Recognizing the critical role of data-driven business intelligence in today's competitive marketplace, many enterprises are building or planning to build a Hadoop data warehouse. A Hadoop data warehouse – sometimes called a Hadoop data lake – differs from traditional enterprise data warehousing by supporting analysis of larger and more diverse volumes of data, at lower cost. Hadoop software runs on clusters of commodity servers and utilizes massively parallel processing to uncover hidden trends, patterns, correlations, and anomalies in vast quantities of structured and unstructured data. While the potential business intelligence benefits are enormous, there are also challenges in building and operating a Hadoop data warehouse including the challenges of loading large volumes of heterogeneous data into Hadoop and maintaining visibility into what data is there and how it is being used.
Data-driven businesses in a wide range of industries are finding that Qlik (Attunity) data integration technologies are the most reliable and cost-effective way to solve the challenges and unlock the value of big data and Hadoop. For example, Qlik Replicate (formerly Attunity Replicate) is a proven solution for efficiently loading data into a Hadoop data warehouse.
There are many reasons driving Qlik Replicate (formerly Attunity Replicate) popularity as a Hadoop data ingestion tool, but the main attractions are:
Once data is ingested, the challenge for Hadoop data warehouse operators is to maintain a clear view into the warehouse and the workloads that it supports. With Qlik Visibility (formerly Attunity Visibility), a powerful data usage monitoring and analytics solution, you can: