The State of Hadoop for the Enterprise Market
Hadoop’s presence in the enterprise is unstoppable. Its unique approach to data management is transforming how companies store, process, analyze, and share big data. According to estimates from analyst firm IDC, The big data market is predicted to be valued at $100bn by 2020, and half of this will be driven by Hadoop. As volumes of business data continue to increase, organizations are rapidly adopting Hadoop to store, manage, and process Big Data for use in analytics, business intelligence (BI), and decision support. Industry experts believe that the size of Hadoop installations will grow significantly as companies incorporate new data sources and business applications. In addition, enterprises that leverage Hadoop to support Big Data initiatives will gain quicker and better insights into their customers, operations, and business environment.
Business and Technology Challenges
Hadoop holds a great deal of promise for organizations, but as an emerging technology, challenges exist when using Hadoop for BI, analytics, and decision-making.
- Data integration is time-consuming
Based on article published in The New York Times on Aug 17 2014, today, data scientists may spend as much as 80 percent of their time on “data janitor work”, collecting and moving large volumes of data, before it can be explored for useful nuggets. Because Big Data is heterogeneous by nature, enterprises must find fast and cost-effective ways to move information from many different sources into the Hadoop system.
As analysts are freed from the constraints of specific data structures and volumes that limit their queries, they can ask new, different and more intuitive questions of the data, with a focus on what might be profitable.
- Real-time analytics are hard to achieve
A major use case for Hadoop has been in the exploration of data to discover patterns or validate hypotheses. Although Hadoop can process large volumes of data quickly, it has limitations and the focus to date has been on batch analytics. Although real-time analytics is an emerging area for Hadoop, transferring large volumes of data quickly has consistently been a challenge.
How Attunity Can Help
Attunity Replicate for Hadoop automates data transfer into Hadoop, the Data Lake, from any data source and out of Hadoop – including both structured and unstructured data. Attunity has partnered with Hortonworks and Cloudera to deliver high performance solutions that move Big Data in and out of Apache Hadoop. This alliance will enable companies to access Big Data for analytics in both the cloud and enterprise data centers. By combining Hortonworks’ and Cloudera’s Apache Hadoop expertises and Attunity’s data integration technology, enterprises will be able to load massive amounts of structured and unstructured data to Hadoop.