The emerging realm of IBM Big Data certification
It should come as no surprise that IBM is a major player in the Big Data marketplace. The venerable corporation’s nickname is “Big Blue,” and its early focus on mainframes and large servers was referred to as “Big Iron.” Moving into Big Data was pretty much a marketing identity must-have.
IBM’s Big Data product portfolio has grown impressively under the watchful eye of the company’s current CEO Ginni Rometty. The century-old technology company has had the computing power to support Big Data platforms for quite some time, thanks to initiatives like Watson, a cognitive computing platform built on machine learning and natural language processing.
A recent eWeek story story noted that over a third of today’s Big Data developers are using machine learning in their projects. IBM’s Watson has been a pioneering project in machine learning for several years, which gives the company a foot up in the Big Data industry.
Where IBM’s product management leads, its Professional Certification Program follows, with new training and credentials based around the company’s most relevant products. The program has established an IBM Big Data & Analytics certification category to cover its Big Data endeavors.
IBM’s Big Data & Analytics certification program is currently made up of three credentials, which are based on well-defined job roles. Let’s take a look at these three certifications, and at what sets them apart from each other.
Solution Advisor – Big Data & Analytics v1
IBM Certified Solution Advisor – Big Data & Analytics v1 is a designation created for people who have exceptional knowledge of Big Data and how it can fulfill business requirements and improve older data solutions. A person in this job role must be able to describe to customers and potential clients what Big Data is, and how it can benefit their organization.
This certification is earned by passing the C2090-136 exam: Foundations of IBM Big Data & Analytics Architecture V1. This exam consists of 58 questions, which candidates are given 90 minutes to complete. The passing score for the exam is 70 percent.
Here are the knowledge domains covered by the exam:
● Big Data & Analytics Benefits and Concepts
● Big Data & Analytics Design Principles
● IBM Big Data & Analytics Adoption
● IBM Big Data & Analytics Solutions
● IBM Big Data & Analytics Infrastructure Considerations
● IBM Big Data and Reference Architecture
Training for this certification is available through several formats, including a two-day live instruction boot camp and several online books and publications.
Certified Data Architect – Big Data
IBM Certified Data Architect – Big Data is an advanced certification for IT pros who are asked to take the outcome of a collaboration between a client and an IBM solutions specialist, and use these findings to design an actual living, breathing system. IBM Big Data architects fashion Big Data solutions that fulfill the business requirements of the client, and meet any relevant governance standards for security and privacy.
This credential is earned by passing exam C2090-102: IBM Big Data Architect.
Candidates must answer 55 questions in 90 minutes when taking this exam, which has a passing grade of 60 percent. Here is a list of exam sections, with an estimate of how much exam content is in each section:
● Requirements (16 percent)
● Use Cases (46 percent)
● Applying Technologies (16 percent)
● Recoverability (11 percent)
● Infrastructure (11 percent)
The advanced nature of this certification means that candidates need a great deal of real-world experience before challenging the exam. There is also web-based training and instructor-led classroom training available that covers many of the associated Big Data products from IBM.
Certified Data Engineer – Big Data
IBM Certified Data Engineer – Big Data is another advanced certification designed for IT pros who build the solutions designed by Big Data architects. If you think of it in terms of houses, Big Data engineers are the carpenters, plumbers, painters, and electricians who use hardware and software to build the structures found in the Big Data architect’s blueprint.
Like IBM’s other Big Data certifications, the Data Engineer credential only requires passing a single exam, C2090-101: IBM Big Data Engineer. This exam has 53 questions, with a maximum time limit of 75 minutes. The passing score for the exam is 65 percent.
The exam is split into the following sections (includes an estimate of how much exam content is in each section):
● Data Loading (34 percent)
● Data Security (8 percent)
● Architecture and Integration (17 percent)
● Performance and Scalability (15 percent)
● Data Preparation, Transformation, and Export (26 percent)
Generally speaking, the Big Data engineer job role is not as high-level as that of the Big Data architect, but it is still a very challenging career path. Big Data engineers must be hands-on experts with a wide array of hardware and software products. In some companies, Big Data engineers don’t just build the solutions; they are also the ones who perform the initial qualification and gathering of data to be passed along to others for analysis.
As with the other two certifications, there are several training options available for the IBM Big Data Engineer credential, including web-based courses and classroom instruction.
Three Job Roles, One Goal
Big Data, like other IT disciplines, can be split into a multitude of specialties depending on how much job granularity is desired. IBM has gone the other route by creating three certifications that cover the primary Big Data job roles.
The IBM Big Data solutions advisor acts as a trusted partner to a client, providing foundation-level knowledge of the technology in order to show how it can provide for an organization’s real-life needs. The IBM Big Data architect takes what the client wants to achieve, and designs a solution that will deliver on the promise. And, the IBM Big Data engineer rolls up their sleeves and grafts hardware and software together based on the architect’s plan, bringing the solution to life.
Three distinct IBM job roles that all work towards a common purpose. It’s a tidy solution from a company that has been at the forefront of creating solutions for more than 100 years.