I remember the day like it was yesterday. Pac Man had finally arrived on the Atari 2600.  It was a clear and sunny day, but it was slightly brisk. My dad drove us down to the video store about three miles from our Michigan house. If I remember correctly, the price for the game was $24.99.  It was quite expensive for the day, probably equaling a $70 game in today’s market, but it was mine. There *was* no question about it. If you purchase a game, it’s your game… right?

You couldn’t be more wrong.  With all the licensing agreements in games today, you only purchase the right to play it. You don’t actually “own” the game. 

Today, game designers want total control over the money that comes in for a game. They add in clauses that keep the game from being resold, rented, borrowed, copied, etc. All of the content in the game, including the items you find that are specifically for you, are owned by the software developer. Why, you ask, do they do this? It’s all about the money.

This need for greed started years ago, when people started modifying current games on the market. One of the first games like this was Doom. There were so many third part mods made, but because of licensing agreement, none of these versions were available for resale. The end user, or you, had to purchase Doom before they could even install the mod.  None of these “modders” were allowed to make any money off their creation.

Learning SQL development can seem like an overwhelming task at first. However, mastering just a few key points will help ease your way through 80 percent of the day-to-day challenges when writing stored procedures and solving common problems. Here are three important SQL development factors to keep in mind:

Outer Joins
One of the most crucial things to understand in SQL server are joins. Joins are a way to retrieve data from two or more tables based on logical relationships between them. Joins dictate how Microsoft SQL Server ought to use data from one table to select the rows in another table.

In my experience inner joins are intuitive while outer joins can present additional hours of grief by overlooking associations in the other table(s). The outer join is the key to answering questions about what the database does not have. For example, if you need to make a query to display all the students who are without report-cards, you’ll need a left join to get all students coupled with a “where clause” to return the ones who have nulls for their report card table columns in the results.

Many talented Java script programmers have muddled through the SQL Server by deficient coding around the inner join. As a result, their queries can take five hours to run, whereas, properly written left joins, can take only two seconds to run.

Aggregation
Grouping results comes up in SQL a lot more than you might think. Knowing how to write a query when answering questions such as, “What’s the average grade for each teacher’s student list?” is invaluable. This kind of question cannot be answered with a single table or solely by joins.  You’ll often find you need to use joins in conjunction with group by statements. Always write the raw query first and then look at the results. Next, you have to figure out the best way to group them, rewrite your select clause and add a group by clause in the end.

Digging Through Data
I find this is the most lacking skill in many programmers. In fact, many otherwise-talented programmers holding Master’s Degrees fail to get jobs because they couldn’t analyze rows of data objectively during interviews. It’s just something that’s not taught but is crucial to get under you belt. Why? Eventually, some query is not going to perform as you may expect. And, the only way to find discrepancies is to look at rows of data, identify what join isn’t finding a match or where bad data is throwing things into chaos. Get familiar with how joins actually work, even if you have to manually walk through the logic of a large stored procedure’s tree of joins. It’s boring and time-consuming but absolutely necessary.

Take the time to master the core skills that will make you a successful SQL Programmer and avoid queries that run for five hours!

In recent decades, companies have become remarkably different than what they were in the past. The formal hierarchies through which support staff rose towards management positions are largely extinct. Offices are flat and open-plan collaborations between individuals with varying talent who may not ever physically occupy a corporate workspace. Many employed by companies today work from laptops nomadically instead. No one could complain that IT innovation hasn’t been profitable. It’s an industry that is forecasted to rake in $351 billion in 2018, according to recent statistics from the Consumer Technology Association (CTA). A leadership dilemma for mid-level IT managers in particular, however, has developed. Being in the middle has always been a professional gray area that only the most driven leverage towards successful outcomes for themselves professionally, but mid-level managers in IT need to develop key skills in order to drive the level of growth that the fast paced companies who employ them need. 

What is a middle manager’s role exactly? 

A typical middle manager in the IT industry is usually someone who has risen up the ranks from a technical related position due to their ability to envision a big picture of what’s required to drive projects forward. A successful middle manager is able to create cohesion across different areas of the company so that projects can be successfully completed. They’re also someone with the focus necessary to track the progress of complex processes and drive them forward at a fast pace as well as ensure that outcomes meet or exceed expectations.

What challenges do middle managers face in being successful in the IT industry today? 

While middle managers are responsible for the teams they oversee to reach key milestones in the life cycle of important projects, they struggle to assert their power to influence closure. Navigating the space between higher-ups and atomized work forces is no easy thing, especially now that workforces often consist of freelancers with unprecedented independence. 

What are the skills most needed for an IT manager to be effective? 

Being educated on a steady basis to handle the constant evolution of tech is absolutely essential if a middle manager expects to thrive professionally in a culture so knowledge oriented that evolves at such a rapid pace. A middle manager who doesn't talk the talk of support roles or understand the nuts and bolts of a project they’re in charge of reaching completion will not be able to catch errors or suggest adequate solutions when needed. 

How has the concept of middle management changed? 

Middle managers were basically once perceived of as supervisors who motivated and rewarded staff towards meeting goals. They coached. They toggled back and forth between the teams they watched over and upper management in an effort to keep everyone on the same page. It could be said that many got stuck between the lower and upper tier of their companies in doing so. While companies have always had to be result-oriented to be profitable, there’s a much higher expectation for what that means in the IT industry. Future mid-level managers will have to have the same skills as those whose performance they're tracking so they can determine if projects are being executed effectively. They also need to be able to know what new hires that are being on-boarded should know to get up to speed quickly, and that’s just a thumbnail sketch because IT companies are driven forward by skills that are not easy to master and demand constant rejuvenation in the form of education and training. It’s absolutely necessary for those responsible for teams that bring products and services to market to have similar skills in order to truly determine if they’re being deployed well. There’s a growing call for mid-level managers to receive more comprehensive leadership training as well, however. There’s a perception that upper and lower level managers have traditionally been given more attention than managers in the middle. Some say that better prepped middle managers make more valuable successors to higher management roles. That would be a great happy ending, but a growing number of companies in India’s tech sector complain that mid-level managers have lost their relevance in the scheme of the brave new world of IT and may soon be obsolete.

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.