From the tech industry to retail and finance, big data is encompassing the world as we know it. More organizations rely on big data to help with decision making and to analyze and explore future trends. For current and future software development companies that want to be knowledgeable about using data and analysis, a few big data skillsets will help give them leverage in the coming year. Whether they want a career as an app developer or data analyst, the skillsets below can help them find lucrative careers in a competitive job market.
Let’s take a look at the skillsets developers need to have.
Big Data Skillsets
From artificial intelligence and machine learning to blockchains and data analytics, big data is everywhere. Take shopping experiences, for example. A global retailer like Amazon with its same-day shipping and multi-channel services might have billions of data points across several sectors.
Gartner estimates a retail IT spend forecast of $210.9 billion by next year with $11.7 billion allocated for data center systems and $90.2 billion for IT services. And, why? Organizing massive data sets can help businesses make effective decisions in real-time. They can no longer rely on historical data alone to accurately predict shopping trends or to anticipate accurate inventory with so many changes in customer preferences and behaviors.
Businesses need software developers that can help ensure data is collected and efficiently stored. They’re looking to hire experienced data analysts, data scientists and data engineers.
With big data careers in high demand, the required skillsets will include:
Software businesses are using Hadoop clusters on a more regular basis now. Apache Hadoop develops open-source software and lets developers process large amounts of data across different computers by using simple models. Software developers can benefit from a proficiency in using this type of technology and they can find work as a Hadoop developer. They would source large volumes of data from different platforms into Hadoop’s.
NoSQL and SQL
In addressing storage needs, traditional databases like Oracle are being replaced. Developers need an understanding of MongoDB, Couchbase, and other NoSQL database types. With NoSQL and Hadoop experience, developers can work anywhere. With SQL, developers need this to help with Hadoop Scala and it’s essential for working with NoSQL.
Machine learning is a trending field and a hot topic right now. That, along with data mining can help if the developer wants to work with supply chains, for example. They can use predictive, descriptive and prescriptive analytics to help CSCOs turn metrics into insights for better decision-making.
More businesses are turning to this technology and developers that study this technology can earn high-paying salaries. Spark is an in-memory database that’s a faster alternative to MapReduce.
Statistics, qualitative analysis and quant are some of the backbones of big data. Having a background in these courses can help software developers across many industries. Knowledge of data analytics tools like SAS, R and SPSS can also help software developers find competitive and lucrative careers.
There are hundreds of different programming languages. However, some of them can give a developer more leverage than others. Take coursework in Python code, Java, Scala, a multi-paradigm, high-level programming language and C or C++. These can help a developer find a career in the data science field.
Software developers will also want to take classes in data visualization and data mining. They also need a good understanding of basic and complex problem solving and theoretical knowledge. Why? Building software requires an understanding of solving problems more so than writing code and working with new technologies. The best software developers are the ones that can solve problems.
As the need for organizing Big Data continues to expand across multiple industries, software developers will be in high demand for several years. Taking coursework now can help developers gain an edge on competitors in a demanding market that will require knowledgeable big data professionals.