“Information is the oil of 21st century and analytics is the combustion engine” ~ Gartner
Big data is the new oil and there’s no denying to this fact. In certain ways the analogy fits, it is easy to draw attention about how information (data) is used to power much of the transformative technology that we see today such as predictive analysis, automation and artificial intelligence etc.
As technology move towards the businesses domain, many organisations are drawing their focus towards data-driven decision making. Many organisations and firms are considering big data mainstream today. And they’re looking for ways to improve and research new tools and models to help improve their big data utilisation. Also, most organisations are now claiming that they are data-driven, making decisions based on data and not figures mentioned in reports.
Currently, the job market has twice the number of jobs than job seekers, indicating an urgent need for professionals in big data. With more jobs becoming data-driven, companies and organisations are now looking for skilled professionals in technologies such as big data, AI and machine learning.
The primary reason behind the shortage of talent is because the kind of skills that organisations and companies need are higher order data skills which are missing in most professionals. What these candidates learn in college is not in sync with the current industry trends. Things have changed and there are many different opportunities aligned in the market, but without having the right skills it is going to be very difficult for one to stay relevant in the current industry.
This is where there is a dire need for professionals to re-skill themselves to stay updated in the job market.
According to SharePost’s second annual survey of IT professionals, the growing demand for the global market of data analytics and business intelligence services may boost revenues north of $200 billion in 2020. Also, more than 150 zettabytes (150 trillion gigabytes of data) will need analysis by 2025, so you can imagine the number of data professionals needed then.
Candidates in big data have a higher potential of earning lucrative compensation and are upskilling themselves with the skills required to secure these positions. Now if you’re thinking of upskilling yourself you need to become a big data certified professional. One also need to take note that professionals who are able to showcase these skills in the form of certifications and credentials are highly valued than the ones who don’t. If you’re looking to have an edge over others then taking up a big data certification is a great way to prove your potential capability to employers.
If you wish to become a certified big data professional then these are five great big data certifications you cannot afford to miss:
Hortonworks Certified Associate (HCA)
The Hortonworks Certified Associate (HCA) certification provides a credential that validates whether an individual understands the technology or not. They also help validate and recognise the business used cases for the Hortonworks Data Platform (HDP) frameworks. A test is conducted and the candidate must pass a multiple choice exam consisting of different topics such as data access (Pig, Hive, Scala, Storm, Spark etc), data management (HDFS and YARN), data governance and workflow (Atlas, Falcon, Kafka, Hortonworks data flow etc), operations (CloudBreak, ZooKeeper, Ambari etc) and security (Ranger and Knox).
Cloudera Certified Professional (CCP): Data Engineer
The Cloudera Certified Professional (CCP): Data Engineer provides the certification and helps one with the ability to perform competencies that are required to transform, store and analyse data in Cloudera’s environment. One needs to get through the exam which is the remote-proctored CCP - Data Engineer exam. In this exam, the candidate is given five to eight customer related problem for which a technical solution must be implemented by the candidate.
Data Science Council of America (DASCA) for Big Data Engineering Professional
The Data Science Council of America (DASCA) for Big Data Engineering Professional provides the credentialing framework that most organisations look for when hiring. Since it is quite difficult for an employer to believe the skills the candidate possess it is important that one needs to showcase their skills through the credentials that one acquires. Professionals learning from here are said to have made 40-50% higher compensation than the usual candidates. The skills you get to learn covers data science, big data, data processing, Hadoop, Pig, Hive, Yarn, decoding sqoop and flume, big data analytics, R, Python, and Deep learning etc.
You then need to undergo an examination after which you will be awarded a digital badge (credbadge) showcasing that you’re the perfect candidate for that particular employer.
HDP Certified Developer Big Data Hadoop
The HDP Certified Developer Big Data Hadoop certification helps validate a candidate’s proficiency in Hive, Pig, Flume, and Sqoop. The exam that is conducted comprises of a series of data ingestion, data transformation and data analysis tasks that are performed on an HDP 2.4 cluster.
You can take up courses on Hortonworks website with options such as live training, self-paced e-learning etc.
SAS Certified Big Data Professional
The SAS Certified Big Data Professional is a certification for individuals who are seeking to build basic programming language by learning how to gather data and analyse it in SAS. This certification program focuses on SAS programming skills such as accessing, transforming, manipulating data, improving data quality for reporting and analytics. Topics such as fundamentals of statistics, Hadoop, Hive Pig, data visualization is covered.
Once the candidate completes with the learning he/she needs to go through two certification exams, both of which the candidate must pass.
Having the right certification will help since these skills are high in demand and professionals with cutting edge technologies have better job opportunities.