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. Additionally, Hadoop has a robust Apache community behind it that continues to contribute to its advancement. Hadoop offers a proven solution to the modern challenges facing legacy systems, but the initial steps to implementing a big data strategy can be daunting to any organization. Having gone through the pain points of implementing Hadoop in a traditional enterprise at our Fortune 100 parent company – and replicating that methodology and success with other customers – NodeLogix delivers the unmatched experience to help you modernize your data storage and analytics capabilities quickly. With the enterprise data warehouse approach, organizations find their data scattered across many systems and silos. This decentralized environment can result in slow processing and inefficient data analysis. Hadoop makes it possible to consolidate your data and business intelligence capabilities within an Enterprise Data Hub. The ability to save all organizational data at its lowest level of granularity and bring all archive data into an Enterprise Data Hub gives business users greater and faster access to data – resulting in deeper analytics using more data points.