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Scale-out NoSQL databases are quickly rising and taking the place of outdated and underperforming SQL databases.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.

3 Big Data Trends for 2017

3 Big Data Trends for 2017

The term “Big Data” has only been around for the last decade or so, but in that time the use of big data has changed drastically. There most common definition of big data was coined by industry leader Doug Laney. He broke the definition up into the three Vs:

Velocity-Data comes in at an alarming rate and needs to be analyzed as soon as possible. Each year technology is making it easier for us to analyze the data in real time.

Variety-Data does not come in one specific format. It can be structured in traditional databases or unstructured documents such as text, email, video, and audio formats.

Volume-Data comes from many different sources and there is a lot of it, hence the term “Big Data.” New technologies are making it easier to compress and store the waves of data coming in.

For a long time, the data was compiled, and not a whole lot was done with it. In recent years, technologies have allowed us to use big data to streamline processes, discover trends, and even catch criminals. Big data has a bright future as it is something we are only recently understanding. Look for it to play a big role in the following ways in 2017.

Cloud Computing

Companies of all sizes are strategizing on ways to take their applications to the cloud, and the same goes for big data analytics. The ability to host data on the cloud instead of in data centers not only gives greater flexibility to companies in terms of where the data is stored, but it also allows those companies to move to a subscription-based service instead of signing multi-year deals on equipment to store data. Cloud service providers are now offering big data processing platforms, which makes the transition much easier.

Real-Time Analytics

Now that big data has been compiled and technology is getting better at sorting that data, executives are going to be making a push towards getting real-time analytics. Having the data is great, but the business world does not slow down or stop for anything, and if executives can have the data results in real time it will give them better insight into the next step they can take.

Incorporation of Dark Data

There is a huge amount of dark data that could be beneficial to companies, but it has yet to be cataloged and analyzed. So many companies have piles of physical documents, videos, and important corporate files that have yet to be converted to digital data. There will be a strong push to add all of these documents to databases in 2017 to help give a more comprehensive view of performance trends and cycles through the history of the company.

As more and more data streams into data centers across the world, we are tasked with the challenge of using it in a constructive and beneficial way for business and society as a whole. The future of big data is bright and exciting, and the technology that is being developed to analyze it will only improve its functions moving forward. Read more about big data and bitcoin at www.juddbagley.io.