If you are a programmer and you want to get into world of analytics, up your sleeves and get ready because there are a lot of exciting opportunities and really good work out there for you!
Programming is not just done for building products. In the world of Big Data, Programming is required for Handling Big Data Sets, making sense out of data, getting answers for what and why of the trends/incidents and to smoothen the whole process of doing data analytics.
Let’s see some examples on how programming comes handy in different analytics scenarios.
Let’s say bank ‘ABC Bank’ has millions of Credit Card customers in North America. The data which is generated every day for this bank has billions of records, stored efficiently in Hadoop clusters across multiple physical locations.
To make a summary like how much was the total payout done by customers in last 2 payment cycles, distributed across region and segmented by the category of Credit Card types, a programmer has to have good skills in Handling big data, ability to work with Hadoop, ability to write efficient queries (because a naive query might take hours just for a dataset sort) and he should be able to automate the whole process, if it’s a regular requirement to generate such a metric.
Let’s take another example of data analytics, where a programmer needs to find out cause for an event by digging in the data and take precautions to tackle the situation. : Say the same ABC bank, who has millions of customers in North America, is hit by a natural calamity like a cyclone, which affected almost whole of North America badly. Obviously, the credit card consumers will care the least about making their payments when they are suffering such a disaster. So there is a need to predict the loss ABC bank will suffer because of this disaster, which can be in order of billion dollars. This task will not only involve applying analytics techniques, but also working with data of huge sizes and types. Querying and modelling of such data will require good programming skills in JAVA, R, and SQL etc.
Such an exercise involves a brilliant combination of Programming skills, optimised queries, Statistical tools and techniques knowledge and reasoning capability. Now, for someone from programming background, it might be a comfort zone to be able to use these technologies to write efficient queries and to play with data with more ease.
Even though there is a lot of complex querying and basic programming for automation involved in performing data analysis, the scope for developing complex algorithms, system level coding using C, C++, OS level coding etc is minimum.
However, analytics is a vast domain and there are loads of tools and technologies that are evolving. Hard Core programmers can look at application development for various analytics requirements. Applications like Pig, Hive, HBase, Impala and many more have been developed on the Hadoop framework for supporting various analytics needs. Programmers can also contribute by building different statistical packages for R which is an open source programming language for analytics.
Also, in today’s world of big data, where almost 80% of data available is unstructured in the form of audio/video/image/text, there is immense scope for research and application development for storing, processing and extracting useful information from such data. Many start-up companies have emerged, working towards building tools specifically for processing unstructured data.
We can confidently say that there is really good scope for programmers in the field of Analytics. In the field of big-data and analytics tools development, you will be required to have good expertise with JAVA, Hadoop, implementing algorithms etc. In data Analytics, the programming platforms and tools generally used are SAS, R, SPSS, SQL etc. For automation purpose, .net, java, ruby, python might also be required.
Originally posted on Silicon India Blogs.
Image credit: www.freedigitalphotos.net By Stuart Miles
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