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Big Data Training, Is It Worth It?

October 13, 2017

Big Data Training, Is It Worth It?

The big data bandwagon has arrived and everyone is jumping on, but there is still a dearth of big data talent. Big data demand is driving the need for more experts, so more integrators and resellers are looking for big data training. But where should you go? Will vendor certification pay off or are other types of big data training more valuable? Or do you need big data training at all?

When you consider the potential value of big data and how it differs from conventional enterprise and database systems, big data training is clearly worth it. Big data is still a new area and qualified experts are in short supply.

McKinsey is calling big data the Next Frontier for Competition, noting that the United States alone will face a shortage of 14,000 to 190,000 professionals with big data analytics expertise, and 1.5 million managers and analysts with the skills to interpret big data analytics. Universities are starting to add big data to their curricula, but you need big data training now.

And with so few true experts, customers are going to be confused by suppliers who can talk the talk but don’t know how to walk the walk. If you can offer real big data expertise, then you will stand head and shoulders above those VARs looking for customers to pay for their on-the-job training.

When you consider the demands of big data, training can come in various forms.

Training in Big Data Training Infrastructure

Big data requires a new way of thinking about the enterprise architecture. Storage needs to be elastic and scalable, able to adapt to handle petabytes of data for analysis. Network-attached storage (NAS) can’t handle the demands of big data analytics so more big data systems are adopting storage clusters and object-based storage architectures. Both local storage and cloud storage has to provide both scalability and performance.

Cisco, VMware, EMC, and other vendors are initiating their own big data training and certification programs. Of course, the training is often specific to their platforms so if you are standardizing on one set of vendors for your big data solutions, vendor certification is a good idea.

There are third-parties offering training in big data design and architectures. If you need a deeper understanding of the strengths and limitations of highly accessible data storage, virtualization, parallel processing, integrating cloud systems, and other elements of big data design, taking a course from established reputable training operations or big data vendors will be beneficial. Having a certification you can show to a potential customer won’t hurt either.

Capitalizing on Big Data Developer Skills

Perhaps the greatest big data training demand is for software and big data programming. Hadoop continues to lead the pack as the big data developer framework of choice, although there are challengers emerging from both the open source community and private vendors.

Apache Hadoop is an open source framework that “allows for the distributed processing of large data sets across clusters of computers using simple programming models.” It is specifically designed to scale from processing on a single server to thousands of machines that share local data storage and computing power. It also has redundancy built it, and is designed to deliver high-available across compute clusters even in the event of a failure.

As an open source framework, Hadoop is well-documented with plenty of resources. Programming experience in Java, Python, and other languages translates well to Hadoop, so starting with programming experience is a definite advantage.

Cloudera, Hortonworks, and other big data software providers offer certification training in Hadoop, Cassandra, Pig, R, and related big data programming tools. Certification in Hadoop also is a great asset, whether you are selling big data services or looking for a job in big data.

There are alternatives to Hadoop, but most of these alternatives are based on the same principles as Hadoop – distributed file systems and MapReduce. If you want to acquire immediate big data programming expertise you can’t go wrong with Hadoop, but you may encounter other big data platforms for specific projects.

Big Data Analytics Are In Demand

In addition to programming, you need to be able to manage Hadoop projects and analyze and present the results.

Data scientists are the unicorns of the big data industry because they are so rare, but the mathematical and statistical analytical skills of data science are exactly what are needed to interpret big data analytics. They must be able to interpret and present patterns revealed in the data.

Data scientists are hard to find but not impossible to train. You need to find someone who is inquisitive and can communicate findings in a way that turns insight into action.

So is big data training worth it? You bet. It’s all a matter of where you want to expand our skills.