The increasing amount of customer and other related data is helping companies to improve their customer experience and provide better customer service. Companies are sourcing data from various platforms including social media, customer relationship management systems (CRM), call logs, etc. to get an insight into their customers. Professionals who can use this data to derive insights and help companies make better use of this data are in demand, but are in acute shortage.
This provides an opportunity for tech professionals as well as beginners to start a career in Big Data. And with lucrative salaries and ample growth opportunities, Big Data career is a no-brainer choice for graduates looking to embark on a tech career.
What is Big Data?
Successful and progressive organizations have relied on data for decision making for a long time. However, in the past few years, the amount of data generated by organizations has been unimaginably huge due to the penetration of the internet and mobile phone in daily life. This requires companies to equip themselves with data systems that can track every customer activity and record them, filling systems with petabytes of data.
Organizations are using distributed storage systems to store this data. As the number of data increases, companies can add new layers of systems. This allows them flexibility and the ease to scale their operations. Analytical systems can further operate on distributed systems and facilitate parallel processing. In simple words, Big Data is a record of customer activities that require distributed storage and parallel processing.
Big Data technology
As a Big Data professional, you are expected to learn a gamut of technologies. Here are some frameworks you are expected to know. This is not a long list, so feel free to add other tools and technologies.
Big Data Frameworks
1. Apache Hadoop – This is a common framework for parallel data processing and distributed data storage.
2. Apache Spark – This is another parallel data processing framework
3. Apache Kafka – This is a stream processing framework
4. Apache Cassandra – This is a distributed NoSQL database management system.
Working with Big Data requires knowledge of a few programming languages —
Working with Big Data requires knowledge of programming. As a beginner in Big Data, you are expected to understand the difference among programming paradigms — declarative, imperative programming, and Map Reduce paradigms.
- Imperative programming – This is the approach where commands should be present to change its state. Backend programming is a primary example of this approach. Java, Python and other backend programming languages use this approach.
- Declarative programming – This is the approach where tasks are declared with the expected output. This approach is common in programming languages like SQL.
- Map Reduce paradigm – This allows parallel processing of distributed data. Using this approach enables data filtering, sorting, parameterization, and summarization of interim results using reduce function.
Big Data jobs
Big Data is an immensely large field with a plethora of job options. Popular roles in this field include —
1. Data Analysts – This an entry-level role that requires hands-on experience on the tools mentioned above. Strong mathematical and analytical aptitude is required for this role.
2. Data Scientists – These are the most sought professionals. They require strong problem-solving skills and in-depth knowledge of analytics, machine learning, and more.
- Data Architects – These are architects of data infrastructure and look after databases and ensure they are operational at all times and stakeholders receive data as and when required.
- Database managers – They organize and maintain databases of organizations.Getting started in a Big Data Career
Demand for Big Data professionals in the industry has been constantly growing, leading to an increase in online courses and big data certifications worldwide. Some courses offer a way to break into the industry for fresh graduates, others offer a convenient and flexible way to learn at home for seasoned tech professionals and transition to a Big Data career.
In a nutshell, Big Data certifications are available for anyone who is aspiring to make a transition. If you’re already in a Big Data career, top Big Data certifications will add more value to your experience. Some popular certifications in the Big Data industry include DASCA, Cloudera, Dell EMC, among others.
Additionally, for fresh graduates pursuing a master’s program at universities is a good step. Master’s programs tend to be long and can take up to 2 years to finish. A few universities have also come up with a bachelor’s program in Big Data, looking at the shortage of Big Data professionals.
Big Data careers are rewarding in terms of salary and opportunities worldwide. As the field is now acquiring the right set of skills and valuable credentials for proven expertise helps to move ahead in the career.