What to Know for a Career in Big Data

What to Know for a Career in Big Data

Positions in big data and analytics are highly coveted right now, and you can turn an expertise in big data into a very lucrative and successful career. Before setting out and applying for these positions, there are few things you should know about the world of big data. By being well-versed on these topics, you will drastically increase your chances of landing that position you’ve been after.

Apache Hadoop

Although Hadoop is now over 20 years old, it is still the frontrunner in terms of storage and distribution architecture. It is an extremely powerful platform, but it is not without its flaws. Technicians versed in the components of Hadoop will be in high demand. Along with Hadoop, it’s a good idea to have a handle on Spark as it could be poised to take over Hadoop in the coming years.

NoSQL

Scale-out NoSQL databases are quickly rising and taking the place of outdated and underperforming SQL databases. These databases are often the source of the data that is then crunched in Hadoop. It is a good rule of thumb to learn them independently and be able to use them together since they essentially complete the big data cycle from opposite sides of the spectrum.

Data Mining

The idea of data mining has been around basically since the time we started collecting data. Be aware of the trends in data mining and how it is used throughout different industries. It takes a certain level of analysis and critical thinking to be able to perform effectively, but once you get it down you will make yourself much more valuable to any employer you apply to.

Machine Learning

Machine learning had a huge year in 2015, and it has only been getting bigger since that breakout. By being able to harness the power of machine learning, you can build predictive apps and train them to be highly analytic in terms of classification, recommendation, and personalization systems.

Data Interpretation and Visualization

With all of the technology out there in the world to interpret data, sometimes the best tool is still the human brain with a well-trained pair of eyes. There are tools out there to help break it down and make interpretation more manageable, but in reality, the best tool to rely on is you. If you want a career in big data and analyzation, you will need to be versed in current visualization tools along with being able to learn tools that haven’t even been developed yet.

Basic Programming

While you may not be applying for a programming position, it doesn’t hurt to have a general knowledge of the most common programming languages, especially SQL, Java, Javascript, C, and Python. This skillset may set you apart from your competition in the interview process and help you earn the job.

Problem Solving

Being able to solve problems, think critically, and be creative will go a long way in the world of big data. You will run into countless issues that will need to be rectified quickly. You’ll also need to constantly learn new technologies, and critical thinking will take you a long way in being able to adapt.

Big Data careers are gaining momentum as more companies are starting to gather and analyze information. Take the time to learn some or all of the above skills to give yourself the best chance of getting your dream job in big data.

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What is the Internet of Things?

What is the Internet of Things?

The Internet of Things (IoT) is a common term that gets thrown around in the tech world, but if you are not part of that world on a daily basis you may not realize what all is covered by that broad term. Developers are pushing the boundaries of technology every day, and the Internet of Things will eventually be a part of everyone’s home.

On a broad spectrum, the IoT is an intricate system of devices that are connected and can transfer data over a network. All of these connected devices are considered “things” and the network is the “internet” giving us the Internet of Things.

A thing can be a smart car with a chip to notify the driver of any internal issues, a refrigerator with an internal camera that can be accessed from another thing (cell phone, tablet, etc.) remotely. A coffee maker that can be set to brew from your cell phone would be another example of a thing. Essentially, anything that can be assigned an IP address and has the ability to transfer data falls into this broad category of things.

Access to the internet is becoming widely available, and the cost of high-speed internet is also becoming more affordable each year. The cost of technology that allows devices to access the internet has also been increasing in affordability. These trends are allowing developers to take devices that are already mainstays in most households (fridge, microwave, coffee maker) and upgrade them with Wi-Fi capability and allow users to access them remotely via their cell phones.

The rush by developers to create Wi-Fi capable items and devices has experts excited about the future of the IoT. There are three relationships for these network connections: human-human, human-thing, and thing-thing. With the early success of the IoT, there is a mindset of “if it can be connected, it should be connected” and that mindset has grown the IoT tremendously in the past few years. Experts are forecasting that there will be over 26 billion connected devices by 2020, and most believe that is a conservative number. The real number could be upwards of over 100 billion.

The IoT will have a large impact on most American households in the not so distant future based on those forecasted numbers. Most people have one of two mindsets when it comes to this world of connects. They either wonder why you would want to be so connected to everything, or they wonder why you wouldn’t want to be. No matter what your thoughts are on the IoT, the reality is that these devices are already in production. I wouldn’t mind living in a world where my alarm clock goes off and sends my coffee maker a notification to start brewing, but that’s just me.

The Future of Autonomous Vehicles

The Future of Autonomous Vehicles

It’s no surprise that the next big innovation in the automobile industry is fully autonomous vehicles. Automotive leaders across the world are all competing design the first mass-produced autonomous vehicle for commercial roadways. Driverless vehicles are already being utilized in the mining industry, and Tesla has rolled out vehicles with an autopilot mode over the past year. Some companies, Google included, have been testing driverless cars, but they are not being mass produced. So how far are we from seeing fully autonomous vehicles driving through our cities?

It seems hard to believe, but it has already been two years since Audi sent an autonomous A7 from San Francisco to CES in Las Vegas. The 569-mile journey was a monumental accomplishment for Audi and the autonomous community alike. The trip showed the capabilities of driverless vehicles even though they were not (and still are not) being mass produced.  

Tesla is the company that is usually top of mind in most autonomous vehicle conversations. The Autopilot feature on the Model S and Model X allows the driver have a hands-free “driving” experience. The Autopilot technology is constantly being improved via software updates, and the updates download in real time with over-the-air syncing. In December Tesla rolled out “Enhanced Autopilot” with a few key improvements. Enhanced Autopilot will match the speed of traffic conditions, keep within lanes or change lanes without needing driver input, transition from one freeway to another, exit the freeway, park in a parking spot, and be summoned to you from your garage. A Tesla recently predicted a collision two cars ahead of it on the freeway and alerted the driver before it happened.

There seems to be a common timeframe for other vehicle manufacturers to roll out autonomous cars to the masses. Ford made an announcement in August of 2016 that it will start shipping self-driving cars without steering wheels, brake pedals, or gas pedals by 2021. Ford CEO Mark Fields stated that the auto giant is moving towards being a mobility company instead of an auto company by launching a new subsidiary, Ford Mobility Solutions. Ford also plans on doubling up on employees in Silicon Valley and opening new offices and labs in Palo Alto. BMW, Toyota, Tesla, Volkswagon, and other manufacturers are all along the same timeline, give or take a year.

While sitting behind the lack of a wheel in an autonomous vehicle seems like something we’ll all be doing in the future, it is going to be a slow process. Vehicles will be rolled out in different stages and with different features. The technology needed to make a car fully autonomous will increase the price by roughly $10,000, and early predictions show that consumers will be very hesitant to make a purchase until the cars are proven to be safe.

The most important factor to getting these vehicles on the road comes in the form of laws and regulations. With autonomous vehicles taking the road, lawmakers must come up with a whole new rulebook to set the standards for driverless vehicles.