Pentaho Instaview – Instant and Interactive Big Data Analytics
From Data to Visualization in Minutes
Instaview, Pentaho’s big data analytics application, dramatically reduces the time required for data analysts and scientists to discover, visualize and explore large volumes of diverse data. Instaview provides self-service analytics for the leading big data stores including Hadoop, Cassandra, HBase, MongoDB and more. With Instaview the big data analytics cycle is accelerated from days and weeks to hours and minutes.
Instant big data analytics for data analysts
Instaview broadens data access to data analysts and removes the need for separate big data visualization tools. Data delivery is simplified to only a few simple steps.
Choose a data source
Choosing from a palette of big data—and other data sources, Instaview will connect and provide a complete view of customers, business operations and performance. Users are not limited to a single data source but can access:
- Hadoop Data: HDFS, Hive
- NoSQL Data: HBase, Cassandra, MongoDB
- Web Data: Twitter, Facebook, Log Files, Web Logs
Automatically prepare data for analysis
Without IT intervention or complicated data preparation, Instaview:
- Automatically turns raw and unstructured data into self-service, analytic-ready data sets
- Dramatically simplifies, groups, sorts and aggregates large volumes of unruly data
Instantly visualize and explore
With an interactive user interface, big data is ready to explore with the power of Penthaho’s interactive visualizations including:
- Geo-mapping
- Heat grids
- Scatter/bubble charts
- Bar/line graphs
Instaview behind the scenes - technical benefits for IT and developers
Instaview allows IT to streamline and manage end user access to big data stores and deploy big data analytics faster. With easy visual steps and no coding required, Instaview provides IT with:
- Fast deployment of big data analytics templates for data analysts
- Managed data access controls
- Easy visual editing steps to create/refine big data analytics templates
- Big data enrichment with reference data from other sources