Apache Hadoop, does not, unfortunately, have an inbuilt analytics capability. Or, for that matter an inbuilt Hadoop data warehouse. But Hadoop analytics are possible since Hadoop does provide a platform and data structure on which analytics models can be built. To do so, the Hadoop administrators and analysts need to be well versed in MapReduce functions and applications. That will enable them to import the input data into an analytics algorithm compatible format and voila! Hadoop analytics are now at the tip of your Hadoop administrator’s fingertips.
hadoop and data analytics
Why bother with Hadoop and data analytics, however, when so many other applications offer inbuilt analytics functions? Because Hadoop’s legacy as the original, and by far most popular database, resulted in many Johnny come lately products ensuring their products would be Hadoop compatible. Accordingly, Hadoop is the lingua franca of analytics – although challengers such as Spark seek to supplant it, offering a native machine learning library and faster operating speeds.
In spite of the challenges to the statues of Hadoop, Hadoop administrators are in high demand. Indeed, the lack of inbuilt Hadoop analytics or Hadoop data warehouse capability, means all the more work for Hadoop administrators adapting the platform for the demands of the 2020s. What skills are required of Hadoop administrators?
Well, operational expertise and troubleshooting skills, system knowledge, Hadoop specific skills such as Hadoop cluster deployment, and good general knowledge of Linux are a good starting point. Knowledge of Hadoop platform analytics however can be the clincher, as adapting the Hadoop platform for analytics tasks is an essential task of many administrators.