100+ datasets found
  1. Grocery Inventory

    • kaggle.com
    Updated Mar 16, 2025
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    willian oliveira (2025). Grocery Inventory [Dataset]. http://doi.org/10.34740/kaggle/dsv/11053760
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 16, 2025
    Dataset provided by
    Kaggle
    Authors
    willian oliveira
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    this graph was created in R and Canva :

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F1a47e2e6e4836b86b065441359d5c9f0%2Fgraph1.gif?generation=1742159161939732&alt=media" alt=""> https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F87de025c5703cb69483764c4fc9c58ab%2Fgraph2.gif?generation=1742159169346925&alt=media" alt=""> https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Fddf5001438c97c8c030333261685849b%2Fgraph3.png?generation=1742159174793142&alt=media" alt="">

    The dataset offers a comprehensive view of grocery inventory, covering 990 products across multiple categories such as Grains & Pulses, Beverages, Fruits & Vegetables, and more. It includes crucial details about each product, such as its unique identifier (Product_ID), name, category, and supplier information, including Supplier_ID and Supplier_Name. This dataset is particularly valuable for businesses aiming to optimize inventory management, sales tracking, and supply chain efficiency.

    Key inventory-related fields include Stock_Quantity, which indicates the current stock level, and Reorder_Level, which determines when a product should be reordered. The Reorder_Quantity specifies how much stock to order when inventory falls below the reorder threshold. Additionally, Unit_Price provides insight into pricing, helping businesses analyze cost trends and profitability.

    To manage product flow, the dataset includes dates such as Date_Received, which tracks when the product was added to the warehouse, and Last_Order_Date, marking the most recent procurement. For perishable goods, the Expiration_Date column is critical, allowing businesses to minimize waste by monitoring shelf life. The Warehouse_Location specifies where each product is stored, facilitating efficient inventory handling.

    Sales and performance metrics are also included. The Sales_Volume column records the total number of units sold, providing insights into consumer demand. Inventory_Turnover_Rate helps businesses assess how quickly a product sells and is replenished, ensuring better stock management. The dataset also tracks the Status of each product, indicating whether it is Active, Discontinued, or Backordered.

    The dataset serves multiple purposes in inventory management, sales performance evaluation, supplier analysis, and product lifecycle tracking. Businesses can leverage this data to refine reorder strategies, ensuring optimal stock levels and avoiding stockouts or excessive inventory. Sales analysis can help identify high-demand products and slow-moving items, enabling better decision-making in pricing and promotions. Evaluating suppliers based on their performance, pricing, and delivery efficiency helps streamline procurement and improve overall supply chain operations.

    Furthermore, the dataset can support predictive analytics by employing machine learning techniques to estimate reorder quantities, forecast demand, and optimize stock replenishment. Inventory turnover insights can aid in maintaining a balanced supply, preventing unnecessary overstocking or shortages. By tracking trends in sales, businesses can refine their marketing and distribution strategies, ensuring sustained profitability.

    This dataset is designed for educational and demonstration purposes, offering fictional data under the Creative Commons Attribution 4.0 International License. Users are free to analyze, modify, and apply the data while providing proper attribution. Additionally, certain products are marked as discontinued or backordered, reflecting real-world inventory dynamics. Businesses dealing with perishable goods should closely monitor expiration and last order dates to avoid losses due to spoilage.

    Overall, this dataset provides a versatile resource for those interested in inventory management, sales analysis, and supply chain optimization. By leveraging the structured data, businesses can make data-driven decisions to enhance operational efficiency and maximize profitability.

