Critical success factors in deploying Hadoop across industries
Hadoop advantages stretch beyond high-volume data processing. The advantages and cost-effectiveness of Hadoop have become so readily apparent that it is quickly becoming a familiar entity within data-driven organizations. Enterprises of many sizes and in a wide range of industries are using it to distill insight from big data and gain a competitive edge.
Besides its ability to combine data types, Hadoop enables impressive performance advantages. Hadoop runs fast because it incorporates parallel processing techniques to distribute processing across multiple nodes. It can also process data where it is stored, rather than having to transport data across a network, which speeds up response times.
Hadoop can help lower IT storage costs, because it can access data from clusters of industry-standard servers rather than high-performance systems. These standards-based clusters also provide less-expensive methods for high availability compared to data warehouse alternatives. Additionally, IT can purge data from operational systems and keep it in near-line data sources until needed for analysis, further reducing costs.
Hadoop has advantages for business users as well. With the development of high-level scripting languages, similar to SQL query languages, in its latest implementations, Hadoop is now easier for less technical users. And because it avoids the need for static database schemas, users can evolve data structures easily. At the same time, Hadoop enables rapid prototyping that enables businesses to iterate more quickly and bring new applications to market faster.
This ebook highlights the benefits of Hadoop across several industries and explores how IBM InfoSphere BigInsights combines open source Hadoop with enterprise-grade management and analytic capabilities. In this ebook you will learn how several industries are making use of Hadoop:
- Healthcare: Improving clinical treatment effectiveness, building sustainable healthcare systems, detecting claims fraud.
- Financial services: Improve customer insight, better manage risk and detect fraud, increase flexibility and streamline operations.
- Energy and utilities: Operational efficiency, customer sentiment analysis, weather data analysis.
- Telecom: Customer churn prevention, network usage analysis and optimization, new product innovation.
- Automotive and manufacturing: Increased customer satisfaction and retention, product quality control, supply chain optimization
Download "Making the case for Big Data and Hadoop in the Enterprise" today for the full scoop on Enterprise-grade management and analytic capabilities.
Also, be sure to check out the Big Data for Social Good Challenge (#Hadoop4good), a global hackathon where developers compete to create innovative solutions using Hadoop that solve civil and other real world social challenges. It’s open, fun and there are big prizes too.