18 big data certifications that will pay off

Data and big data analytics are becoming the life’s blood of business. Data scientists and analysts with expertise in the techniques required to analyze big data and engineers and developers who know their way around Hadoop clusters and other technologies, are hard to come by. If you’re looking for a way to get an edge — whether you’re job hunting, angling for a promotion or just want tangible, third-party proof of your skills – big data certification is a great option. Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers that you have the right skillset. The number of big data certs is expanding at a rapidly. Here are 16 you should consider.

Updated on April 20, 2017.

What it’s all about: The CAP certification is a rigorous general analytics certification. It certifies end-to-end understanding of the analytics process, from framing business and analytic problems to acquiring data, methodology, model building, deployment and model lifecycle management. It requires completion of the CAP exam (available at more than 700 Kryterion computer-based testing centers in more than 100 countries) and adherence to the CAP Code of Ethics.

How to prepare: INFORMS provides preview material and a Complete CAP Study Guide as an aid. It also provides free half-day CAP refresher sessions for organizations with 10 or more candidates.

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What it’s all about: This data science certification is offered jointly through TheFU Foundation School of Engineering and Applied Science and The Graduate School of Arts and Sciences at Columbia University. The program consists of four courses: Algorithms for Data Science (CS/IEOR), Probability & Statistics (STATS), Machine Learning for Data Science (CS) and Exploratory Data Analysis and Visualization (STATS).

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What it’s all about: This intensive 18-week program consists of 10 courses (lectures and labs) for students of all aspects of analytics, including working with big data using Hadoop. It focuses on R and Hadoop skills, as well as statistical modeling, data analytics, machine learning, text mining and optimization. Students are evaluated on a real-world capstone project and a series of quizzes.

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What it’s all about: Designed for software engineers, statisticians, predictive modelers, market research, analytics professionals and data miners, this certification requires four courses and demonstrates mastery of efficient, powerful techniques and algorithms for extracting information from large datasets like the Web, social network graphs and large document repositories. The certificate usually takes one to two years to complete.

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What it’s all about: This undergraduate-level program is intended for business, marketing and operations managers, data analyst and professionals, financial industry professionals and small business owners. The program brings together statistics, analysis, and written and oral communication skills. It introduces students to the tools needed to analyze large data sets, covering topics including importing data into an analytics software package, exploratory graphical and data analysis, building analytics models, finding the best model to explain correlation among variables and more.

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What it’s all about: The EMCDSA certification demonstrates an individual’s ability to participate and contribute as a data science team member on big data projects. It includes deploying the data analytics lifecycle, reframing a business challenge as an analytics challenge, applying analytic techniques and tools to analyze big data and create statistical models, selecting the appropriate data visualizations and more.

How to prepare: EMC offers a training course available as either a video or an instructor-led course.

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What it’s all about: The CCP:DS certificate demonstrates the skills to work with big data at an elite level. It requires passing a written exam that evaluates knowledge of fundamental data science topics. They must also prove their abilities under real-world conditions in a Data Science Challenge by designing and developing a production-ready data science solution that is peer-evaluated. The Challenge must be passed within 24 months of completing the written exam and is offered twice per year, every other quarter.

How to prepare: Cloudera offers classroom training with technical instructors, a practice test and a Data Science Challenge Solution Kit with a live data set, tutorial and explanation of process.

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What it’s all about: The CCP Data Engineer credential certifies the ability to perform core competencies requires to ingest, transform, store and analyze data in Cloudera’s CDH environment. It requires passing the remote-proctored CCP: Data Engineer Exam (DE575), a hands-on, practical exam in which each user is given five to eight customer problems each with a unique, large data set, a CDH cluster and four hours. For each problem, the candidate must implement a technical solution with a high degree of precision that meets all the requirements.

How to prepare: Cloudera suggests professionals seeking this certification have hands-on experience in the field and take the Cloudera Developer Training for Spark and Hadoop course.

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What it’s all about: The Cloudera Certified Associate (CCA) Spark and Hadoop Developer credential certifies a professional has proven their core skills to ingest, transform and process data using Apache Spark and core Cloudera enterprise tools. It requires passing the remote-proctored CCA Spark and Hadoop Developer Exam (CCA175), which consists of eight to 12 performance-based, hands-on tasks on a Cloudera Enterprise cluster. Each question requires the candidate to solve a particular scenario. Some cases may require a tool such as Impala or Hive, others may require coding. Candidates have 120 minutes to complete the exam.

How to prepare: There are no prerequisites required, but Cloudera says the exam follows the same objectives as the Cloudera Developer Training for Spark and Hadoop course, making it excellent preparation for the exam.