  2. Toxics Release Inventory (TRI)

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Oct 12, 2021
    + more versions
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    U.S. EPA Office of Environmental Information (OEI) (2021). Toxics Release Inventory (TRI) [Dataset]. https://catalog.data.gov/dataset/toxics-release-inventory-tri
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    Dataset updated
    Oct 12, 2021
    Dataset provided by
    United States Environmental Protection Agencyhttp://www.epa.gov/
    Description

    The Toxics Release Inventory (TRI) is a dataset compiled by the U.S. Environmental Protection Agency (EPA). It contains information on the release and waste management for over 800 toxic chemicals and toxic chemical categories as reported annually by facilities in certain industries as well as federal facilities. This inventory was established under the Emergency Planning and Community Right-to-Know Act of 1986 (EPCRA) and expanded by the Pollution Prevention Act of 1990. TRI data support informed decision-making by communities, government agencies, industries, and others.

  3. R

    Gadget Inventory Dataset

    • universe.roboflow.com
    zip
    Updated May 3, 2025
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    Personal (2025). Gadget Inventory Dataset [Dataset]. https://universe.roboflow.com/personal-r9dts/gadget-inventory/model/1
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    zipAvailable download formats
    Dataset updated
    May 3, 2025
    Dataset authored and provided by
    Personal
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Objects Bounding Boxes
    Description

    Gadget Inventory

    ## Overview
    
    Gadget Inventory is a dataset for object detection tasks - it contains Objects annotations for 530 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  4. B

    Barcode Inventory Management Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Feb 13, 2025
    + more versions
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    Data Insights Market (2025). Barcode Inventory Management Software Report [Dataset]. https://www.datainsightsmarket.com/reports/barcode-inventory-management-software-524410
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    doc, ppt, pdfAvailable download formats
    Dataset updated
    Feb 13, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Barcode Inventory Management Software Market Overview: The global barcode inventory management software market size was valued at USD 3.1 billion in 2025 and is expected to expand at a compound annual growth rate (CAGR) of 12.5% from 2025 to 2033. The growth of this market is attributed to the increasing adoption of barcode technology in various industries to enhance inventory management efficiency, reduce operational costs, and improve supply chain visibility. Additionally, the rising demand for real-time inventory tracking, automation, and data analytics capabilities is further driving the market growth. The market is segmented into Small and Medium Enterprise (SME) and Large Enterprise based on application, and Cloud-based and Local Deployment based on type. Competitive Landscape: The barcode inventory management software market is highly competitive with numerous players offering a wide range of solutions. Key players include Sortly, Zoho, inFlow Inventory, Label LIVE, seventhings, EZOfficeInventory, NetSuite, Asset Panda, Lightspeed Retail, Fishbowl, Cin7 Omni, Square for Retail, InventoryCloud, ERPAG, Sage, Unleashed, Finale Inventory, GoFrugal, WooPOS, Katana Cloud Inventory, SalesPad, Megaventory, MRPeasy, LABELVIEW, Thrive by Shopventory, and Reftab. These companies are focusing on developing innovative solutions, expanding their geographical presence, and acquiring smaller players to gain market share.

  5. R

    Real-time Inventory Management System Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Jun 4, 2025
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    Data Insights Market (2025). Real-time Inventory Management System Report [Dataset]. https://www.datainsightsmarket.com/reports/real-time-inventory-management-system-1403597
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    pdf, ppt, docAvailable download formats
    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The real-time inventory management system (RTIMS) market is experiencing robust growth, driven by the increasing need for efficient supply chain management and enhanced operational visibility across diverse industries. The market, estimated at $15 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 15% between 2025 and 2033, reaching an estimated $45 billion by 2033. This expansion is fueled by several key factors: the rising adoption of cloud-based solutions offering scalability and accessibility; the growing integration of RTIMS with other enterprise resource planning (ERP) systems; and the increasing demand for real-time data analytics to optimize inventory levels, reduce waste, and improve forecasting accuracy. Furthermore, the e-commerce boom and the resulting need for agile inventory management are significant contributors to market growth. The market is segmented by deployment type (cloud-based, on-premise), industry (retail, manufacturing, healthcare), and company size (small, medium, large). Competition is fierce, with a multitude of vendors offering a range of solutions catering to different needs and budgets. However, the market presents significant opportunities for innovative providers offering advanced features such as AI-powered demand forecasting, blockchain-based inventory tracking, and integrated IoT capabilities. Despite the positive growth trajectory, the RTIMS market faces certain challenges. High implementation costs associated with integrating new systems into existing infrastructures can be a barrier for smaller businesses. Data security and privacy concerns also remain a key consideration, particularly with the increasing reliance on cloud-based solutions. Furthermore, the complexity of integrating RTIMS across diverse and geographically dispersed operations presents ongoing challenges for many companies. The ongoing evolution of technology and the need for continuous system updates further contribute to the complexities within this market. Despite these obstacles, the long-term outlook for the RTIMS market remains exceptionally promising, driven by continuous advancements in technology, the rising demand for enhanced supply chain visibility and efficiency, and the growing need for data-driven decision-making across industries.

