For organizations and individuals needing application productivity gains, cost-effective scalability and simplified data management, SANZ has become the trusted storage advisor to assist in solving storage related business problems. SANZ sets the standards in storage management effectiveness and simplicity.
SANZ solutions allow some of the most successful organizations in the world to gain competitive advantage, improve profitability, reduce complexity, and increase efficiencies to lower the Total Cost of managing information assets.
EarthWhere
Smarter about Geospatial Storage
SANZ saw a need for a fully integrated data management and distribution solution in the geospatial community, and developed EarthWhere™ - the first spatial data provisioning system that stores, manages, processes and delivers customized spatial imagery.
With EarthWhere™, you get real-time access to all of your data in the format, projection and datum required by your application. So your people work more efficiently, make better decisions, and answer their questions on time.
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Consolidate your spatial archives with EarthWhere`s Smart Storage Management
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and optimize your storage costs while maintaining capacity, reliability and performance
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Deliver on-demand custom spatial imagery to users in minutes directly to their desktop
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Enhance your desktop GIS applications — ESRI, Intergraph, MapInfo, and ERDAS — with real-time access to project-specific data
The Challenge
There are two main problems that limit the effectiveness of spatial imagery: Complex and expensive data management and storage, and an expanding user base with unique data requirements that leads to a growing combination of custom datasets.
Complex and expensive data management and storage
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Spatial imagery is stored in large files. The cost of traditional storage infrastructure often prohibits the consolidation of these assets.
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Images are stored as datasets with associated geometry files and metadata in tiles dictated by file structure limitations; users often need multiple tiles and all of the associated data to use in their applications
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Distribution using traditional file copies and FTP is inefficient in resources and network bandwidth
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Duplicate copies of the data are used throughout the enterprise, which leads to data currency issues — the end users may not have the most recent data stored on their workstation.
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Data can be stored in various locations on various types of media; access becomes limited when the data are difficult and time consuming to retrieve.
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Lack of a central catalog leaves expensive data assets underutilized.
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Creating and managing the associated metadata is a separate, resource intensive operation with a wide variety of requirements.
An expanding user base with unique data requirements leads to a growing combination of custom datasets
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As the breadth of applications grows, users will find new and unique ways to use existing datasets to answer their questions.
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Users need special tools and special skills to generate the data specific to their requirements from the various source data currently available; the native files are seldom used as initially acquired.
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There are complex, time consuming repetitive image processing tasks that occur each time a user utilizes imagery.
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Most organizations try to ``normalize`` data in generic formats that can serve the majority of user requirements. This normalization tends to lessen the effectiveness of the data for unique projects and leads to considerable and often unnecessary processing time.
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Users often need multiple files from multiple sources to answer their questions.
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Users require information that is limited to their specific AOI (Area of Interest; a polygon which defines a project area) and often must manage more data than they require.
For most users, developing accurate datasets specific to their mission or project requirements is a complex and time consuming process that often takes days or weeks.
