Hadoop – Begin your Big Data Journey
The complexity of modern analytics needs is outstripping the available computing power of legacy systems. With its distributed processing, Hadoop can handle large volumes of structured and unstructured data more efficiently than the traditional enterprise data warehouse. Because Hadoop is open source and can run on commodity hardware, the initial cost savings are dramatic and continue to grow as your organizational data grows. Hadoop can be contagious. It’s implementation in one organization can lead to another one elsewhere. Thanks to Hadoop being robust and cost-effective, handling humongous data seems much easier now.
Hadoop’s ability to integrate data from different sources, systems and file types allows you to answer more difficult questions about your business:
- If you could test all of your decisions, how would that change the way you compete?
- Could you create new business models based on the data you have within your company?
- Are you ready to harness the hidden value in your data that until now has been archived, discarded or ignored?
- What if you could drive new operational efficiencies by modernizing ETL and optimizing batch processing?
Major Benefits of Hadoop are:
- Faster Data Processing – Hadoop excels at high-volume batch processing. Because of its parallel processing,
- Get More from Less – The true beauty of Hadoop is its ability to cost-effectively scale to rapidly growing data demands
- Robust Ecosystem – Hadoop has a very robust and a rich ecosystem that is well suited to meet the analytical needs of developers, web start-ups and other organizations.
- Hadoop is getting “Real Time” – Hadoop also provides a standard approach to a wide set of APIs for big data analytics comprising MapReduce, query languages and database access, and so on
- Hadoop is getting cloudy – cloud computing and Hadoop are synchronizing in several organizations to manage Big Data