Xcc Service Data

[Awilda]

Vehicleservice is a gold mine that every dealership should be capitalizing on. Our vehicle service data, including OEM service schedules, NHTSA Recall and service bulletins, provide a means for reengaging with existing customers and improving retention rates.

Business and profit generating opportunities have only just begun when a new owner drives their vehicle off the lot. Tap into the huge opportunity vehicle service and maintenance activities present by building your solutions on a solid data foundation.

OEM, dealer, independent garages and aftermarket solutions are easily supported by our flexible and OEM compliant recommended service schedules data. Our Auto Care Association ACES mapping ties the ACES standard to both DataOne VehicleID and VIN. NHTSA Recall and Service Bulletin data round out our service offering.

Providing valueable, vehicle specific offers and reminders becomes a regular touch point with your customer(s) and building brand and business loyalty. In fact, most dealerships find providing regular service to a customer is one of the most significant contributors to customer loyalty for their next vehicle purchase. It also is the greatest indicator of where a person will choose to have more costly repairs done.

Our OEM Service Schedule product was developed to support the full spectrum of service related activities. This includes everything from powering service scheduling and shop logistics, to supporting detailed and vehicle specific service marketing efforts.

When employed, these optional schedules can increase maintenance related visits and revenue significantly. Our OEM Service Schedules data offering is optimized to support both the operations and scheduling side of service, as well as targeted/re-marketing activities.

Our Auto Care ACES Mapping ties our VIN referenced automotive data to the Auto Care Association's* Aftermarket Catalog Exchange Standard (ACES). It allows users to easily decode a vehicle's VIN and be returned the appropriate ACES IDs.

The ACES ID can be used for easy and convenient identification of appropriate parts, accessories, tires or fluids. ACES Mapping is a great fit for parts and service providers and the vehicle salvage industry.

All Recalls, whether voluntary or ordered by the NHTSA, require a public report to be filed with the NHTSA that records the Years, Makes, Models and equipment involved, a description of the issue, a recall schedule and the corrective action for the recall.

The National Highway Traffic Safety Administration (NHTSA) is the organization that automobile manufacturers are required to report to when there are significant issues with the vehicles they produce.

These reported issues can result in a Recall if the NHTSA determines that a threat to driver safety is involved or if the manufacturer deems the quality issue is significant enough to warrant a recall.

The Library Services Team annually collects statistics from Wisconsin public libraries. Excel files of more than 115 data elements grouped by general categories are available below. Send any questions or report problems to librar...@dpi.wi.gov.

All data has been reviewed by the Division for Libraries and Technology for accuracy and submitted to the Institute for Museum and Library Services (IMLS) as part of the Public Libraries Survey (PLS). Formatting and calculation issues may persist in these files due to the complexity of the published files.

M365 is showing the new server and sync results are all good. Dashboard shows healthy. Then i get an email alert saying the "Health service data is not up to date. " and references the old server. M365 still says all is good, but AAD has their own sync area apparently, and the new server is not there, just the old with the error.

Section 207(f)(2) of the E-Government Act of 2002 requires federal agencies to develop an inventory of information to be published on their Web sites, establish a schedule for publishing information, make those schedules available for public comment, and post the schedules and priorities on the Web site.

CroplandCROS hosts the Cropland Data Layer (CDL). The app allows users to geolocate farms and map areas of interest. To aid users, the app features a user guide and instructional videos. CroplandCROS was developed in cooperation with the Agricultural Research Service.

VegScape is a geospatial data service, which offers automated updates of the vegetative condition at daily, weekly, and biweekly intervals. It delivers interactive vegetation indices that enable quantification of U.S. crop conditions for exploring, visualizing, querying, and disseminating via interactive maps. VegScape was developed in cooperation with the Center for Spatial Information Science and Systems at George Mason University.

Crop Condition and Soil Moisture Analytics (Crop-CASMA) is a web-based geospatial application. It is designed to remotely sense geospatial soil moisture and vegetation index data derived from NASA Soil Moisture Active Passive (SMAP) and Moderate Resolution Imaging Spectroradiometer (MODIS) missions to assess U.S. soil moisture condition and crop vegetation conditions. It is designed and developed by USDA-NASS and the Center for Spatial Information Science and Systems at George Mason University.

