Six Hot Big Data Certifications for 2018

Which Big Data certifications should be at the top of your list in 2018?

In 2018 (and beyond), an organization's ability to innovate and grow will depend partly on its capacity to leverage, manage, and analyze big data. Relevant and timely insights enable companies to make correct business decisions.


A considerable number of enterprises, however, still face a skills gap in data management and analysis. It's no wonder that the demand for high-quality data management and analytics professionals is so high.


According to Glassdoor, Data Scientist was the top IT role in 2017. McKinsey forecasts a shortage of up to 190,000 data scientists in 2018 in the United States. And a recent Forrester Research report states that the demand for data engineers will continue to increase in 2018. Enterprises are also looking for data architects, data analysts, database administrators and managers.


If you're an IT professional with current big data capabilities, growth prospects are encouraging. There are an increasing number of big data certifications on offer from vendors, universities and institutes looking to address the growing demand for technical expertise.


Certifications demonstrate a holder's understanding of specific tools, platforms and technologies and constitute one of the criteria for an employer to assess whether a candidate has the knowledge and real-world skills to help implement a company's big data analytics plan and enable it to sustain a competitive edge.


Listed below are six of the hottest big data certifications:


1) Certified Analytics Professional (CAP)


The Certified Analytics Professional (CAP) certification is a vendor-neutral global qualification administered by the Institute for Operations Research and the Management Sciences (INFORMS). This certification is designed for candidates with experience in business analytics. It validates a general understanding of the seven stages of the analytics process:


? Framing business problems
? Framing analytics problems
? Acquiring data
? Selecting methodology
? Model building
? Deployment
? Model lifecycle management


Candidates must possess either a master's degree in an analytics-related discipline and three years of professional analytics experience, or a bachelor's degree in an analytics-related discipline and five years of work experience in analytics, or a non-analytics degree and seven years of professional analytics experience.


Additional eligibility requirements include previous or current employer's endorsement of necessary soft skills and acceptance of the CAP Code of Ethics. The Cap exam is multiple-choice with a 3-hour duration and the credential needs to be renewed every 3 years.


2) PGP in Big Data Analytics and Optimization (previously CPEE)


This globally-recognized credential is offered by the International School of Engineering (INSOFE). It consists of an 18-week program available in Bengaluru and Hyderabad, India. Aspirants are required to complete 10 courses comprised of lectures and labs on analytics with an emphasis on Hadoop and Rtools.


The courses cover statistics, text and social media analytics, optimization, machine learning and big data analytics. Candidates are evaluated with exams at the end of each module, daily quizzes and a real-world culminating project. Admission to the program is based on academic qualifications and work experience as well as performance on an entrance exam.


3) MCSE: Data Management and Analytics


This certification has replaced the Microsoft Certified Solutions Expert (MCSE): Business Intelligence, which was discontinued on March 31, 2017. The MCSE: Data Management and Analytics credential prepares candidates for roles in database design, database analysis and business intelligence analysis. It certifies skills in SQL administration, developing data solutions for enterprises, and using business intelligence data for business growth in on-premises and cloud environments.


Candidates are required to earn at least one of the following MCSA certifications:


? SQL Server 2012/2014
? SQL 2016 Database Administration
? SQL 2016 Database Development
? SQL 2016 BI Development
? Machine Learning
? BI Reporting
? Data Engineering with Azure


They must also pass one of 12 MCSE elective exams. For your certification to remain valid, you will need to pass a different elective exam annually. Sitting for the annual exams also demonstrates your keenness to learn new technologies and augment your skills.


Big Data SS 2017 man lifting numbers

4) Oracle Business Intelligence Foundation Suite 11g Certified Implementation Specialist


This certification validates skills in developing and managing data solutions using Oracle Business Intelligence Suite and is intended for mid-level Oracle Partner Network members who have experience selling and deploying Oracle Business Intelligence Suite solutions.


To earn this certification, you need to pass the Oracle Business Intelligence Foundation Suite 11g Essentials exam with a score of at least 63 percent. The exam consists of 75 multiple-choice questions to be completed within two hours.


Oracle does not require candidates to take specific preparation courses, but does recommend completing either the Oracle Business Intelligence Foundation 11g Implementation Specialist course or the Oracle Business Intelligence Enterprise Edition Plus Implementation Boot Camp (available to partners only).


5) SAS Certified Data Scientist Using SAS 9


This SAS credential demonstrates in-depth knowledge of and expertise in the use of SAS and open-source tools to manipulate big data. Certification holders understand how to derive business insights, make business recommendations using machine learning models and implement complex models.


Earning this certification isn't easy; you need to pass 5 exams, comprised of multiple-choice, short answer and interactive questions:


? SAS Big Data Preparation, Statistics and Visual Exploration
? SAS Big Data Programming and Loading
? Predictive Modeling Using SAS Enterprise Miner 13 or 14
? SAS Advanced Predictive Modeling
? SAS Text Analytics, Time Series, Experimentation and Optimization


Interactive questions are answered in a simulated SAS environment.


While there are no prerequisites or mandated courses to prepare for these exams, SAS does recommend its official preparation course for those who need guided training and can afford the fees. The SAS Data Science course is available in both e-Learning and instructor-led formats.


The SAS Certified Data Scientist Using SAS 9 credential does not expire, but exams may be retaken.


6) MongoDB Certified Developer Associate


MongoDB is a widely-used open-source NoSQL database. The MongoDB Certified Developer Associate certification is designed for software engineers who have the expertise to develop applications using MongoDB. This credential validates a thorough understanding of application design and development fundamentals based on MongoDB.


To become a MongoDB Certified Developer Associate, candidates need to pass a multiple-choice and �check all that apply' questions to be completed within 90 minutes. MongoDB does not specify prerequisites for the exam, but recommends in-person training, the MongoDB Certification Exam Study Guide, or one of its free online courses.


Which credential is right for you?


The choice of credential depends on one's career goals, aptitude, background and employer's needs. A quick Google search will reveal a range of other certifications from various universities, institutes and vendors, including Cloudera and IBM.


While a certification is a plus, by itself it is unlikely to land you a data analytics job. You will need significant experience working with big data issues. One excellent way to gain experience is to enter and ace data science competitions. Ultimately, employers will want proof of your coding ability and that you can solve real-world data queries.


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Reena Ghosh

Reena Ghosh is an independent ghostwriter who writes promotional, developmental and explanatory content for individuals and businesses. She came to professional writing with work experience in financial services operations and corporate communication. Reena speaks three languages and hopes to learn Sanskrit.