The name placard in your cube might not say anything about sales, but the truth is that everyone, employed as such or not, is a salesperson at some point every single day. In the traditional sense, this could mean something like pitching your company’s solutions to a client. In the less-traditional sense, it could mean convincing your child to eat their vegetables. Yet for those two drastically different examples and everything in between, there is a constant for successful sellers: unveiling the “Why.”

Spending time and energy making prospects understand why you do what you do instead of exactly what it is you do or how you do it is not a new concept. But I’m a firm believer that proven concepts, no matter how old and frequently referenced they are, can’t be repeated enough. This idea has recently and fervently been popularized by marketer, author, and thinker extraordinaire Simon Sinek via his 2009 book, Start With Why. You can learn about him here on Wikipedia or here on his site. To begin, let me suggest that you watch Sinek’s TED talk on Starting With Why here on YouTube before reading any further. I’ll let him take care of the bulk of explaining the basics, and then will offer some ideas of my own to back this up in the real world and explore the best ways to start thinking this way and apply it to your business.

First, a little on me. After all, if I were to practice what Sinek preaches, it would follow that I explain why it is I’m writing this piece so that you, the reader, not only have a good reason to pay attention but also understand what drives me on a deeper level. So, who am I? I’m an entrepreneur in the music space. I do freelance work in the realms of copywriting, business development, and marketing for artists and industry / music-tech folks, but my main project is doing all of the above for a project I’ve been on the team for since day one called Presskit.to. In short, Presskit.to builds digital portfolios that artists of all kinds can use to represent themselves professionally when pitching their projects to gatekeepers like label reps, casting directors, managers, the press, etc. This core technology is also applicable to larger entertainment industry businesses and fine arts education institutions in enterprise formats, and solves a variety of the problems they’re facing.

Not interesting? I don’t blame you for thinking so, if you did. That’s because I just gave you a bland overview of what we do, instead of why we do it. What if, instead, I told you that myself and everyone I work with is an artist of some sort and believes that the most important thing you can do in life is create; that our technology exists to make creators’ careers more easily sustainable. Or, another approach, that we think the world is a better place when artists can make more art, and that because our technology was built to help artists win more business, we’re trying our best to do our part. Only you can be the judge, but I think that sort of pitch is more compelling. It touches on the emotions responsible for decision making that Sinek outlines in his Ted Talk, rather than the practical language-based reasons like pricing, technicalities, how everything works to accomplish given goals, etc. These things are on the outside of the golden circle Sinek shows us for a reason – they only really matter if you’ve aligned your beliefs with a client’s first. Otherwise these kind of tidbits are gobbledygook, and mind-numbingly boring gobbledygook at that.

Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

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.

The Zen of Python, by Tim Peters has been adopted by many as a model summary manual of python's philosophy.  Though these statements should be considered more as guideline and not mandatory rules, developers worldwide find the poem to be on a solid guiding ground.

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!