Six Niche Big Data Certifications

The right Big Data certification can lead to a great job.

Small, medium, and large enterprises the world over are transforming themselves digitally as they focus on mining data to improve decision-making and sharpen business strategy. Thus, current demand for specialists who know how to manipulate data is quite robust.


It's not surprising that Data Scientist is currently one of the top jobs in America. In January 2019, Glassdoor reported that Data Scientist was the best job in America for the fourth year in succession.


A recent Forbes article by Gil Press cites twp significant business developments in the Big Data space: Google's and Salesforce's announcements of their plans to acquire, respectively, Looker, a start-up focused on data discovery and analytics, and data visualization and analytics company Tableau. This indicates the growing importance of data analytics as more and more enterprises move to the cloud.


Specialization in a particular area is a good way to advance your career. Once you've worked with data for two or three years, you should decide what you want to specialize in. Database managers, architects, or administrators are responsible for storing, maintaining, and moving big data sets in order to facilitate data analysis.


Data analysts study data to discern patterns and derive inferences. Business intelligence specialists analyze data and present information to CEOs and managers to enable informed decision making.


The right certification can help demonstrate required skills and add value to your resume. There are several niche data certifications available today, some of which have a hands-on emphasis while others are concept-based. The certifications listed below will suit experienced professionals aspiring to concentrate on the area that most interests them.


Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics


The MCSE: Data Management and Analytics certification validates database administration and analytics skills using SQL Server technology for cloud and enterprise data centers. This credential is suitable for those aspiring to work as database analysts and designers, and business intelligence analysts.


To earn the MCSE certification, you need to earn an MCSA in SQL Server 2012/2014, or SQL 2016 Database Administration, Database Development, BI Development, Machine Learning, BI Reporting or Data Engineering with Azure, and pass one of these exams: Exam 70-464, or Exam 70-465, or Exam 70-466, or Exam 70-467, or Exam 70-762, or Exam 70-767, or Exam 70-768, or Exam 70-777.


After you earn the MCSE, you will need to pass one of the specified exams each year to maintain your certification. To prepare for the exam, you can opt for self-paced learning, instructor-led training, practice tests, video-based training, and community support.


SAS Certified Data Scientist Using SAS 9


This certification demonstrates the ability to manipulate large data sets and derive insights using a range of open source and SAS applications. You'll also verify your ability to provide business recommendations, as well as implement machine learning models at scale using the SAS platform.


To earn the SAS Certified Data Scientist Using SAS 9 accreditation, you need to earn the SAS Certified Big Data Professional and SAS Certified Advanced Analytics Professional credentials. This requires passing five exams, two for the SAS Certified Big Data Professional credential and three for SAS Certified Advanced Analytics Professional.


Preparation options include practice exams and an official course from the SAS Academy for Data Science for those who need professional guidance. You can also join the SAS certification community. SAS currently offers versioned credentials, which do not expire; however, certain exams may be retired if new or upgraded software makes that necessary.


AWS Certified Big Data – Specialty


The AWS Certified Big Data – Specialty certification is designed for professionals who have a background in AWS Big Data solutions, with a minimum of two years practical experience using AWS to analyse complex Big Data sets. This credential validates the holder's expertise in implementing fundamental AWS Big Data services in line with architecture best practices, designing and managing Big Data, and automating data analyses.


Amazon recommends aspirants earn an AWS Certified Cloud Practitioner, or AWS Certified Solutions Architect – Associate, or AWS Certified Developer – Associate, or AWS Certified SysOps Administrator – Associate before preparing for a specialty accreditation. Amazon also recommends at least five years of practical experience in a field of data analytics, with a background in AWS Big Data services architecture.


The right Big Data certification can lead to a great job.

To earn this certification, you need to pass the specified specialty certification exam. An exam guide and sample questions are available on the AWS website. AWS also offers a self-paced, Digital Data Analytics Fundamentals course and a classroom Big Data on AWS course.


AWS Specialty certifications are valid for three years. You will need to recertify to maintain your certification.


Certified Analytics Professional (CAP)


This vendor-neutral credential from INFORMS is intended for experienced professionals who wish to specialize in analytics. CAP demonstrates advanced knowledge of analytics, which includes articulating   business problems, as well as real-world application of analytics, data, developing models, deployment, and lifecycle management.


CAP has ANSI and ISO accreditation. According to Analytics Magazine, more than 20 percent of Fortune 100 enterprises employ CAP certified professionals.


To earn this certification, you need to fulfil specific education and experience requirements, formally accept the CAP Code of Ethics, and pass the CAP exam. You need to register on the site in order to avail of the sample exam, CAP Study Guide, and webinars, and join the CAP Study Group.


You will need to renew the certification every three years by earning professional development units.


Oracle Business Intelligence Foundation Suite 11g Certified Implementation Specialist


This specialist credential is suitable for mid-level BI implementation professionals who have hands-on experience with Oracle Business Intelligence Suite applications. It is primarily intended for Oracle Partner Network members involved in sales and implementation of this technology.


The certification validates advanced skills in installation of Oracle Business Intelligence Suite, building the BI Server metadata repository and BI dashboards, developing ad hoc queries, defining security settings, and managing cache files.


Oracle recommends real-world experience and current training. You need to pass one two-hour exam with a passing score of 63 percent or better.


Preparation options include the Oracle Business Intelligence Enterprise Edition Plus Implementation boot camp for Oracle Partners only, the Oracle Business Intelligence Foundation 11g Implementation Specialist, Oracle BI 11g R1: Build Repositories, and Oracle BI 11g R1: Create Analyses and Dashboards courses.


Data Mining and Applications Graduate Certificate


This graduate certificate offered by Stanford University has a data mining and machine learning focus, both of which are critical skills when it comes to working with huge volumes of data. This credential demonstrates the ability to apply these skills in developing solutions for business as well as science and technology.


Students learn how to use statistical methods to derive insights from Big Data, build and implement predictive models and analytics, and understand how to use Big Data applications to enhance strategic decision making.


This program is intended for researchers in medicine, science, and social sciences, strategy managers, data analysts, and marketing professionals. Prerequisites for application include introductory courses in three specific fields: statistics or probability, linear algebra, and computer programming, and a conferred bachelor's degree with a GPA of a minimum of 3.5.


To earn this credential, you need to complete your first course, which will either be STATS202 or STATS216, with at least a B+. Once you achieve this, you can progress to the other courses, which you must complete with at least a B.


The average time taken to earn this certification is one to two years. Students are allowed a maximum of three years to complete the certification process.


More Options


Other intriguing Big Data certifications include EMC Proven Professional Data Scientist Associate (EMCDSA), Certification of Professional Achievement in Data Sciences from Columbia University, Microsoft Professional Program in Big Data, IBM Certified Data Architect, and Cloudera Certified Professional Data Engineer (CCP Data Engineer), to name a few.


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