TerramEarth manufactures heavy equipment for the mining and agricultural industries.
About 80% of their business is from mining and 20% from agriculture.
They currently have over 500 dealers and service centers in 100 countries.
Their mission is to build products that make their customers more productive.
Solution Concept - There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port.
This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly.
At a rate of 120 fields of data per second, with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment - TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single U.S, west coast based data center.
These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse.
Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%
However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements -Decrease unplanned vehicle downtime to less than 1 weekSupport the dealer network with more data on how their customers use their equipment to better position new products and servicesHave the ability to partner with different companies " especially with seed and fertilizer suppliers in the fast-growing agricultural business " to create compelling joint offerings for their customers Technical Requirements -Expand beyond a single datacenter to decrease latency to the American midwest and east coastCreate a backup strategyIncrease security of data transfer from equipment to the datacenterImprove data in the data warehouseUse customer and equipment data to anticipate customer needs Application 1: Data ingest - A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:Windows Server 2008 R2 - 16 CPUs - 128 GB of RAM - 10 TB local HDD storage Application 2: Reporting - An off the shelf application that business analysts use to run a daily report to see what equipment needs repair.
Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:Off the shelf application.
License tied to number of physical CPUs - Windows Server 2008 R2 - 16 CPUs - 32 GB of RAM - 500 GB HDD Data warehouse:A single PostgreSQL server - RedHat Linux - 64 CPUs - 128 GB of RAM - 4x 6TB HDD in RAID 0 Executive Statement - TerramEarth.
Considering the TerramEarth business and technical requirements, what should you do?
Click on the arrows to vote for the correct answer
A. B. C. D.A.
Based on the given scenario, TerramEarth is facing several business and technical challenges that require improvements to their existing architecture. TerramEarth is currently collecting a massive amount of data from their vehicles, but their existing system takes too long to process the data, resulting in delayed reports that are up to three weeks old. This stale data causes TerramEarth customers to experience unplanned downtime that can last up to four weeks. To address these challenges, TerramEarth needs to implement a more robust and scalable data architecture that can process and analyze data in real-time to help minimize downtime, support their dealer network with better data, and improve customer experience.
Solution Concept: TerramEarth has 20 million vehicles that collect 120 fields of data per second, resulting in approximately 9 TB of data per day. Approximately 200,000 of these vehicles are connected to a cellular network, which allows TerramEarth to collect data directly. The rest of the vehicles collect data locally, and the data is downloaded via a maintenance port when the vehicle is serviced. The same maintenance port can be used to upgrade the vehicle's computing modules.
Existing Technical Environment: TerramEarth's current architecture is composed of Linux and Windows-based systems that reside in a single data center on the U.S. West Coast. These systems gzip CSV files from the field and upload them via FTP, and the data is stored in their data warehouse. However, the process takes too long, and the aggregated reports are based on data that is three weeks old. To improve their data processing and reporting, TerramEarth needs to expand beyond a single data center to decrease latency to the American Midwest and East Coast, create a backup strategy, increase the security of data transfer, and improve data in the data warehouse.
Business Requirements: To address TerramEarth's business challenges, the following requirements need to be met:
Technical Requirements: To address TerramEarth's technical challenges, the following requirements need to be met:
Application 1: Data Ingest: A custom Python application reads uploaded datafiles from a single server and writes them to the data warehouse.
Compute: Windows Server 2008 R2 - 16 CPUs - 128 GB of RAM - 10 TB local HDD storage
Application 2: Reporting: An off-the-shelf application that business analysts use to run a daily report to see what equipment needs repair. Only two analysts out of a team of 10 (5 West Coast, 5 East Coast) can connect to the reporting application at a time.
Compute: Off-the-shelf application. License tied to the number of physical CPUs - Windows Server 2008 R2 - 16 CPUs - 32 GB of RAM - 500 GB HDD
Data Warehouse: A single PostgreSQL server - RedHat Linux - 64 CPUs - 128 GB of RAM - 4x 6TB HDD in RAID 0
Executive Statement: TerramEarth needs to replace its existing architecture with a more robust and scalable solution that can process and analyze data in real-time to minimize downtime and improve customer experience. To meet these requirements, TerramEarth should consider the following options:
A.