The DHS Data Inventory Program is working to create a single data inventory of all data within DHS, including the DHS Components, the DHS Functional Data Domains, and DHS HQ. rnrnThe Data Inventory Program is designed to exceed DHS obligations under the Foundations for Evidence-Based Policymaking Act (the Evidence Act), the OPEN Government Data Act, the DHS Data Framework Act of 2018, and DHS Delegation Number 04004 rev 00 of May 18, 2021 from Secretary Mayorkas to the Chief Data Officer. The goal is to create a data inventory that will be useful for all of DHS to help answer questions about DHS data in a timely manner and help DHS leadership plan new activities.

The data inventory lists data that is created, collected and managed by the Government of Ontario, including the title, description and frequency of update for each dataset. It also shows whether a dataset is open, will become open, is under review, or is restricted from being open due to reasons outlined by the Open Data Directive. This inventory does not include dataset files or personal information. Datasets listed in the inventory are also available to view on Ontario's data catalogue. We will update this dataset regularly as data continues to be added to the inventory. Provincial agency data inventories are also available.

By using this dataset you acknowledge the following:Kansas Open Records Act StatementThe Kansas Open Records Act provides in K.S.A. 45-230 that "no person shall knowingly sell, give or receive, for the purpose of selling or offering for sale, any property or service to persons listed therein, any list of names and addresses contained in, or derived from public records..." Violation of this law may subject the violator to a civil penalty of $500.00 for each violation. Violators will be reported for prosecution.By accessing this site, the user makes the following certification pursuant to K.S.A. 45-220(c)(2): "The requester does not intend to, and will not: (A) Use any list of names or addresses contained in or derived from the records or information for the purpose of selling or offering for sale any property or service to any person listed or to any person who resides at any address listed; or (B) sell, give or otherwise make available to any person any list of names or addresses contained in or derived from the records or information for the purpose of allowing that person to sell or offer for sale any property or service to any person listed or to any person who resides at any address listed."

This dataset is a view of the State of Oregon Agency Data Inventory, showing only the inventory items from the Oregon Water Resources Department (OWRD). The OWRD data inventory is updated as needed and is submitted to the state EIS department to be updated in the main State of Oregon Agency Data Inventory.

The State of Oregon Agency Data Inventory is an enterprise level inventory that provides a listing of all state agency data inventories, as required in HB 3361(2017), and codified in ORS276A.350-374. This statute requires that state agencies must “create and maintain an inventory of agency information resources,” and include an indication as to whether or not the information or dataset is considered “publishable.” They must then contribute this information to an enterprise level data inventory, maintained by the Chief Data Officer, for display on a centralized open data portal.
For questions about any dataset listed in this inventory, contact the agency directly. For additional information about this inventory or Oregon’s Open Standard, visit Oregon’s Open Data Program. https://data.oregon.gov/stories/s/Oregon-s-Open-Data-Standard/xr2x-d2d7/

The dataset is about a retail sales dataset containing information about store sales for various products over time.

The specific variables include: Store: Unique identifier for the store location Date: Calendar date of the sales data Product: Name of the product being sold Weekly Sales: Total number of units sold for the product in a week Inventory Level: Number of units of the product currently in stock at the store Temperature: Average temperature for the week at the store location Past Promotion of Product (in lac): Total value (in lakhs) of any past promotions for the product during the week (1 lac = 100,000) Demand Forecast: Predicted number of units to be sold for the product in the next week (provided for baseline model comparison)

This dataset can be used for various analytical purposes related to retail sales and inventory management, including:

Demand forecasting: By analyzing historical sales data, temperature, past promotions, and other relevant factors, you can build models to predict future demand for products. This information can be used to optimize inventory levels and prevent stock outs or overstocking. Promotion analysis: You can compare sales data during promotional periods with non-promotional periods to assess the effectiveness of different promotions and identify products that respond well to promotions. Product analysis: By analyzing sales data across different stores and time periods, you can identify which products are most popular and in which locations. This information can be used to inform product placement, marketing strategies, and assortment planning. Store performance analysis: You can compare sales performance across different stores to identify top-performing stores and understand factors contributing to their success. This information can be used to identify areas for improvement in underperforming stores.

By utilizing this dataset for these analytical purposes, retail organizations can gain valuable insights into their sales patterns, customer behavior, and inventory management practices. This information can be used to make data-driven decisions that improve sales performance, profitability, and customer satisfaction.

Graph and download economic data for Total Business Inventories (BUSINV) from Jan 1992 to Apr 2025 about inventories, headline figure, business, and USA.

Graph and download economic data for Retailers Inventories (RETAILIMSA) from Jan 1992 to Apr 2025 about inventories, retail, and USA.

The DHS Data Inventory is a list of datasets used in and by the department. The dataset details include a verbose set of metadata identifying the source, quality, governance, publication, size and characteristics of the data, with pointers to the data access URL(s) and access rights for use within the department. The Data Inventory was created in response to legislative requirements of the Evidence Act (and Open Government Data Act). Metadata about datasets that are marked as 'public' are sent to Data.gov on a weekly basis.

