopped development a long time ago. Even though there is nothing really to replace it.
The other issue is any experience in it, is no longer valued, hasn't been valued for a long time. I still think its powerful and I think many places will struggle to replace it. But that ship has sailed.

Completely agree. The reason I stated for wanting SQL training in the first place was because it was a desirable skill for the job, but the real reason was because it was a requirement for many other jobs and it had become apparent by then that VBA wasn't a skill that was valued. The frustration I had in the VBA days was knowing VBA skills won't get me another job.

What gets me overall is that when I've had a choice in what direction I take my number one consideration is what will make me more employable but it hasn't worked.

 

[NickK]

I've used Python, R and Matlab. I've also used Tableau and Power BI.


Completely agree. The reason I stated for wanting SQL training in the first place was because it was a desirable skill for the job, but the real reason was because it was a requirement for many other jobs and it had become apparent by then that VBA wasn't a skill that was valued. The frustration I had in the VBA days was knowing VBA skills won't get me another job.

What gets me overall is that when I've had a choice in what direction I take my number one consideration is what will make me more employable but it hasn't worked.

Unfortunately technology moves fast and companies prefer to hire in new staff with experience rather than cross train existing staff.

I did a 4 year software engineering degree, including set theory and formal methods. I also specialised in parallel & distributed systems and databases which is why I studied numerical computation and have a maths/set slant to the way I see languages/systems.

I started in software -> 6502/ARMassembler/BASIC -> Pascal/Fortran77 (uni) -> C/C++/Pro*C/SQL (work) -> Java (work) -> Objective C/OpenCL/C++/Python/R (work/home).

I can see Python is great for hacking up something, the reality is it's not great. I'm considering learning Go but at the moment the focus is on find a new job.

 

[HangTime]

You're Pret example reflects what I'd like to do in retail i.e. try to have enough sandwiches in stock for people to buy but not too many that they have to get thrown away.

Basically you are interested in supply chain. Have a look at oil&gas companies, the likes of BP have a massive need for insight on their supply chain at the moment. In fact generally I would imagine the market for supply chain analysis has grown in the past year or two in a lot of industries.

As you have highlighted however, you have to be a bit wary of what the job entails. Some organisations aren't really structured to empower analysts to provide insight, they are essentially just there to mash data together and then have a business SME interpret and suggestion actions based on the data. I've seen it first hand where a data scientist (who seemed pretty switched on in the short time I as there) was itching to really get stuck in to some datasets and surface interesting patterns etc was basically reduced to churning out spreadsheets to meet the baseline hygiene factors of having numbers to look at. It's maybe an anachronism handed down from where 'data provisioning' used to be seen as this completely segregated thing sat in IT with "actionable insights" being something handled by completely different sets of people. I think the most agile organisations will find ways to harness unicorn skillsets whereby they can have skilled analysts both leverage modern technology but also generate useful insight and keep those people interested and engaged through them being a business partner, rather than just a 'supplier'.

 

[mattx2]

Have you looked into no code/low code app development?

I work for a consulting firm and we are seeing a lot of interest in companies adding these to their software stack. In essence these no code platforms often replace bits of excel vba/python that was hacked to together to make a report or perform some workflow

 

[Bassmansam]

I’m learning vba at my current job. I can’t see businesses fully ditching excel so whats wrong with it?

 

[OspreyO]

That seems un

I’m learning vba at my current job. I can’t see businesses fully ditching excel so whats wrong with it?

It's old tech. It's not trendy. Programmers don't want to do anything that not cutting edge as you don't get paid as much.

It has technical limitations as it's run solely on the client, it can't be run or distributed through the web. There are security issues. Its single threaded so can't deal with massive datasets. Though I think that's overstated. If you needed to handle massive data you wouldn't be using Office to do it anyway.

On the flip side it's very capable and nothing has been created to replace it. It's simple to manage. You don't need programmers to use it. Though a programmer will be able to do more with it then a power user. But you won't get programmers to touch it usually.

It's still widely used and in demand, but plays less than other tech. But that's kinda moot if you aren't a programmer as you won't get those jobs anyway.

 

[Bassmansam]

That seems un


It's old tech. It's not trendy. Programmers don't want to do anything that not cutting edge as you don't get paid as much.

It has technical limitations as it's run solely on the client, it can't be run or distributed through the web. There are security issues. Its single threaded so can't deal with massive datasets. Though I think that's overstated. If you needed to handle massive data you wouldn't be using Office to do it anyway.

On the flip side it's very capable and nothing has been created to replace it. It's simple to manage. You don't need programmers to use it. Though a programmer will be able to do more with it then a power user. But you won't get programmers to touch it usually.

It's still widely used and in demand, but plays less than other tech. But that's kinda moot if you aren't a programmer as you won't get those jobs anyway.

thanks for explaining. My job is in data analysis so lots of excel including vba now.

