Big Data is a huge volume of structured, semi structured, and unstructured collection of data which is growing rapidly. Such data is so gigantic and complex that it cannot be processed from any traditional data management tool. In order to effectively manage the ever-increasing volume of unstructured data, companies demand for data analyst & data scientist.
Over the last 5 years, the role of a data analyst has significantly evolved from being a data miner to complex problem solver. Presently, large business models like Netflix & Walmart rely upon data intelligence. The primary responsibility of a data analyst is to collect, analyze, and interpret Big Data to improve a company’s operation.
Though data analytics has become most critical for the businesses, there remains a shortage of required skills for this position in the market. You can avail this opportunity to gain higher paychecks by learning the necessary skills in Big Data. We in this blog will evaluate the main reasons for the demand of Data Analysts and how you can build a career in Big Data.
Why is there a need for Data Analyst?
The amount of data that today’s businesses are generating and collecting, is greater than ever. Companies collect data to get a better understanding of their customers. It is done by closely reading the collected data, thoroughly identifying correlations & interpretative patterns to draw useful information. For this purpose, companies look for professional data analysts who are proficient in organizing big data.
Let’s have a look at the reasons that led to the increase in demand of data analysts:
- Surge in Data Generation- Data is generated in bulk at every hour of the day. Whether someone searches on Google or shares an Instagram post or purchase something online, each activity generates a heap of data which needs to be stored and managed.
- Useful for Marketing Purpose- The modern-day customers are demanding and have plenty of options. So, in order to understand their unique needs and improve the quality of services, businesses hire data analyst who can help them in getting an insight of consumers wants.
- Increase in Internet-Connected Devices– There are around 31 billion IoT devices across the world. It surrounds our lives to a large extent from personal to professional realm. Following are the most-common internet connected devices:
- Desktops, computer servers, laptops, monitors, hard drives
- Smartphones, tablets, smart-watches
- Security systems, locks, home alarms
- Refrigerators, dryers
- Voice-activated speakers like Siri or Alexa
- Light switches, thermostats, Wi-Fi modems and routers
- Streaming and gaming devices like TV, play station
The technology experts of Internet of Business anticipated that we’ll have 125 million cars connected by 2025. With more devices connected to the internet, the more data will be generated; hence, there will be more demand for people who knows to interpret data.
Scope and Future of Data Analyst
- IBM claims that the annual demand for data analysts, data scientists, data developers & engineers will lead to 700,000 new hiring by 2020. Also, the number of jobs for the US data professionals will rise by 364,000 openings.
- Data Science and Analytics (DSA) jobs remain open for 45 days, which is five days longer to find qualified candidates than the market average.
- DSA job demand is predominantly created in IT, Professional Services, Finance & Insurance sectors.
- The most lucrative data analytics skills are Apache Hadoop, Apache Pig, MapReduce, & Apache Hive.
- Top Companies in the US earnestly look for data analysts offering high salaries as shown below:
Undoubtedly, salary is one of the major factors in searching for data analyst jobs and decide what is the next big gig. The more experience and skills you gain in the career field of data analyst, the more lucrative options you get.
Which is the most popular coding language for Data Analyst Job?
70% of data scientist and data analysts use Python as their primary coding language. It is the most used programming language that help data analyst to increase their skill-set.
As employers are looking for competent data analysts with well-rounded knowledge of SQL & Spark, knowing Python will only provide you an added benefit.
Skills required to be a Data Analyst
- People with a mathematical background usually do well as a data analyst. Besides, if you are competent in stats, this career is the best-fit for you.
- Data analysts must possess remarkable coding skills along with the knowledge of technologies like Hadoop and coding languages Python.
- Data analysts should also have the ability to translate data graphically for the business audience.
- Efficient data analysts have the skills to dig through a pile of data and make connections. So critical thinking is a key factor for data analysts and data scientists.
- Soft Skills are equally important for data analysts to illustrate the value of their thoughts and articulate their findings to the business people.
Considering the rapid growth of Big Data, one can determine that the demand for data analyst and data scientist will continue to increase. Those looking to build data analyst career are likely to find opportunities across various industries from healthcare to technology, media, finance, automotive, or aerospace. However, becoming a data analyst doesn’t happen overnight.
You need to have a comprehensive knowledge of latest technologies, programming languages & computer systems. Additionally, you should learn to use software analysis to work with Big Data, research on-going market trends, & future jobs for data analysts.
Many career advancement options are waiting for those with the right skills. Enroll into our Big Data-Hadoop training course to learn core concepts of the Hadoop framework including Apache, Hive, MapReduce, & HBase.
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