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What it’s all about: The CCSHB accreditation demonstrates technical knowledge, skill and ability working with Apache HBase, including core HBase concepts, data model, architecture, schema design, API and administration. Earning the certification requires passing a written exam of 45 questions with a 90-minute time limit.

How to prepare: Cloudera offers a practice test (with 180-day subscription) and a study guide.

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What it’s all about: A SQL developer who earns the CCA Data Analyst certification demonstrates core analyst skills to load, transform and model Hadoop data to define relationships and extract meaningful results from the raw output. It requires passing the CCA Data Analyst Exam (CCA159), a remote-proctored set of eight to 12 performance-based, hands-on tasks on a CDH 5 cluster. Candidates have 120 minutes to implement a technical solution for each task. They must analyze the problem and arrive at an optimal approach in the time allowed.

How to prepare: Cloudera recommends candidates take the Cloudera Data Analyst Training course, which has the same objectives as the exam.

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What it’s all about: This certification validates you can deploy and manage the Vertica Analytics Platform to help organizations optimize and monetize big data analytics. It verifies that you can: identify and describe key features of Vertica architecture, install the platform, identify characters and determine features of projections used in Vertica, describe how to load data into Vertica, articulate Vertica cluster management concepts, delineate backup/restore and resource management in Vertica and identify how to monitor and troubleshoot Vertica. The certification requires passing an exam with 50 multiple choice questions in one hour and 30 minutes.

How to prepare: HP recommends that candidates combine specific product knowledge and three to six months of field experience with solid understanding of RDBMS. Training is not required, but HP recommends taking the three-day Vertica Introduction course.

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What it’s all about: This certification validates that you can manage the Vertica Analytics Platform and verifies that you can perform advanced administrative tasks, including: manual projection design, diagnostics, advanced troubleshooting and database tuning. The certification requires passing an exam with 60 multiple choice questions in one hour and 40 minutes.

How to prepare: HP recommends candidates administer, manage and operate the Vertica Analytics platform for a minimum of six months before seeking this certification. Training is not required, but HP recommends taking the two-day HP Vertica Advanced Performance Tuning course.

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What it’s all about: Designed for data architects, this certification requires passing a test that consists of five sections containing a total of 55 multiple-choice questions. It demonstrates a data architect can work closely with customers and solutions architects to translate customers’ business requirements into a big data solution. IBM recommends a series of seven multi-day courses on SPSS Modeler to InfoSphere BigInsights to prepare for the test. More on IBM Certified Data Architect – Big Data

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What it’s all about: This certification is intended for big data engineers, who work directly with data architects and hands-on developers to convert an architect’s big data vision into reality. Data engineers understand how to apply technologies to solve big data problems and have the ability to build large-scale data processing systems for the enterprise. They develop, maintain, test and evaluate big data solutions within organizations, providing architects with input on needed hardware and software. This certification requires passing a test that consists of five sections containing a total of 53 multiple-choice questions. IBM recommends a series of nine multi-day courses to prepare for the test. More on IBM Certified Data Engineer – Big Data

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What it’s all about: This certification program is for individuals seeking to build on their basic programming knowledge by learning how to gather and analyze big data in SAS. You need at least six months of programming experience in SAS or another programming language to enroll. The six-week course uses an instructor-led classroom format in Cary, NC. Participants will focus on SAS programming skills; accessing, transforming and manipulating data; improving data quality for reporting and analytics; fundamentals of statistics and analytics; working with Hadoop, Hive, Pig and SAS; and exploring and visualizing data. The program includes two certification exams, both of which the participant must pass.

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What it’s all about: The MongoDB Certified Developer Associate credential is intended for software engineers who want to demonstrate a solid understanding of the fundamentals of designing and building applications using MongoDB. It requires a 90 minute, multiple choice exam.

How to prepare: There are no prerequisites, but MongoDB suggests candidates complete an in-person training or one of its online courses (M101J: MongoDB for Java Developers; M101JS: MongoDB for Node.js Developers; M101N: MongoDB for .NET Developers; M101P: MongoDB for Developers). MongoDB also provides the MongoDB Certification Exam Study Guide, available to those who have registered for a certification exam.

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What it’s all about: the MongoDB Certified DBA Associate credential is intended to demonstrate that operations professionals understand the concepts and mechanics required to administrate MongoDB. It requires a 90 minute, multiple choice exam.

How to prepare: There are no prerequisites, but MongoDB suggests candidates complete an in-person training or one of its online courses (M102: MongoDB for DBAs; M202: MongoDB Advanced Deployment Operations). MongoDB also provides the MongoDB Certification Exam Study Guide, available to those who have registered for a certification exam.

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