Simplify and accelerate the integration of big data.
Free TrialOrganizations are being disrupted by the advent of big data. Here is a unique opportunity to harness big data and make faster, more informed decisions, recognize new revenue streams and deliver highly personalized customer experiences at massive scale. This could be a game changer for your organization.
You need to efficiently capture and store the big data as it emerges in any volume, velocity or variety. You have to distribute it to hundreds of downstream applications—sometimes in real-time. You need to be certain the data flows are continuous and scalable, from the source to the analytics. And you need the skills and resources to design and operate the big data flows.
Removing Big Data Complexity With Automation
CA Automic Workload Automation simplifies and accelerates the integration of big data projects. It integrates across enterprise applications, databases and platforms, automating the flow of big data—from source to staging to reporting. You can visually design your processes without coding, easily monitor the execution of the workflows and scale your operations to thousands of data flows. Moreover, every operation is audited, monitored and tracked to ensure compliance with corporate rules.
CA Automic Workload Automation provides a self-service approach using an object-oriented framework combined with out-of-the-box actions and templates. Data engineers and non-technical users like data scientists can quickly build complex Hadoop workflows, reducing development effort and increasing business agility.
Visual designer tailored to support the different types of database jobs without coding
Explorer view of the Hadoop file system that simplifies building Hadoop jobs
Connections to various Hadoop environments configured by users in connection profiles
Self-Service portal to enable non-technical users to submit workflows that process data or execute reports
Integrated file transfer ensures timely, accurate and secure raw data transfer
Comprehensive auditing of all automated processing and user activity
Eliminate complexity and open up big data to end users, platform engineers and data scientists.
Reduce technology management costs by eliminating the need for extensive scripting.
Enable greater agility in the acquisition, processing and distribution of information.