Your data, smarter (15)

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Apache Hop: Visually Design Your Data Pipelines

Apache Hop is an innovative metadata-driven that uses metadata objects to describe how you want to process your data. Apache Hop architecture takes care of the heavy lifting. Based on visual development, Apache Hop allows you to visually design your workflows and pipelines. Let’s say scripting and code are an option, not a necessity.

You can design runtime configurations, a new metadata type, to design pipelines once, and run them in any environment, on any engine you choose. Apache Hop places the ETL processes in a centrally managed platform, which also manages the quality and persistence of data, resulting in higher availability, and reliable information.

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Neo4j: Graphs are everywhere!

When analyzing your data, there often is more value in finding out how your data is related than in the individual data points themselves.  There are numerous use cases where graphs can provide new insights: fraud detection, social network analysis, pathfinding, and many more.

With Neo4j's Cypher query language and the powerful algorithms that can be applied to your graphs, you'll be ready to look at your data in entirely new ways. The combination of Neo4j and Kettle/PDI/Hop makes loading data to and extracting data from your graphs a breeze.  Know.bi is ready to help in modeling, loading, and querying your data into Neo4j graphs.  

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Vertica: lightning fast analytics

When data volumes and the analytics that need to be performed on that data grow, so does the time that is spent loading and querying or analyzing that data. 
Vertica, as a distributed database, stores data on a cluster of machines, has seamless integration with external data (e.g. Hadoop or your data lake) . On top of that, machine learning algorithms can be applied directly on the database. All of this is done through familiar SQL syntax to avoid steep learning curves. 
Vertica is strategically used by the biggest and most data intensive companies on the planet, but can easily add value for smaller organizations as well. 
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