In this tutorial we are going to take a look at how you work with strings in Python. Now, any language worth its salt will have a number of options for working with text and Python is probably one of the best to use when it comes to processing text.

If you are new to programming in general you may be wondering what a string is. In terms of programming, a string is classed as any sequence of characters you can type with your keyboard, and let’s face it, if you want your application to be of any use to yourself or other users then you need it to tell you what it’s doing or to prompt you for an action, and that is where strings come into play.

They are your applications way of communicating with the user. Without the ability to enter and display text or software would be pretty useless.

So, how would you create a string in Python? Take a look at the following code:

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?

One of the biggest challenges faced by senior IT professionals in organizations is the choice of the right software vendor. In the highly competitive enterprise software industry, there are lot of vendors who claim to offer the best software for the problem and it can be really daunting to narrow down the best choice. Additionally, enterprise software costs can often run into millions of dollars thereby leaving very little margin of error. The real cost of choosing a wrong software can often result into losses much more than the cost of the software itself as highlighted by software disasters experienced by leading companies like HP, Nike etc. In such a scenario, senior IT professionals despite years of expertise can find it very difficult to choose the right business software vendor for their organization.

Here are some of the proven ways of short-listing and selecting the right business software vendor for your organization,

·         Understand and Define The Exact Need First: Before embarking on a journey to select the software vendor, it is critical to understand and define the exact problem you want the software to solve. The paramount question to be asked is what business objective does the software need to solve. Is the software required to “reduce costs” or is it to “improve productivity”? Extracting and defining this fundamental question is the bare minimum but necessary step to go searching for the right vendor. It will then form the basis of comparing multiple vendors on this very need that your organization has and will help drive the selection process going forward. The detailed approach involves creating a set of parameters that the software needs to meet in order to be considered. In fact, consider categorizing these parameters further in “must-haves”, “good to have” etc. which will help you assign relevant weights to these parameter and how the software’s fare on each of these parameters

·         Building The List of Vendors Who Meet The Need: Once you have defined your need and distilled that need into various parameters, it’s time to built the list of vendors who you think will meet the need. This is akin to a lead generation model wherein you want to identify a large enough pool and then filters your list down to the best ones. There are multiple ways of building a list of vendors and more often than not, you must use a combination of these methods to build a good enough list.

o   Use Industry Reports: We discussed the IT intelligence offered by leading industry firms Gartner and Forrester in How To Keep On Top Of Latest Trends In Information Technology. These firms based on their access to leading software vendors and CIO network publish vendor comparison research reports across specific verticals as well as specific technologies. Gartner’s Magic Quadrant and Forrester’s Wave are a very good starting point to get an insight into the best software vendors. For example, if you were looking for a CRM solution, you could look for Gartner’s Magic Quadrant for CRM and look at the vendors that make the list. These reports can be pricey but well worth the money if you are going to invest hundreds of thousands in the software. Having said that, you don’t have to trust these report blindly because how these firms define the best software may not match how you define the best software for your organization

o   Competitive Intelligence: If you are a smart professional, you are already keeping tabs of your competition. Chances are that if you are a big organization, you might see a Press Release either from your competitor or their vendor announcing the implementation of new software. Extrapolate that across 5-10 key competitors of yours and you might discover the vendors that your competitors are choosing. This gives you a good indicator that the vendors used by your competitors must be offering something right.

Another blanket article about the pros and cons of Direct to Consumer (D2C) isn’t needed, I know. By now, we all know the rules for how this model enters a market: its disruption fights any given sector’s established sales model, a fuzzy compromise is temporarily met, and the lean innovator always wins out in the end.

That’s exactly how it played out in the music industry when Apple and record companies created a digital storefront in iTunes to usher music sales into the online era. What now appears to have been a stopgap compromise, iTunes was the standard model for 5-6 years until consumers realized there was no point in purchasing and owning digital media when internet speeds increased and they could listen to it for free through a music streaming service.  In 2013, streaming models are the new music consumption standard. Netflix is nearly parallel in the film and TV world, though they’ve done a better job keeping it all under one roof. Apple mastered retail sales so well that the majority of Apple products, when bought in-person, are bought at an Apple store. That’s even more impressive when you consider how few Apple stores there are in the U.S. (253) compared to big box electronics stores that sell Apple products like Best Buy (1,100) Yet while some industries have implemented a D2C approach to great success, others haven’t even dipped a toe in the D2C pool, most notably the auto industry.

What got me thinking about this topic is the recent flurry of attention Tesla Motors has received for its D2C model. It all came to a head at the beginning of July when a petition on whitehouse.gov to allow Tesla to sell directly to consumers in all 50 states reached the 100,000 signatures required for administration comment. As you might imagine, many powerful car dealership owners armed with lobbyists have made a big stink about Elon Musk, Tesla’s CEO and Product Architect, choosing to sidestep the traditional supply chain and instead opting to sell directly to their customers through their website. These dealership owners say that they’re against the idea because they want to protect consumers, but the real motive is that they want to defend their right to exist (and who wouldn’t?). They essentially have a monopoly at their position in the sales process, and they want to keep it that way. More frightening for the dealerships is the possibility that once Tesla starts selling directly to consumers, so will the big three automakers, and they fear that would be the end of the road for their business. Interestingly enough, the big three flirted with the idea of D2C in the early 90’s before they were met with fierce backlash from dealerships. I’m sure the dealership community has no interest in mounting a fight like that again. 

To say that the laws preventing Tesla from selling online are peripherally relevant would be a compliment. By and large, the laws the dealerships point to fall under the umbrella of “Franchise Laws” that were put in place at the dawn of car sales to protect franchisees against manufacturers opening their own stores and undercutting the franchise that had invested so much to sell the manufacturer’s cars.  There’s certainly a need for those laws to exist, because no owner of a dealership selling Jeeps wants Chrysler to open their own dealership next door and sell them for substantially less. However, because Tesla is independently owned and isn’t currently selling their cars through any third party dealership, this law doesn’t really apply to them. Until their cars are sold through independent dealerships, they’re incapable of undercutting anyone by implementing D2C structure.