Many organizations today are hoping that Big Data will take their business to greater heights. But for that to happen, the data needs to support the organizational expectations with their Big Data initiatives. Often times, the data does not meet the expectations of the users. The reasons can be many – ineffective integration of data, vague inputs from established CRM or ERP systems, mistakes by sales teams, among others. This can lead to badly targeted campaigns, inaccurate reports and more exposure to risks.
To avoid the scenarios mentioned above, businesses need to be proactive. They need to invest in effective data cleansing which will result in clear, consistent data. Data cleansing helps you take care if data defects very quickly and standardizes it to work seamlessly with all your existing systems.
Apache Hadoop offers a great way for data cleansing as part of the ETL pipeline. Apache Pig is a great add-on in the Hadoop framework which helps execute Mapreduce data processing. Essentially, it is a scripting language used with Hadoop. Pig identifies data analysis problems as data flows and allows you to do data manipulations as required. A great advantage of Pig is that it can get code in various languages such as Java, Jython and JRuby. Users can also execute Pig scripts in many languages. The language offers a great way to build complex applications that solve critical business problems.
Pig can receive data from files or other data streams through User Defined Functions (UDF). After ingesting the data, it can perform various actions on the data. It then stores the results in the Hadoop Data File System (HDFS).
e-Zest offers Data Cleansing Services with Pig. Our dedicated Big Data practice is already making Big Data work across global organizations. We are also a Hortonworks Hadoop partner and bring the best global practices to your Big Data initiatives.
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