Why lifelong learning is critical in data science


I have a mantra that I try to follow: “Always be ready for the next job opportunity”. This does not mean I’m looking for a new job — quite the reverse, in fact. This is my excuse to keep learning new stuff. The dilemma is that I’m sometimes too busy with my current projects, and it can be hard to make time to be a #LifeLearner.

Once we were all ‘just’ SAS programmers who had to know about ‘everything’, and now everyone needs to be a data scientist. Or do they? I think there is a distinction between those who need to be Jacks-of-all-trades, both technical and business, and others who drift into self-service use of applications. Still others will become specialists: Administrators, developers or statistical modelers, for example. The level of specialist knowledge is increasing and becoming more challenging as solutions have more and more impact.

How do you decide what to learn?

I think it is important not to spend too much time evaluating new topics, before deciding whether it is relevant to spend time on them. If after two minutes, the subject sounds interesting, then why not send your manager an email asking for time and money to do the training? Yes, of course time and money are limited, but sometimes we need to shoehorn learning into small gaps in between other work or find other ways to learn.

Education, conferences and knowledge-sharing with peers can change our understanding of how we work. You could also take a simple online test, for example, challenge yourself with one of the widely-available knowledge and skills practice tests or test your skills with a free Self-Assessment Test. Perhaps completing one of these tests will help you answer the question “Where should I start?”.

Wealth of opportunities

Today we have so many different options for learning that we can pick and choose formats. The hard part is deciding what to learn, how to learn it and when. And ‘when’ does not only mean freeing up time in your calendar, but deciding whether you should learn before you need the skill, and risk it being wasted because requirements change, or wait until it’s almost too late, because the project starts tomorrow.

The hard part is deciding what to learn, how to learn it and when #LifeLearner #SASNordicFANS Click To Tweet

Learning resources

You need to find the tools to help you learn at your preferred pace and format. For example, for #SASNordicFANS , we have compiled a wide range of learning resources. These include:

  • Classroom training – it is thorough and there is always someone on hand to answer questions
  • Live Web Classes – a bit like traditional classroom training, but virtual
  • Webinars – few opportunities for interaction, but can be a good introduction to a topic
  • Communities – great for questions or to browse to discover new ways to work or to solve problems
  • SAS User forums, both local and global – fantastic resources to see how others are handling business problems and finding clever ways to solve problems, together with speakers’ papers in pdf form to browse
  • Local Networking groups – topic related meeting with peers discussing challenges and sharing solutions
  • How-to tutorials via a video library, and e-learning with small snippets about different topics to get you started.
  • Newsletters – often contain useful summaries and links to resources for self-study
  • Blogs – Views and opinions from around the world
  • SAS Books – either as e-book or on paper

This list is more or less ordered in interaction/time allocation, and the hashtag #SASNordicFANS can help you to search for local Nordic content under all these options.

In December, we will be running the SAS Learning Conference, with short sessions, more topics, and lots of hands-on opportunities. It is a great way to get started with your #lifelearning.

Always be ready for the “next job opportunity”

If you are preparing for the next job opportunity, it might also be a good idea to document your skills, for example, by getting some certification, which also helps you to self-evaluate. Your next step could be the more formal Data Science Academy, or you might use a formal Training Needs Analysis to help identify a suitable learning path or career opportunities.

Training and education will help you to develop your capabilities, but it is important to remember that your day-to-day work will give you the experience that will enable you to address challenges with confidence. You may also find it helpful to have a mentor to review and evaluate your work, and help you move forwards.

Or perhaps you just need to book a regular slot with Google once a week to browse through the possibilities. Once a month, you could book the whole day! Close the door, mute the phone and let others know your development is important to you.

Most of all, never stop learning.


About Author

Gert Nissen

"Inspiring #SASNordicFANS to maximize their value from SAS Software" When working with data in many shapes as an SAS programmer since 1994 I have from many projects got great insights into the many ways data and SAS are used to support many different processes and decisions – From acquiring data and making sure the data quality will not be an issue for the analytics and reporting. When you are working with data not everything is perfect – especially not the time you are allocated to do the job, therefore you need tools and skills that accelerate this process. Some solutions will have a very short lifetime being born as an ad hoc question, while others might by critical to the organization in real-time decisions used by Customers. What a great job working with all these possibilities trying to expand usage and value of SAS and data!

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