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Six Hot Big Data Certifications for 2019

A new year approaches! If you have a serious professional interest in Big Data, then make a big impact on your career outlook by focusing on one of these six certifications in 2019.

Get one of these credentials to take you interest in Big Data to the next level!It’s almost 2019. With the passing of another year, many companies are jumping onto the certification bandwagon and offering certifications in anything and everything ... and I love it!


Nothing is more satisfying and rewarding than getting a certification, a document that says you have mastered an IT topic, or sometimes just that you gained a basic understanding of that topic. To make your 2019 bright and beautiful, here is a list of my top six Big Data certifications for the coming year.


First up is the CCA Data Analyst credential (exam CCA159) offered by Cloudera. I love Cloudera tests because they are hands-on and incorporate real-world examples, and this test does not disappoint. It is special because it is straightforward and focused. Where else are you going to get 8 questions with 120 minutes to answer them?


To say Cloudera tests are tough would be highly accurate — but once you bag one, no one is going to question your prowess. Each test consists of between eight and 12 customer problems that involve a unique large data set and a CDH cluster. As noted above, you’ve got 120 minutes.


For each problem, you must implement a technical solution with a high degree of precision that meets all the requirements. You may use any tool or combination of tools on the cluster — you get to pick the tool(s) that are right for the job. You must possess enough knowledge to analyze the problem and arrive at an optimal approach given the time allowed.


You need to know what you should do and then do it on a live cluster, within the specified time allotment, while being watched by a proctor. Make no mistake: You should have a LOT of real-world knowledge before you tackle this exam. In terms of fess, the CCA159 will set you back $295.


My second recommendation is a bit unconventional and not really a “certification” per se, but I recommend getting a master’s degree in data analytics. If you have a genuine interest in Big Data, then I recommend jumping in with both feet to show future employers just how deep the fire burns. A degree will show that you have knowledge and experience that goes beyond just excelling at test taking.


I recommend looking around for a reputable college that does most (if not all) of its course delivery online. I also believe your best bet for funding an advanced degree is through your current employer. Many employers participate in cost-sharing for higher education, and if yours doesn’t then you may still be able to work out a deal.


Don’t be shy about asking either, because to make Big Data a reality, a team of individuals executing the delivery needs to be well-trained. I like this method of learning because it is going to set you apart from the pack and put you head-and-shoulders above the rest of the folks trying to break into Big Data.


My third recommendation is EMC (Dell)’s data science certification track. Science is an overarching theme of working with Big Data. Data extraction is a science, data processing and data storage is a science, and, analyzing data is definitely a science.


You will need to take a couple of tests for this, but aim for the Dell EMC Certified Specialist – Data Scientist credential. The exam to focus on is E20-065 Advanced Analytics Specialist Exam for Data Scientist, which has two associate-level prerequistes Associate – Data Science Version 1.0 and Associate – Data Science Version 2.0.


The Advanced Analytics certification is designed to build on the skills developed at the associate level and help aspiring Data Scientists continue to evolve and expand their skill sets


The main growth areas include advanced analytical methods, Hadoop (including Pig, Hive, HBase), Social Network Analysis, Natural Language Processing, and Visualization methods. This certification is above and beyond others due to its focus on NLP.


Natural Language Processing (NLP) is a subfield of computer scienceinformation engineering, and artificial intelligence concerned with the interactions between computer and human (natural) languages. In particular, NLP studies how to program computers to process and analyze large amounts of natural language data.


If you want a fast track to a long-term job, get in on the NLP movement. Right now, engineers are real-time translating languages and archiving all known languages throughout the earth. This is highly interesting stuff and will have you on the cutting edge of AI.