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Big Data's Hidden Jewel

Machine data is one of the fastest growing and complex areas of big data. It’s also one of the most valuable, containing a definitive record of transactions, customer behavior, sensor readings, machine behavior, security threats, fraudulent activity and more. Splunk® software can help you unlock the hidden value of all your machine-generated data.

Our big data solutions include:

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Why Splunk for Big Data?

Splunk software can collect and index any machine data in real time. Now you can search, explore, navigate, analyze and visualize all your data from one place.

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Easy to Deploy and Use

Connect to your data with just a few clicks and easily create powerful dashboards.
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Real-Time Alerts

Monitor your data to spot trends and identify specific patterns of activity or behavior.
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Massively Scalable

Easily scale from a single server to multiple datacenters.
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Robust Security

Secure data handling, role-based access controls, auditability and data integrity.

Platform for Big Data Analytics

Splunk® Enterprise provides a unified way to organize and extract real-time insights from massive amounts of machine data from virtually any source. This includes data from websites, business applications, social media platforms, app servers, hypervisors, sensors, traditional databases and open-source data stores.

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Deploying Hadoop?

Traditional business intelligence, data warehouse or IT analytics solutions are simply not engineered for this class of high-volume, dynamic and unstructured data. Splunk Analytics for Hadoop is an integrated analytics add-on that enables anyone in your organization to interactively explore, analyze and visualize raw, unstructured big data.

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Big Data Apps

Splunk Analytics for Hadoop

Seamlessly search and analyze Hadoop-based data within Splunk Enterprise.

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ODBC Driver

Provides connectivity between Splunk Enterprise and third-party analytics tools, such as Microsoft Excel or Tableau Desktop.

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Splunk DB Connect

Delivers reliable, scalable, real-time integration between Splunk Enterprise and traditional relational databases.

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