Anonymous reprint from Quora (career advice)

Occasionally we come across a unique profound perspective that makes one stop and really listen. The following advice is one such as this.

1. Small actions compound: Reputation, career trajectory, and how others perceive you in the workplace can come down to a handful of things/moments that seem inconsequential/small at the time but compound. Random Thought: Redwood trees come from small seeds and time. With every action you're planting small seeds and these seeds can grow into something bigger (sometimes unimaginably bigger) over time. Don't let small basic mistakes sabotage your reputation because it only takes a few small snafus for people to lose confidence/trust in your ability to do more important tasks. Trust is a fragile thing and the sooner people can trust you the faster they'll give you more responsibility. Some Examples: Being on time (always) or early (better); spending an extra 10-15 minutes reviewing your work and catching basic mistakes before your boss does; structuring your work so it's easy for others to understand and leverage (good structure/footnotes/formatting); taking on unpleasant schleps/tasks (volunteer for them; don't complain; do it even when there's no apparent benefit to you)  


2. Rising tide lifts all boats: Fact: You don't become CEO of a multi-billion dollar public company in your 30s based purely on ability/talent. Your career is a boat and it is at the mercy of tides. No matter how talented you are it's a lot harder to break out in a sluggish situation/hierarchy/economy than a go-go environment. Even if you're a superstar at Sluggish Co., your upside trajectory (more often than not) is fractional to what an average/below average employee achieves at Rocket Ship Co. There's a reason Eric Schmidt told Sheryl Sandberg to "Get on a Rocket Ship". I had colleagues accelerate their careers/income/title/responsibility simply because business demand was nose bleed high (go go economy) and they were at the right place at the right time to ride the wave. Contrast that to the 2008 bust where earnings/promotions/careers have been clamped down and people are thankful for having jobs let alone moving up. Yes talent still matters but I think people generally overweight individual talent and underweight economics when evaluating/explaining their career successes. Sheryl Sandberg Quote: When companies are growing quickly and they are having a lot of impact, careers take care of themselves. And when companies aren’t growing quickly or their missions don’t matter as much, that’s when stagnation and politics come in. If you’re offered a seat on a rocket ship, don’t ask what seat. Just get on.


3. Seek opportunities where the outcome is success or failure. Nothing in between! You don't become a star doing your job. You become a star making things happen. I was once told early in my career that you learn the most in 1) rapidly growing organizations or 2) failing organizations.  I've been in both kinds of situations and wholeheartedly agree. Repeat. Get on a rocket ship. It'll either blow up or put you in orbit. Either way you'll learn a ton in a short amount of time. Put another way; seek jobs where you can get 5-10 years of work experience in 1-2 years.


4. Career Tracks & Meritocracies don't exist: Your career is not a linear, clearly defined trajectory.  It will be messy and will move more like a step function.


5. You will probably have champions and detractors on day 1: One interesting byproduct of the recruiting & hiring process of most organizations is it can create champions & detractors before you even start the job. Some folks might not like how you were brought into the organization (they might have even protested your hiring) and gun for you at every turn while others will give you the benefit of the doubt (even when you don't deserve one) because they stuck their neck out to hire you. We're all susceptible to these biases and few people truly evaluate/treat folks on a blank slate.


6. You'll only be known for a few things. Make those labels count: People rely on labels as quick filters. Keep this in mind when you pick an industry/company/job role/school because it can serve as an anchor or elevator in the future. It's unfortunate but that's the way it is. You should always be aware of what your "labels" are.


7. Nurture & protect your network and your network will nurture & protect you: Pay it forward and help people. Your network will be one of the biggest drivers of your success.

Voice recordings are useful at any point in time. If you want to save a lecture (or presentation) that you are attending, or record a voiceover for a project, the iPhone can be your solution. You don’t have to use an old tape recorder, or a standalone recorder. The iPhone’s fantastic technology records high quality voice recordings on demand, whenever you need it.

To get started, look for an application named “Voice Memos.” Most likely, this particular application is found in your Utilities category by default. Once you open it up, you are greeted by a large microphone, indicating you are in the correct application. When you want to start recording, simply tap on the large red button in the bottom left, and you are on your way to begin recording. What is important about recording voices on this application to the highest degree of quality, ensure that your meter in the bottom is within the middle range; with the pointer in the red zone, your recording will be awfully loud, while otherwise, it will be too quiet. Finished recording? Simply tap on the square button, and you have your recording.

What can you do with these recordings? Once you have finished recording, you are able to now share this recording through email or even in a text message; email it to yourself so you can save it on your computer, and listen to it later, or start editing it to put into a movie production, or text it to a friend for their needs.

The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

Related:

Who Are the Main Players in Big Data?

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”