Big Data Automation with Automic

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Organizations are being disrupted by an era 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

Automic Data Automation simplifies and accelerates the integration of Big Data projects through the use of powerful automation. The Automic platform integrates across enterprise applications, databases and platforms, automating the flow of Big Data—from source to staging to reporting. With the unified web interface 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.

Automic Data 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. Infrastructure and operations staff can then automate Hadoop tasks without the additional stress of learning to use a multitude of new tools.

Benefits

  • Eliminates complexity and opens up Big Data to end users, platform engineers and data scientists
  • Reduces technology management costs
  • Provides Development, Operations and Data Scientists with tools tailored to their roles
  • Empowers end-users to manage their own workloads
  • Manages the entire data pipeline, enhancing visibility and securing access
  • Ensures data is being collected, processed and analyzed​ in a timely manner

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