  6. I

    Inventory Management Software Market Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Feb 9, 2025
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    Archive Market Research (2025). Inventory Management Software Market Report [Dataset]. https://www.archivemarketresearch.com/reports/inventory-management-software-market-10313
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    pdf, ppt, docAvailable download formats
    Dataset updated
    Feb 9, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    global
    Variables measured
    Market Size
    Description

    The global inventory management software market size was valued at USD 3.58 billion in 2023 and is projected to grow from USD 4.02 billion in 2025 to USD 7.52 billion by 2033, at a CAGR of 6.7% during the forecast period (2023-2033). Rising adoption of IoT and cloud computing, increasing demand for real-time inventory visibility, and growing need for efficient supply chain management are the key factors driving the market growth. The growing adoption of inventory management software is primarily attributed to the increasing need for businesses to maintain accurate and up-to-date inventory records. The software helps businesses in tracking and managing their inventory levels in real-time, reducing the risk of stockouts and improving operational efficiency. Additionally, the adoption of inventory management software is driven by the need for businesses to improve their supply chain visibility, which is essential for optimizing inventory levels and reducing costs. The market is further driven by the growing adoption of e-commerce, which is leading to an increase in the demand for inventory management software that can help businesses manage their online inventory and fulfill customer orders efficiently. Recent developments include: In May 2024, Epicor, announced that it has completed the acquisition of Smart Software, a leading provider of demand planning and inventory optimization applications. This acquisition enhances Epicor’s capabilities in supply chain management, specifically strengthening its ability to offer advanced inventory planning and forecasting tools to its customers. The acquisition underscores Epicor's commitment to providing comprehensive inventory management applications that meet the evolving needs of manufacturing, distribution, retail, and other industry sectors. , In May 2024, Zimbis and DSN Software announced a strategic partnership to integrate their technologies, enhancing inventory management and supply chain applications. The collaboration aims to leverage Zimbis' expertise in cloud-based inventory management with DSN Software's capabilities in digital transformation for supply chain optimization. The integration of Zimbis Smart Inventory Cabinets with DSN's comprehensive practice management software will help dental clinics to streamline operations, minimize waste, and optimize the use of essential supplies. This partnership aims to establish a higher benchmark for efficiency and management within the dental industry, promising improved operational workflows and better resource management. , In May 2023, BoxHero, a global inventory management Application, officially launched its applications in the US and Canadian markets. The software offers comprehensive features for small to medium-sized businesses (SMBs) to manage their inventory effectively. BoxHero's user-friendly interface, barcode scanning capabilities, and real-time tracking functionality cater to the needs of retail, e-commerce, and logistics sectors. The expansion into North America aims to capitalize on the growing demand for streamlined inventory management applications, providing SMBs with tools to optimize operations, reduce costs, and improve overall efficiency in their supply chains. , In December 2023, Syrup Tech announced that it has secured a funding worth USD 17.5 billion in Series A funding to enhance AI-powered inventory forecasting for retailers. The funding will support Syrup Tech's mission to revolutionize inventory management by leveraging advanced AI algorithms, enabling retailers to optimize stock levels, reduce costs, and improve supply chain efficiency. .

