Big data is all about what organizations do with the massive amount of data collected on a day-to-day basis. The data gets collected at a faster rate in varied forms and large volumes. It is used by organizations and businesses to discover patterns and trends to understand human behavior. It helps to know how humans interact with technology, what products or information he consumes, and many more. These data are further used to make decisions for human benefit and profit.
Scientists, medical practitioners, governments, advertisers, marketers, and businesses are using big data. The ability to slice and dice big data facilitates predictive analytics and user behavior analytics. The companies need the best talent as a big data job involves analyzing data, extracting systematic information, and dealing with large or complex datasets.
The analytics industry has grown to $3.03 billion in size in 2019 and is expected to double by 2025 as per Analyticsindiamag.com reports. Big data specialists will be trending by the year 2022 according to the World Economic Forum. The Dice 2020 Tech Job Report labeled data engineer as the fastest-growing job in 2019 with a 50% year-over-year growth in the number of positions.
Big data has made the industries highly competitive and opting for a big data career will give you the right up thrust to stay ahead in the job market. It is one of the most lucrative tech markets to date with companies competing to recruit the best talent.
To get into the big data career path, start with the following steps.
Big data career path
A career in big data makes you an elite professional. To embark on your journey into big data, start from learning the skills.
Learn basics and new skills:
Invest in yourself and your career. Gain a stronghold on basics by understanding what and why in big data. It includes learning of Hadoop and Spark too. Continuous learning is recommended to keep yourself abreast. Earning top big data certifications is one of the best ways to stay updated. It helps you gain in-depth learning of the subject and recognition.
It helps you fill the necessary skill gaps and positions you for future success in a big data career. A certified big data professional is preferred to fill the competent jobs or get promoted in any organization. You can opt from various top big data certifications as per your core interest.
You must get well acquainted with at least 2-3 programming languages. It depends on the use case. For instance, if you are interested in hardcore data analytics with a lot of statistical computing, learning ‘R’ is best recommended. Likewise, if you want to use machine learning to build predictive models, then you should learn ‘Python’.
Popular languages with use cases are summarized here.
· Scala is preferred by many big data professionals as it is fast and robust. Learning Scala is worth it when you work with big data tools like Apache Spark for distributed big data processing.
· Python integrates effortlessly with big data frameworks like Apache Hadoop and Spark. It facilitates you to perform predictive analytics at scale.
· R supports Hadoop and Spark. If you are into statistical modeling and visualization, then R is a must for you to learn.
· Java is used to develop big data applications. It enables you to use a large ecosystem of tools and libraries for monitoring, interoperability, and much more.
· Businesses prefer ‘Go’ to build data analysis systems and operate at scale. If you are integrating machine learning and processing data in parallel, then you must learn ‘Go’.
Job roles and skills:
There are many job roles in big data. It is essential to choose a role that interests you and learn the skills necessary for it. There are multiple roles in big data to choose from. A few of them are introduced here.
Big data analyst
As a big data analyst, it is necessary to have a working knowledge of key technologies like Apache Hadoop, Pig, Hive, Statistics, and algorithms.
Big data architect
Big data engineer
A big data engineer must know data architecture, SQL, data warehousing, ETL, Hadoop-based analytics, machine learning, coding, and operating systems.
As a data scientist, one has to have in-depth knowledge in the Hadoop ecosystem, perform queries against stored data, extract data, wrangle data, and more.
Apart from the aforementioned job profiles, other demanding professions include data visualization developers, machine learning engineers, business intelligence engineers, business analytic specialists, and big data developers.
Business and communication skills
As you step up in your big data career, you will be playing a significant role in strategy and planning. You may have to spend more time in meetings with people who are not from a technical background and talk business. so, it is critical to developing business and communication skills. You should be a good big data storyteller so that non-tech people can communicate and understand the value of data for business. it is recommended to join groups, improve presentation skills, and continuously track progress. Keep yourself updated with the industry knowledge for continued success.
This article has been published from a wire agency feed without modifications to the text. Only the headline has been changed.