I did start learning python in my spare time, got about 1/2 way through a udemy course but stopped when i started this job as its been my first analyst(bit of a stepup in brain usage) job so i wanted to settle in before resuming python. It would be cool if they would let me use it in this job, hope to finish the course by July.

 

[OspreyO]

Have you looked into no code/low code app development?

I work for a consulting firm and we are seeing a lot of interest in companies adding these to their software stack. In essence these no code platforms often replace bits of excel vba/python that was hacked to together to make a report or perform some workflow

Have to say from Ms power apps point of view, they are limited and you basically need to be programmer to build them properly anyway. The permissions are complicated. You end up using a bunch of different tech to do what you can do easily in VBA. But you can't put VBA on the web, cloud. Office 365 etc. Whereas power apps integrate with SharePoint online, teams etc and single sign on.

 

[OspreyO]

thanks for explaining. My job is in data analysis so lots of excel including vba now.

I did start learning python in my spare time, got about 1/2 way through a udemy course but stopped when i started this job as its been my first analyst(bit of a stepup in brain usage) job so i wanted to settle in before resuming python. It would be cool if they would let me use it in this job, hope to finish the course by July.

Might be useful to build something in VBA then replicate it in Python. You'll need Python and some of it's excel library's in your skillset going forward. If you want to say in that space.

 

[Bassmansam]

Might be useful to build something in VBA then replicate it in Python. You'll need Python and some of it's excel library's in your skillset going forward. If you want to say in that space.

Yeah that sounds good, will make a note of that, thanks. Definitely want to stay data analysis going forwards.

 

[OspreyO]

have a look at this:

That's real time processing. But doesn't seem to get into the analytics of it from a data analytics person's pov. I asked the question because I was (following the suggestions on this thread) reading about R and python working with large datasets and people needing different hardware to run it. Something I've noticed with Tableau users at work.

Personally these days I do most of the heavy lifting in the database. But in the past over had to optimize old workflows in access in excel. One time getting a access job that took two weeks to process down to 24hrs. These days I can't think of anything we do that takes longer than about 20 mins at most.

 

[dowie]

I've used Python, R and Matlab. I've also used Tableau and Power BI.

So you've apparently got the degree and you've got relevant skills/job title that is very much in demand right now... You need to work on the interviews - if you're claiming those things on your CV but all your examples are work done in VBA then that perhaps raises questions for a start.

Completely agree. The reason I stated for wanting SQL training in the first place was because it was a desirable skill for the job, but the real reason was because it was a requirement for many other jobs and it had become apparent by then that VBA wasn't a skill that was valued. The frustration I had in the VBA days was knowing VBA skills won't get me another job.

That's completely context-dependent, again it's used in banks etc... Excel isn't going away anytime soon. It's not necessarily useful if you're dealing with large datasets but that isn't necessarily going to be the case at all.

 

[NickK]

That's real time processing. But doesn't seem to get into the analytics of it from a data analytics person's pov. I asked the question because I was (following the suggestions on this thread) reading about R and python working with large datasets and people needing different hardware to run it. Something I've noticed with Tableau users at work.

Personally these days I do most of the heavy lifting in the database. But in the past over had to optimize old workflows in access in excel. One time getting a access job that took two weeks to process down to 24hrs. These days I can't thing of anything we do that takes longer than about 20 mins at most.

Correct - realtime transactions, which correspond to data points. Being the TPM and ITIL service manager for that project I know precisely how, what and who. Some of which I can't/won't discuss for obvious reasons.

Data risk and security means that production data is not available for interactive sessions or extraction. Not to mention regulatory requirements in terms of gaining regulatory and your individual authorisation for processing your data for specific tasks. In that project a data protection breach could illicit fines of $800M, not to mention the subsequent higher impact to the business.

There is processing data and then there is building the processor.

You can anonymise production data sets to a regulatory and legal stand point - this can be transferred outside of production (depending on the local country legals - you may still need authorisation from the user for use of their data to be anonymised).
That is the data set you can use within data science platforms to mine and identify patterns - that pattern is then something that can be built for business value and presented to the regulator/user for authorisation.

Machine learning on production data, subject to regulation and legals, occurs - the output from the machine learning is anonymised. You won't see the machine learning in realtime, nor will you be allowed for the ML identify for action against data without further steps and testing plus risk sign off. The ML needs to be part of a known processing process (regulatory), for explaining to the customer and business what it does (customer/legal) and finally for explaining/recording the problems if it went wrong (risk) for the country CEO delegate signing off.

You build a better processor. Then release that processor into production. Iterate.

You're correct that you're not running R as an interactive session. Reality is that it's never going to happen on personal identifiable production data. However it is used (actually depends on the data size) to mine data but also to test hypothesis to code a higher performance test system for larger data sets.

 

[OspreyO]

I would have assumed that anonymising the data analytics have access to would be normal. Even at our tiny scale we do that.

I think the scale of what you're talking about isn't relatable to anyone who doesn't work in those specific companies.

None of our data analytics people work on real time time data. Real time data is all within the realm of infrastructure,DevOps and developer's.

