The closer Apache Hadoop comes to being a real time platform for your enterprise data, the more business critical the data integration layer becomes.To enable the real time platform, it requires both minimal impact on production with CDC (change data capture) and real time data via Kafka and HDF™.Watch this webinar to hear real life use cases and learn how leading global financial, insurance and retail organisations are combining Attunity and Hortonworks solutions to meet enterprise big data challenges.
Data lakes based on Hadoop technologies have proved themselves valuable in mission-critical use cases such as data warehousing, advanced analytics, multichannel marketing, complete customer views, digital supply chains, and the modernization of data management.Most Hadoop users are committed to the data lake method of managing data, but they are limited by Hadoop shortcomings in key areas such as cluster maintenance, administration cost, resource management, metadata management, and support for SQL and other relational technologies. Many view cloud-based solutions as the optimal replacement for their data lake, but they are not ready to make such a significant change. The truth is: they don't have to, as the two technologies can coexist.
Business Intelligence and associated tools are becoming widely used for gathering, providing access to, and analyzing data to enable the enterprise to make sound business decisions.With so much jargon and so many technologies involved, this one hour presentation provides a much-needed step-by-step explanation of what's involved and how to use this powerful technology to improve your business. Business Intelligence encompasses a broad collection of tools and concepts designed to help business owners, managers, and technical staff direct the effort effectively.
Rapid data growth from a wide range of new data sources is significantly outpacing organizations’ abilities to manage data with existing systems. Organizations now look to capture all data, keep it longer, and prepare to use the data in new ways as business conditions evolve. As a result, legacy data architectures and IT budgets are straining under the pressure. Community-driven open source technologies with Apache Hadoop at its center offers a viable approach to making data architectures capable of realizing new and improved business outcomes while driving significant cost out of the IT budget.