Six Hot Big Data Certifications for 2020
There is value in data. Enterprises that have the expertise to manage huge amounts of data, extract relevant information, analyze it, and derive insights about customers' unique needs and behaviors stand to gain. Therefore, more and more organizations are hiring professionals who have the knowledge and skills to manage large data sets and make sense of all the data.
Professionals who manage, store, and move large sets of data are normally known as data system administrators. Data engineers build big data infrastructure. Data analysts study data, discern trends, and draw inferences. Data scientists use data and scientific methods to mine information and solve complex problems.
Data scientists and data engineers are among the most in-demand IT professionals today. Key skills for data scientists include data science, machine learning, Python, Apache Spark, and R. Data engineers are expected to be conversant with AWS, Hadoop, Apache Spark, Python, and ETL.
Many data professionals have a background in mathematics, statistics, or engineering. According to a Forbes article by Eva Murray, employers expect data analysts to have technical skills, business acumen, communication and stakeholder management skills, critical thinking ability, and presentation and data visualization skills.
Certification programs offer candidates the framework to develop current knowledge and skills and measure their professional capabilities against industry-relevant benchmarks.
Listed here are 6 sought-after big data and analytics certifications:
The MCSE: Data Management and Analytics credential is designed for professionals looking to work as database designers, database analysts, and business intelligence analysts. It indicates expertise in SQL administration, as well as the ability to develop data solutions for large enterprises and manage business intelligence information in the cloud and on-premise.
Microsoft requires candidates to hold a valid MCSA certification in one of the following:
? SQL Server 2012/2014
? SQL 2016 Database Administration
? SQL 2016 Database Development
? SQL 2016 BI Development
? BI Reporting
To earn the MCSE: Data Management and Analytics credential, you need to pass one of the specified MCSE elective exams. In order to ensure that MCSE holders stay up-to-date with current technologies and products, Microsoft requires them to pass another elective exam every year to maintain their MCSE certification.
Microsoft recommends practical experience in the subject of the exam and advises candidates to review the exam preparation guide. Other exam prep resources include instructor-led training, self-paced training, exam prep videos, official practice tests, exam replays, and community discussions.
SAS is a well-known American multinational business analytics and software services company. The SAS certification program offers several certifications, including the SAS Certified Data Scientist credential. This certification covers core topics of the SAS Certified Big Data Professional and the SAS Certified Advanced Analytics Professional programs.
The SAS Certified Data Scientist credential demonstrates a range of data management and analytics skills. To become a SAS Certified Data Scientist, candidates must pass the following 5 certification exams:
? Big Data Preparation, Statistics and Visual Exploration
? Big Data Programming and Loading
? Predictive Modeling
? Advanced Predictive Modeling
? Text Analytics, Time Series, Experimentation and Optimization
Prerequisites include a minimum of 6 months experience in SAS programming or in another language. SAS recommends at least 6 months experience in the application of statistics or mathematics in a business environment.
Exam prep options include the official SAS Data Science Certification Curriculum, which comprises 18 courses and case studies. It is available in both self-paced e-learning and live instructor-led classroom formats.
Versioned SAS credentials do not expire, but some exams may retire. According to the SAS website, "Some exams may retire as new software is developed and/or enhanced."
The vendor-and software-neutral CAP credential is managed by INFORMS, a global professional association of specialists, researchers, and trainers in analytics and operations research. This certification demonstrates knowledge of business and analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management.
Candidates are required to fulfill education and experience specifications, develop soft skills, undertake to comply with the CAP® Code of Ethics, and pass the CAP® exam. You can take the CAP® exam once your application has been reviewed and accepted.
Exam prep options include the CAP Prep course, official study guide, practice exam, glossary, exam references, the Analytics Body of Knowledge, Job Task Analysis in the CAP Handbook, and the CAP forum on INFORMS Connect. Details are available on the MyCAP section of the CAP website.
You can renew the CAP every 3 years by earning professional development units as specified by INFORMS.
The CCP-DE certification managed by Cloudera — an enterprise data cloud vendor that was named a leader in open-source Apache Hadoop platforms by Forrester Research, Inc., in Q1 2019 — is designed for data professionals with professional experience in open-source development. The credential validates the ability to obtain, import, convert, store, and analyze data in Cloudera's CDH environment.
Cloudera requires candidates to have extensive professional experience and advanced knowledge and skills in the development of data engineering solutions. Additionally, the company recommends their Spark and Hadoop Developer training course.
To earn the CCP-DE, candidates must pass the four-hour hands-on CCP Data Engineer Exam (DE575) with a passing score of 70%. Candidates will be tested on how they perform tasks on a pre-configured Cloudera Enterprise cluster.
Exam preparation options include live and virtual classroom training, self-paced study, blended learning, and on-demand training. Other resources include the Cloudera community and Cloudera's OnDemand Library.
MongoDB Certified Developer
MongoDB is a widely-used open-source and NOSQL document-oriented database program. There is growing demand for software professionals with MongoDB skills.
The MongoDB Certified Developer certification is offered by MongoDB Inc. This credential is designed for software professionals who have in-depth knowledge of MongoDB fundamentals and can design and develop applications using MongoDB.
To earn this credential, you need to pass the 90-minute, multiple-choice MongoDB Certified Developer Associate Exam (C100DEV). Exam prep options include online and instructor-led courses, the official study guide, MongoDB documentation, MongoDB presentations, the MongoDB Definitive Guide, and official practice exams.
As per information on the MongoDB website, "MongoDB certifications align to a specific MongoDB major release and they remain valid for that version."
Oracle Business Intelligence Foundation Suite 11g Certified Implementation Specialist
This certification is designed especially for intermediate-level implementation team members of the Oracle Partner Network (OPN) who sell and implement Oracle Business Intelligence solutions. Others can also take the exam, however, and attain this credential if they pass. OPN members who earn this credential will be known as OPN Certified Specialists.
The Oracle Business Intelligence Foundation Suite 11g Certified Implementation Specialist validates expertise in installing OBIEE, building the BI Server metadata repository and BI dashboards, developing ad hoc queries, and other implementation tasks.
To earn this certification, candidates are required to pass the 120-minute, 75-question Oracle Business Intelligence (OBI) Foundation Suite 11g Essentials exam (1Z0-591).
There are no prerequisites for this exam. Oracle recommends a combination of practical experience and current training as the best way to prepare for this exam. The company offers a number of Oracle training courses.
As the demand for data administrators, data analysts, and business intelligence experts continues to grow, the number of big data and analytics credentials is also increasing. Other noteworthy certifications include data science credentials from EMC, IBM, AWS, Teradata, Splunk, and Hortonworks. Also worth considering are the Data Mining and Applications graduate certificate from Stanford University and the Certification of Professional Achievement in Data Sciences from Columbia University.