 

[OspreyO]

It's interesting though. I have a transformation project to do at the moment. I might do it both in VBA and Python myself just for the CV.

 

[NickK]

I would have assumed that anonymising the data analytics have access to would be normal. Even at our tiny scale we do that.

I think the scale of what you're talking about isn't relatable to anyone who doesn't work in those specific companies.

None of our data analytics people work on real time time data. Real time data is all within the realm of infrastructure,DevOps and developer's.

Yup, data anon should be mandatory regardless of size.

Ignoring this size, the need for realtime really driven by uscases - customer experience and risk/competitive reactionary capabilities.

People relate realtime to embedded systems, that used to be true, however through the progression of "internet time" to "Amazon time" to on demand that realtime capability and how fast the organisation can adapt is accelerating. Sure - content delivery may be realtime, viewing figures may be 24hours for the weekly planning reports and content investment steer.

I get your point about the ML/DS analysis for the processor not being realtime. The processor analysing by itself being realtime for things like personalised adverts etc.

 

[OspreyO]

What you talking about is at a scale way out of my league. I suspect the same is true for the OP.

I think if the OP wants to focus on Analytics they should do some qualifications in it. Because you won't just pick it up. It's a very academic discipline.

 

[Career Compromise]

Unfortunately technology moves fast and companies prefer to hire in new staff with experience rather than cross train existing staff.

I did a 4 year software engineering degree, including set theory and formal methods. I also specialised in parallel & distributed systems and databases which is why I studied numerical computation and have a maths/set slant to the way I see languages/systems.

I started in software -> 6502/ARMassembler/BASIC -> Pascal/Fortran77 (uni) -> C/C++/Pro*C/SQL (work) -> Java (work) -> Objective C/OpenCL/C++/Python/R (work/home).

I can see Python is great for hacking up something, the reality is it's not great. I'm considering learning Go but at the moment the focus is on find a new job.

This is another reason why I want to be more focused on data than technology.

Basically you are interested in supply chain. Have a look at oil&gas companies, the likes of BP have a massive need for insight on their supply chain at the moment. In fact generally I would imagine the market for supply chain analysis has grown in the past year or two in a lot of industries.

As you have highlighted however, you have to be a bit wary of what the job entails. Some organisations aren't really structured to empower analysts to provide insight, they are essentially just there to mash data together and then have a business SME interpret and suggestion actions based on the data. I've seen it first hand where a data scientist (who seemed pretty switched on in the short time I as there) was itching to really get stuck in to some datasets and surface interesting patterns etc was basically reduced to churning out spreadsheets to meet the baseline hygiene factors of having numbers to look at. It's maybe an anachronism handed down from where 'data provisioning' used to be seen as this completely segregated thing sat in IT with "actionable insights" being something handled by completely different sets of people. I think the most agile organisations will find ways to harness unicorn skillsets whereby they can have skilled analysts both leverage modern technology but also generate useful insight and keep those people interested and engaged through them being a business partner, rather than just a 'supplier'.

I suppose I am.

Have you looked into no code/low code app development?

I work for a consulting firm and we are seeing a lot of interest in companies adding these to their software stack. In essence these no code platforms often replace bits of excel vba/python that was hacked to together to make a report or perform some workflow

Doesn't sound like the sort of thing I'd want to do.

So you've apparently got the degree and you've got relevant skills/job title that is very much in demand right now... You need to work on the interviews - if you're claiming those things on your CV but all your examples are work done in VBA then that perhaps raises questions for a start.



That's completely context-dependent, again it's used in banks etc... Excel isn't going away anytime soon. It's not necessarily useful if you're dealing with large datasets but that isn't necessarily going to be the case at all.

I get the impression interviewers want to hear about times you were proactive and achieved some sort of result. Unfortunately when I started to use Python etc my job was to do what I was told and most of what I did seemed pointless. A lot of people think I should be able to easily get a job but the reality is the opposite.

 

[dowie]

I get the impression interviewers want to hear about times you were proactive and achieved some sort of result. Unfortunately when I started to use Python etc my job was to do what I was told and most of what I did seemed pointless. A lot of people think I should be able to easily get a job but the reality is the opposite.

Yup you should be able to get a job quite easily, the reality is there is lots of demand for these skills and you've obviously been able to land the interviews but you're failing at that stage.

Have you ever done any kaggle competitions or similar? Have you used any of this stuff in your spare time at all and could stick some side projects on github etc..?

 

[Career Compromise]

Yup you should be able to get a job quite easily, the reality is there is lots of demand for these skills and you've obviously been able to land the interviews but you're failing at that stage.

Have you ever done any kaggle competitions or similar? Have you used any of this stuff in your spare time at all and could stick some side projects on github etc..?

No I don't do anything like that in my spare time. I do some data analysis around sports for my own interest, but nothing too technical and certain no fancy tools get used. Manually trawling through the sports data is part of the fun and some of it is in books.