Big Data can provide remarkable benefits for business intelligence and real-time analytics – but only when enterprises have the right Big Data solution in place.

Managing Big Data is hard. Data volumes can quickly grow at exponential rates. Integrating disparate data sources is incredibly complicated and generating insight from thousands of real-time data streams is a huge challenge.

A powerful Big Data solution can help by enabling enterprises to ingest Big Data at scale, to manage Big Data usage and performance, and to minimize the cost of Big Data initiatives.

For hundreds of companies worldwide, Qlik (Attunity) simplifies Big Data management with innovative Big Data solutions

Qlik (Attunity): a Big Data solution for ingesting and managing data

Qlik (Attunity) provides a software solution for universal data replication and data ingestion, and a Big Data solution that can simplify ingestion and streaming across a wide range of heterogeneous databases, data warehouses and Big Data platforms. Qlik (Attunity) provides automated and real-time data integration both on premises and in the cloud. With Qlik (Attunity), enterprises get a Big Data solution for accelerating data delivery, enhancing agile analytics and reducing the cost and effort of cloud database replication.

Qlik (Attunity) solution provides a simple graphical interface that automates data replication and moves data at high speed from source to target. Streamlined and agentless configuration enables administrators to easily set up, control and monitor bulk loads with real-time updates, without requiring manual coding. Centralized control provides global visibility into replication and cloud database backup across distributed, hybrid environments.

A Big Data solution to accelerate ingestion, enhance performance and reduce costs.

With Qlik (Attunity), enterprises can augment their Big Data solution to:

• Accelerate data ingestion at scale into Hadoop Data Lakes, with support for many types of sources, including all RDBMS, data warehouses and mainframe systems.
• Support database streaming (DB streaming) ingest with Apache Kafka, to enable real-time analytics with live data from many sources at scale.
• Integrate mainframe data into big data analytics platforms such as data warehouses and Hadoop, offloading queries from the mainframe and enabling analytics on Big Data stores.