Big Data is big business. More than three-quarters of business executives already recognize that failing to embrace Big Data could mean losing their competitive edge. For those who understand how to work with it, that translates to a substantial career opportunity.
Whether you're thinking of becoming a Machine Learning Engineer you want to be able to harness the power of Big Data as part of your career in development, architecture, or programming, learning the fundamentals of Hadoop and how to use it is essential. Learn more about what Hadoop is, its history and how to use it in this quick guide.
What is Apache Hadoop?
Hadoop Big Data isn't the same thing as Big Data. On its own, Big Data is an asset. It's a complex and ever-growing flood of information. Hadoop is a type of open-source software with the framework needed to interpret the immense volumes of information running through it. It's an offshoot of Nutch, an open-source web search engine created by Mike Cafarella and Doug Cutting to return web search results quickly and more accurately. It was in development at the same time as Google and based on a very similar concept: processing and storing data automatically to return the most relevant search results faster than ever. When Cutting moved to Yahoo in 2006, he brought Nutch with him. Nutch was divided into the web crawler and the computing and processing portion, which was christened Hadoop in 2008. It's managed and maintained by Apache, which is a foundation comprised of a community of developers.
Importance of Hadoop
As Big Data becomes increasingly important, so does Hadoop. It enables users to store and process large volumes of data of all types with speed and flexibility. Because it's open-source software framework, it's free to use, which makes it a low-cost option. Adding nodes allows users to grow their system quickly to scale up as needed to accommodate growing data streams.
How to Use Hadoop
When it was initially released in 2008, Hadoop's goal was merely to search the millions of web pages available to provide the most relevant search results. Today, it's an exciting platform for Big Data. Common ways to use Hadoop include:
- As low-cost data storage
- To run analytics that uncover new business opportunities and operational efficiencies for increased business advantage and innovation
- As a data lake, which stores data in its original format for analysts to view
- To complement the data warehouse by storing and processing data of various formats
Why Learn Hadoop?
There are many valid reasons to learn Hadoop and its unique programming language. It's powerful, flexible, and versatile, allowing you to store and process immense volumes of data, warehouse it, and use it to complete discovery and analytics. Hadoop is also among the chief skills employers are looking for in the Big Data field. Administrators, data scientists, developers, and architects — anyone working with Big Data would benefit from cultivating this skill set, which may very well be a requirement for anyone working in the field sometime in the near future.
If you're interested in artificial intelligence, machine learning, or Big Data, learning Hadoop provides an excellent foundation for the skills you need to succeed. Begin your future now with a Udacity Nanodegree program.