The word big data sounds like a big thing. Big data is becoming the next big thing due to the way it is emerging and the way it is viewing, storing, analyzing, sharing, and interpreting data. Big data that was only used to be associated with human genomes is now expanding progressively and becoming a crucial part of businesses in the market today. Big data has become an important aspect of business solutions for companies all around the world. As the amount of data is growing exponentially in every sector of business, it is becoming more complex to capture, store, share, analyze, and visualize using the different available tools.
The Big Data Developer is the person who is accountable for developing Hadoop applications. They typically serve the big data needs of the company which he is employed in. He is responsible for solving the huge data challenges and needs.
The huge volume of data that is collected from different sources like motion sensors, mobile cameras, bar code scanners, web analytical tools, CCTV cameras, CRMs, and many others contains both structured and unstructured forms of data. The sheer velocity at which data is collected through different sources is exponentially exploding and it becoming quite complex to control and process data through the means of traditional tools and techniques.
However, gone were the days when big data used to be the thing for large companies, today, small companies are leveraging the collected data to remain a competitive part of the competitive landscape. Small businesses are now relying on budget-friendly tools for collecting a large pool of data so that they can take better advantage of the big data. Despite the collection of a large volume of data, its processing requires specialized software that can easily extract and process large and complex data. So, for analyzing the big data in the right competently, businesses require experienced big data developers who can solve big data problems and requirements.
The big data engineer should be able to handle the entire Hadoop process lifecycle, including the selection of a platform, designing technical architecture, analysis of requirements as well as design and development of the application, testing, and deployment. He is in charge of the actual development and development of Hadoop applications.
The big data developers are the ones who are well proficient in coding languages and are responsible for designing, building, testing, and deployment of big data applications. As the work of big data developers revolves around Hadoop applications, they are actually responsible for the coding and programming of Hadoop applications. Moreover, a big data developer is also responsible for creating high-performance and highly scalable web services for tracking the data. The skilled big data developers also work with other data specialists such as big data scientists, big data anal and big data engineers to meet the big data needs and requirements of the companies.
As big data developers deal with the large and complex volume of data, there are certain skills that one needs to master to become an experienced and successful big data developer. Big data developer skills include everything from the understanding of the different programming languages to having a special aptitude in multi-threading and knowing about the big data quarrying tools.
For becoming a professional big data developer, one needs to have good knowledge of the different programming languages like Scala, R, Python, and Java, all of which add a great advantage to the profession for the big data developer. All these different programming languages have different syntax but cater to the same purpose. Moreover, the big data developers should also be familiar with the algorithms and database structures, both of which are vital to dealing with the sheer volume of data.
Among all the skills required to become a professional big data developer, having vast knowledge about the different technologies holds a great advantage. Among the rising big data technologies, learning Hadoop prevails from all other technologies that manage the data storage and data processing for big data applications. Moreover, the big data specialists also need to have knowledge about other technologies such as SQL, NoSQL, that use different big data tools for data analysis.
An experienced big data developer should have experience in the different tools for data mining to extract, store, and process large volumes of data. This exploring and analysis of big data are important to discover the hidden patterns, customer preferences, market trends, and correlations to help businesses make better decisions. Moreover, the big data specialists also need to be familiar with the different data mining tools such as Rapid Miner, KNIME, Apache Mahout, Oracle data mining, Kaggle, and Orange, etc.
To become a specialist in big data, big data specialists need to have a good knowledge of machine learning algorithms. Machine learning accelerates the process of big data analytics that helps with decision-making algorithms. As big data includes structure, semi-structured, and unstructured data, machine learning translates this data into valuable insights that become beneficial for business operations.
As big data revolves around numeric digits, big data developer needs to have a strong command of statistical analysis of the big data. Moreover, quantitative analysis is also important to determine the statistical data. However, big data specialists need to learn both statistical and quantitative analysis skills and should have knowledge about the different tools such as SAS, SPSS, and R, etc. to solve the varying problems of big data.
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