Crop Progress and Condition Gridded Layers are gridded geospatial datasets which are fully synthetic representations of confidential, county level data. These new data are available for U.S. corn and soybeans, and eventually cotton and wheat.

Crop Sequence Boundaries are field polygons, geospatial datasets that produces estimates of field boundaries, crop acreage, and crop rotations across the U.S. It uses satellite imagery with other public data over a set time frame. It was developed in cooperation with the Economic Research Service.

Disaster Analysis - USDA-NASS can now monitor agricultural disasters in near real-time and provide quantitative assessments using remotely sensed data and geospatial techniques. View disaster assessments in geospatial data format, reports, and metadata as available.

Land Use Strata for Selected States - The USDA-NASS area sampling frame delineates all parcels of land for the purpose of sampling. The area frame is constructed by visually interpreting satellite imagery to divide a state into stratification classes (strata) based on percent of land used in cultivation. View the most recent land use strata map for each state.

Hi, Looking to filter the MongoDB input tool for the collection AS_Results. Have 20 GB of data and it takes forever without filtering. Looking to filter the __ServiceData blob prior to inputting; specifically ExecutionStartTime:

In my Mongo, the AS_Results collection contains 831K records, which takes 15 mins to query. Given the volume of workflows run on our servers, this collection will continue to grow at a rapid pace going forward. Needless to say, as the volume continues to increase, so will the retrieval time.

I've needed a solution like this for a while now. Looked into it today. What I needed was to be able to filter the MongoDB results for the day prior to read the logs of scheduled workflows. The steps I took:

Although a very large AS_Results collection might take a while to query, the primary bottleneck is the time it takes to parse the service data from the AS_Results collection. So the solution is to filter the data BEFORE we parse the service data.

Instead of using the filter tool after querying the collection, we could use the criteria field in the MongoDB Input tool. But since the AS_Results collection has no datetime field available prior to parsing the service data, we have no choice but to pull the entire collection. However ...

While there is no datetime field with which we could filter the AS_Results collection from the MongoDB Input tool, there are datetime fields on the AS_Queue collection. Adding the criteria in the MongoDB Input tool for the CreationDateTime field allows us to filter the AS_Queue collection. The _id field, once parsed (renamed JobId by the Alteryx Server Usage Report macro), can then be joined to the AS_Queue__ID field from the AS_Results collection to limit the volume of AS_Results service data that must be parsed.

JSON criteria for a datetime field depends on (1) whether the MongoDB Input tool's mode is Manual (criteria is specified by element) or Automatic (criteria is specified for the collection), and (2) whether the field is stored as a string or as a datetime.

The CreationDate field in the sessions collection [in the AlteryxGallery database] is stored as a datetime. The criteria to filter the sessions collection where the CreationDate field is greater than a specified date would be:

I used the JobId from the AS_Queue collection as Criteria for querying the AS_Result collection. To do so I grouped and concatenated the JobId and used it as a Control Parameter for a Batch macro that contains the connection to the AS_Result collection. In the macro each batch replaces the AS_Queue__ID. So I can query only the service data for the jobs of the defined timeframe. I grouped it for 1000 JobIds to avoid that the Criteria gets too long and that works fine. I changed the Icons of the two macros to the MongoDB Input because it is basically that tool with added parameters.

The Surface Transportation Board requires Class I rail carriers to provide weekly reports containing data on rail service performance. These reports, which also include data pertaining to the Chicago gateway, allow both the agency and the public to have greater real-time visibility into the performance of the Class I industry. The weekly reports filed by the Class I rail carriers can be found below. In addition to the individual carrier reports, the Board has created a spreadsheet of consolidated service performance data for all Class I rail carriers.

As of November 11, 2020, the Chicago Terminal weekly report will no longer include data for terminal forecast indicators cars enroute (through no I/C) and subtotal no I/C field. It was determined that data for cars enroute (through no I/C) cannot be collected at this time. Accordingly, those two fields will no longer be included in the weekly report.

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