  7. Online Inventory Management Software Market Report | Global Forecast From...

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Online Inventory Management Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-online-inventory-management-software-market
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    pptx, pdf, csvAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Online Inventory Management Software Market Outlook




    The global online inventory management software market size was valued at approximately USD 2.3 billion in 2023 and is projected to reach around USD 5.8 billion by 2032, growing at a CAGR of 10.8% during the forecast period. This growth is driven by increasing adoption of digital solutions, burgeoning e-commerce activities, and the need for efficient supply chain management. The demand for real-time tracking and automation in inventory processes is significantly boosting the market.




    One of the primary growth drivers of the online inventory management software market is the rapid digital transformation across different industry verticals. Businesses are increasingly adopting cloud-based solutions to streamline their operations, reduce costs, and enhance productivity. The move towards digitalization is not only confined to large enterprises but is also being embraced by small and medium enterprises (SMEs). This is because cloud-based solutions offer scalability, flexibility, and cost efficiency, which are essential for the growth and sustainability of SMEs.




    Another significant growth factor is the exponential rise of e-commerce and online retailing. The e-commerce sector has seen unprecedented growth in recent years, driven by changing consumer behaviors and the convenience of online shopping. Inventory management software is crucial for e-commerce businesses to manage their stock levels, fulfill orders efficiently, and prevent stockouts or overstock situations. The software provides real-time visibility into inventory, helping businesses make informed decisions and improve customer satisfaction.




    The growing importance of supply chain optimization is also driving the adoption of online inventory management software. Efficient inventory management is critical for maintaining a smooth supply chain, reducing operational costs, and increasing profitability. Businesses are increasingly relying on advanced software solutions to manage their inventory, track shipments, and forecast demand. The integration of technologies like Artificial Intelligence (AI) and Machine Learning (ML) into inventory management software is further enhancing its capabilities, enabling predictive analytics and automated decision-making.



    In the realm of laboratory environments, the need for precise and efficient management of resources is paramount. Lab Inventory Management Software has emerged as an essential tool for laboratories to streamline their operations. This software aids in tracking the usage and availability of laboratory supplies, reagents, and equipment, ensuring that experiments and research activities proceed without interruption. By providing real-time data on inventory levels, it helps in minimizing waste and optimizing procurement processes. Laboratories can also benefit from the software's ability to maintain compliance with regulatory standards by keeping accurate records of inventory usage and storage conditions. As laboratories continue to adopt digital solutions, Lab Inventory Management Software is becoming increasingly vital in enhancing operational efficiency and supporting scientific advancements.




    Regionally, North America holds a significant share of the online inventory management software market, attributed to the high adoption rate of advanced technologies, presence of major market players, and the growing e-commerce sector. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. This growth can be attributed to the rapid industrialization, increasing number of SMEs, and the booming e-commerce industry in countries like China and India. The increasing investments in digital infrastructure and supportive government initiatives are further propelling the market growth in this region.



    Component Analysis




    The component segment of the online inventory management software market is categorized into software and services. Software solutions comprise the core of inventory management systems, offering functionalities such as inventory tracking, order management, and real-time analytics. The software segment is expected to hold a substantial market share due to the increasing demand for automated solutions that enhance inventory accuracy and operational efficiency. The integration of advanced features li

