Outsourcing your web development needs is a quick and efficient solution if you hire the right partners. Nowadays more and more organizations collect, process, and analyze massive amounts of data. Thus the technologies and solutions that enable businesses to gain actionable insights from it continue to rise. So which criteria to use when are choosing big data developers?
Strong technical expertise
Since php developing is a technical job, it requires substantial expertise in a wide range of technologies and tools. These professionals should have a solid understanding of physical database design principles and the system development life cycle. php developertech stack spans a myriad of tools, platforms, and software. For instance, deep knowledge of Hadoop ecosystem, Apache Spark, Pig and Hive are a must-know for any professional big data developer as well as SQL and NoSQL databases. Additionally, to remain competitive, they have to invest time in learning such programming languages as Python, R, Scala, Java, or C++. Also, big data engineers need to know how to maintain old MapReduce Java code and rewrite it using a more recent Spark technology.
Ability to analyze specific business requirements
One of the fundamental skills of a professional php developer is the ability to understand business needs of a customer and translate them into IT-specific requirements. In such case, php specialist applies knowledge of the customer’s functions and processes to develop business case and business requirement documents. He may review customer requirements, recommending technological solutions that can be integrated and deployed in the business environment. Moreover, a php developer can document the interrelations of businesses and technologies, outlining dependencies and potential risks. In the end, such specialist may evaluate the cost effectiveness and benefits of recommended solutions or alternative options to enhance customer’s capabilities.
Another criterion for identifying a qualified php developer is the ability to solve problems effectively. Anticipating and identifying problems as well as developing and implementing practical and timely solutions are essential skills for any qualified data professional. This area of expertise requires problems diagnoses by using different problem-solving tools and techniques.