How can Big Data Make You Employable?

Big Data is a term that refers to the huge volume of data gathered from different sources available in today’s world. It includes structured and unstructured information from many sources such as social media, applications, websites, sensors, transactions and more. Big Data Analytics focuses on gathering data to uncover patterns within the data that can be used to make business decisions. It provides a better understanding of customers so marketers can identify their needs quickly. It also helps companies predict customer behaviors and preferences thus enabling them to present products at the right time according to customers’ interests. In this infographic, you get an overview of Big Data; understand how it makes you employable by providing tips covering career paths, technical skills or personal skills required for jobs in big data analytics.

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Programming Languages for Big Data

Big data analytics requires the use of specific languages to process and analyze large data sets. Here are some popular programming languages used in big data analytics:

R is a free statistical package used in the big data processing. It has its own environment which means you need RStudio to run it on your computer. Python’s Numpy, Scipy & Matplotlib packages are very similar to R with an interactive interface that offers support for visualization and analysis of large amounts of structured and unstructured data. Java is one of the most widely used programming languages with good support for data analysis. It is an object-oriented language that makes it easy to read, write, maintain and reuse the code. You can deploy Java for use in big data analytics. Scala is an object-oriented programming language used by developers to create scalable applications with high availability. Hadoop requires Java skills so you need to learn Java before moving on to Hadoop and other Map-Reduce frameworks. For a depth understanding of Big Data and its complete concept, enroll in our course offered in classroom or online training mode.

Professional Certifications for Big Data Analytics

There are many ways you can stand out against your peers when applying for jobs in big data analytics: Certification demonstrates that the candidate has industry-ready skills required to succeed in a particular job role. 

Here are some important certifications:

• Cloudera Certified Professional (CCP) certification is for IT professionals who want to build and support Hadoop clusters on the enterprise infrastructure. It provides valuable knowledge of Apache Hadoop, its components and related technologies such as Cloudera Search, Cloudera Impala and Cloudera Hue used in data discovery, ad hoc querying and business intelligence application development. Big Data Analytics Foundation Certification is an industry-trusted certification program offered by Big Data Council to develop professional skills required for different roles in big data analytics. This foundation level certification focuses on understanding what’s behind all the hype around big data, where it can be applied, the importance of key concepts like analyzing large sets of data, cloud computing and more.

Professional Certifications for Big Data Analytics Professionals

Big data professionals are always in demand as almost every industry deals with large volumes of structured or unstructured data that need to be processed fast to draw any useful insights out of them. This can only be possible through the right tools, techniques and experts who have the skills required to process it. Here are some professional certifications you should aim for: Certified Data Scientist is an information technology certification offered by Big Data Council to validate your competency in different concepts related to big data analytics like machine learning, statistical analysis, visualization etc. Certified Hadoop Administrator Certification is a valuable credential for administrators who want to Hadoop on premise or private cloud infrastructure. Certified Big Data Developer is a certification that helps developers to develop, implement and maintain big data solutions using the Hadoop framework on cloud or converged infrastructures.

Professional Roles in Big Data Analytics

The field of big data analytics is growing at a fast pace with businesses trying to outdo each other with better analytics tools and techniques for monetizing their huge volumes of collected information. This has created numerous job opportunities across different roles in big data analytics: 

Here are some professional roles in the big data industry:

• Data Analysts need to manage analyze and interpret large sets of complex data into meaningful insights that can help customer relationship management or improve marketing strategies, etc. Business Intelligence Analyst is responsible for analyzing business trends through various reports, building complex queries, consolidating data from multiple sources for business intelligence.
• Data Architects are responsible for designing the strategies of how to store, access and process big data using different storage technologies etc. Data Engineer is responsible for handling tools like Map-Reduce used to process large sets of data connected through a distributed file system i.e. HDFS or other PaaS technologies such as Google App Engine, Microsoft Azure etc.

Conclusion:

In conclusion, big data is a vast field and it’s growing at a rapid pace with the need for professionals who have the technical skills required to make sense of large sets of information. This has given rise to numerous job opportunities in different roles along with professional certifications that can help you stand out from the rest and secure your dream job.