The purpose of the SNF Study was to develop the techniques to make the link from biophysical measurements made on the ground to aircraft radiometric measurements and then to scale up to satellite observations. Therefore, satellite image data were acquired for the Superior National Forest study site. These data were selected from all the scenes available from Landsat 1 through 5 and SPOT platforms. Image data substantially contaminated by cloud cover or of poor radiometric quality was not acquired. Of the Landsat scenes, only one Thematic Mapper (TM) scene was acquired, the remainder were Multispectral Scanner (MSS) images. Some of the acquired image data had cloud cover in portions of the scene or other problems with the data. These problems and other comments about the images are summarized in the data set. This data set contains a listing of the scenes that passed inspection and were acquired and archived by Goddard Space Flight Center. Though these image data are no longer available from either the Goddard Space Flight Center or the ORNL DAAC, this data set has been included in the Superior National Forest data collection in order to document which satellite images were used during the project.

Grocery Inventory and Sales Dataset

Dataset Overview:

This dataset provides detailed information on various grocery items, including product details, supplier information, stock levels, reorder data, pricing, and sales performance. The data covers 990 products across various categories such as Grains & Pulses, Beverages, Fruits & Vegetables, and more. The dataset is useful for inventory management, sales analysis, and supply chain optimization.

Columns:

• Product_ID: Unique identifier for each product.
• Product_Name: Name of the product.
• Category: The product category (e.g., Grains & Pulses, Beverages, Fruits & Vegetables).
• Supplier_ID: Unique identifier for the product supplier.
• Supplier_Name: Name of the supplier.
• Stock_Quantity: The current stock level of the product in the warehouse.
• Reorder_Level: The stock level at which new stock should be ordered.
• Reorder_Quantity: The quantity of product to order when the stock reaches the reorder level.
• Unit_Price: Price per unit of the product.
• Date_Received: The date the product was received into the warehouse.
• Last_Order_Date: The last date the product was ordered.
• Expiration_Date: The expiration date of the product, if applicable.
• Warehouse_Location: The warehouse address where the product is stored.
• Sales_Volume: The total number of units sold.
• Inventory_Turnover_Rate: The rate at which the product sells and is replenished.
• Status: Current status of the product (e.g., Active, Discontinued, Backordered).

Dataset Usage:

• Inventory Management: Analyze stock levels and reorder strategies to optimize product availability and reduce stockouts or overstock.
• Sales Performance: Track sales volume and inventory turnover rate to understand product demand and profitability.
• Supplier Analysis: Evaluate suppliers based on product availability, pricing, and delivery frequency.
• Product Lifecycle: Identify discontinued or backordered products and analyze expiration dates for perishable goods.

How to Use:

This dataset can be used for various tasks such as: - Predicting reorder quantities using machine learning. - Analyzing inventory turnover to optimize stock levels. - Conducting sales trend analysis to identify popular or slow-moving items. - Improving supply chain efficiency by analyzing supplier performance.

Notes:

• This dataset is fictional and used for educational or demonstration purposes only.
• The expiration dates and last order dates should be considered for time-sensitive or perishable items.
• Some products have been marked as discontinued or backordered, indicating their current status in the inventory system.

License:

This dataset is released under the Creative Commons Attribution 4.0 International License. You are free to share, adapt, and use the data, provided proper attribution is given.

Wholesale Inventories in the United States decreased 0.30 percent in May of 2025 over the previous month. This dataset provides - United States Wholesale Inventories - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Catalog of high value data inventories produced by Connecticut executive branch agencies, pursuant to Connecticut General Statutes Section 4-67p.

Executive branch agencies update their high value data inventories annually in December. This dataset was last collected in December of 2023.

High value data is defined as any data that the department head determines (A) is critical to the operation of an executive branch agency; (B) can increase executive branch agency accountability and responsiveness; (C) can improve public knowledge of the executive branch agency and its operations; (D) can further the core mission of the executive branch agency; (E) can create economic opportunity; (F) is frequently requested by the public; (G) responds to a need and demand as identified by the agency through public consultation; or (H) is used to satisfy any legislative or other reporting requirements.

This is a list of the items shared through the open data portal and their view counts. This is not a full list of the City's open data. Only the items shared through this portal.Updated weekly.

The stocks of goods held by firms in the United States increased by 160.50 USD Billion in the first quarter of 2025. This dataset provides - United States Changes in Inventories - actual values, historical data, forecast, chart, statistics, economic calendar and news.

An inventory of datasets and other data assets that are published by the City of Seattle on data.seattle.gov

United States Inventories to Sales Ratio data was reported at 1.300 Unit in Sep 2018. This records an increase from the previous number of 1.190 Unit for Aug 2018. United States Inventories to Sales Ratio data is updated monthly, averaging 1.240 Unit from Jan 1992 (Median) to Sep 2018, with 321 observations. The data reached an all-time high of 1.540 Unit in Jan 2016 and a record low of 1.060 Unit in Mar 2011. United States Inventories to Sales Ratio data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s United States – Table US.C019: Wholesalers Inventories to Sales Ratio: By NAIC System.

As a mandate of the New Orleans City Data Policy - Executive Order 16-01 & Policy Memorandum 135, we are taking an inventory of all City datasets. This on-going inventory process will help us to categorize and identify data that could be made publicly available. This process also assists our ability to work cross-departmentally and increases our resilience.

Why is the data inventory important? • Stimulate new ideas and services. By publishing a data inventory, city departments may help to stimulate new and innovative ideas from the community. • Increase internal sharing and resilience. A data inventory can also help us access information from other departments that we need to improve service delivery and resilience planning. • Enabling better and more up-to-date processes. The process of publishing a data inventory will help us to realize the constraints of current City technology and processes, and then plan for future improvements. • Changing how we use data. A data inventory can help empower us to change how we use, share and consume our data externally and internally, ultimately transforming data into better services for citizens and fostering continuous improvement.