With the mass adoption of IoT and cloud computing, big data has never been more important to businesses. But getting insight from large volumes of data isn't so straight forward and the right tools and people are needed.
One of the benefits of big data is the variety of jobs it creates, from niche roles with analytics to AI and machine learning specialisms, there's a world possibility for potential job seekers. At the same time, however, this is also creating a skills shortage where companies are struggling to fill digital-based positions as access to talent is in short supply.
Right now there is a demand for data analyst, data scientist, developer, engineer and other data-focused roles. However, in order to fully understand big data in a way that can qualify you for these jobs, you need both education and experience. Be it formal university studies, home learning or, if you're lucky, a secondment via a job, there are a number of ways to train in big data.
No matter which way you get into big data, it's important to have a specific focus in mind before you begin - particularly as there are many niche roles available. Luckily, there are a plethora of courses to look into. we've highlighted just a few below.
Cloudera CCP Spark and Hadoop Developer Training
Cloudera's big data course is a comprehensive guide for developers to understand how to use Spark and Hadoop to query data and gain insights into information. It's available as both a classroom-based course and online with virtual tutors, making it a very flexible option.
There aren't any prerequisites for the training, although at least a little knowledge of the Spark and Hadoop environment is recommended. Cloudera also advises that developers know how to build applications in Scala or Python and they have basic knowledge of the Linux and SQL environments.
Don’t just collect data, innovate with it.
Removing the barriers to the experience economy
Cloudera's big data course is a completely industry-agnostic programme, so anyone can undertake the training, gaining the skills they need to build data analysis tools to help their business make better data-based decisions.
During the training, Developers will learn how to build applications with Apache Spark 2 and use Spark SQL to query structured data and Spark Streaming to use real-time processing on streamed data from lots of different sources. During the course, participants will also gain experience working with large datasets stored in a distributed file system, executing Spark applications on a Hadoop cluster.
All activities take place on a live cluster, with students building their own private cluster as one of the first stages of the training.
The exam at the end of the course will test developers using real-world scenarios that will enable them to test their skills as if they were creating real applications in a production environment.
Oracle Business Intelligence (OBI) Foundation Suite 11g Essentials
If you want to go down the route of joining one of the biggest big data businesses around for its training, you could do worse than checking out Oracle's Business Intelligence (OBI) Foundation Suite 11g Essentials.
Oracle's big data exam exists to identify those most skilled in implementing Oracle's Business Intelligence Suite tools. It covers the entire process of installing OBIEE from scratch and setting it up, including building the BI Server metadata repository, BI dashboards, ad hoc queries, defining security settings and configuring and managing cache files.
This isn't a qualification for everyone - it's particularly targeted at educating Oracle Partner Network members who need to know the intricacies of the product to sell to end users and set it up. However, Oracle isn't particular about who takes the exam and it's open to anyone who wants to further their Oracle learning, or sell and deploy the technology.
CCP Data Scientist: Cloudera Certified Professional Data Scientist
Cloudera offers several big data-related certifications, but of particular interest is the CCP Data Scientist certification. It's focused on designing and developing solutions for production environments. Three exams must be passed: Descriptive and Inferential Statistics on Big Data, Advanced Analytical Techniques on Big Data, and Machine Learning at Scale. Each exam involves an eight-hour test during which the student must complete a challenge. All exams must be completed within 365 days.
MongoDB NoSQL certification
MongoDB certifications recognise developers and DBAs with the knowledge needed to build and maintain MongoDB applications. This certification programme currently has a couple of associate-level credentials: MongoDB Certified DBA and MongoDB Certified Developer. The firm offers training in the classroom and free online video training through the MongoDB University.
SAS Certified Data Scientist
The certification is designed for people who can operate and gain insights from Big Data with a variety of SAS and open source tools, make business recommendations with complex machine learning models, and then deploy models at scale within the SAS environment.
EMC Data Scientist Associate (EMCDSA)
The EMCDSA certification offers curriculum-based training and certification to provide a hands-on practitioner's approach to the techniques and tools required for Big Data Analytics. The course centres on technology concepts and principles, which EMC claims is ideal for multi-vendor, multi-technology environments. The curriculum leverages industry best practices and industry-standard terminology and definitions.
Don’t just collect data, innovate with it.
Removing the barriers to the experience economy
HP ASE - Vertica Big Data Solutions Administrator V1
This certification validates that IT professionals can manage the Vertica Analytics Platform. It also validates that candidates can perform advanced administrative tasks such as manual projection design, diagnostics, advanced troubleshooting and database tuning. According to HP, typical candidates are technical specialists with at least six months of experience in administering, managing, and operating the Vertica Analytics platform and who understand the purpose and use of the system tables. The certification requires passing an exam with 60 multiple choice questions in one hour and 40 minutes.
Big Data on AWS
This course introduces IT professionals to cloud-based Big Data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis and the rest of the AWS Big Data platform. The course shows candidates how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue.
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