  8. O

    Online Inventory Management Platform Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated May 13, 2025
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    Data Insights Market (2025). Online Inventory Management Platform Report [Dataset]. https://www.datainsightsmarket.com/reports/online-inventory-management-platform-1431142
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The online inventory management platform market is experiencing robust growth, driven by the increasing adoption of cloud-based solutions and the need for real-time visibility across supply chains. The market, estimated at $15 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This growth is fueled by several key factors. Businesses, particularly small and medium-sized enterprises (SMEs), are increasingly adopting these platforms to streamline operations, reduce manual errors, and improve overall efficiency. The integration of advanced analytics capabilities within these platforms enables businesses to make data-driven decisions regarding inventory levels, purchasing, and forecasting, leading to significant cost savings. Furthermore, the rise of e-commerce and omnichannel retailing necessitates sophisticated inventory management solutions capable of handling high transaction volumes and diverse sales channels. The market is segmented by application (real-time inventory management, scanning, reporting and analytics) and type (integrated, non-integrated), with integrated solutions gaining traction due to their seamless workflow integration. Geographic expansion is another significant factor, with North America and Europe currently dominating the market, while Asia Pacific is expected to witness significant growth driven by rapid e-commerce development and increasing digitalization across various industries. Competitive pressures are high, with established players like QuickBooks and Xero competing against specialized inventory management platforms like Fishbowl and Cin7. However, the overall market exhibits strong growth potential due to increasing demand for improved inventory control and supply chain optimization. The competitive landscape is dynamic, with both established enterprise resource planning (ERP) vendors and specialized inventory management software providers vying for market share. The success of individual companies will depend on factors such as the breadth and depth of their feature sets, integration capabilities with existing business systems, ease of use, and the quality of their customer support. The market's growth will be further propelled by advancements in artificial intelligence (AI) and machine learning (ML), enabling predictive analytics and automated inventory optimization. The continued adoption of mobile and cloud technologies will also contribute to enhanced accessibility and scalability, broadening the platform's appeal to businesses of all sizes. However, potential restraints include the initial investment costs associated with implementation and integration, the need for robust IT infrastructure, and concerns surrounding data security and privacy. Nevertheless, the overall outlook for the online inventory management platform market remains highly positive, driven by the increasing demand for streamlined inventory management, improved operational efficiency, and better data-driven decision-making capabilities.

  9. g

    Dataset inventory

    • gimi9.com
    • data.sfgov.org
    • +1more
    Updated Oct 15, 2023
    + more versions
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    (2023). Dataset inventory [Dataset]. https://gimi9.com/dataset/data-gov_dataset-inventory/
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    Dataset updated
    Oct 15, 2023
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    A. SUMMARY The dataset inventory provides a list of data maintained by departments that are candidates for open data publishing or have already been published and is collected in accordance with Chapter 22D of the Administrative Code. The inventory will be used in conjunction with department publishing plans to track progress toward meeting plan goals for each department. B. HOW THE DATASET IS CREATED This dataset is collated through 2 ways: 1. Ongoing updates are made throughout the year to reflect new datasets, this process involves DataSF staff reconciling publishing records after datasets are published 2. Annual bulk updates - departments review their inventories and identify changes and updates and submit those to DataSF for a once a year bulk update - not all departments will have changes or their changes will have been captured over the course of the prior year already as ongoing updates C. UPDATE PROCESS The dataset is synced automatically daily, but the underlying data changes manually throughout the year as needed D. HOW TO USE THIS DATASET Interpreting dates in this dataset This dataset has 2 dates: 1. Date Added - when the dataset was added to the inventory itself 2. First Published - the open data portal automatically captures the date the dataset was first created, this is that system generated date Note that in certain cases we may have published a dataset prior to it being added to the inventory. We do our best to have an accurate accounting of when something was added to this inventory and when it was published. In most cases the inventory addition will happen prior to publishing, but in certain cases it will be published and we will have missed updating the inventory as this is a manual process. First published will give an accounting of when it was actually available on the open data catalog and date added when it was added to this list. E. RELATED DATASETS

  10. d

    Life Cycle inventory database - Dataset - CE data hub

    • datahub.digicirc.eu
    Updated May 10, 2022
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    (2022). Life Cycle inventory database - Dataset - CE data hub [Dataset]. https://datahub.digicirc.eu/dataset/life-cycle-inventory-database
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    Dataset updated
    May 10, 2022
    Description

    (i) The CPM LCA Database is developed within the Swedish Life Cycle Center, and is a result of the continuous work to establish transparent and quality reviewed LCA data. The Swedish Life Cycle Center (founded in 1996 and formerly called CPM) is a center of excellence for the advance of life cycle thinking in industry and other parts of society through research, implementation, communication and exchange of experience on life cycle management. The mission is to improve the environmental performance of products and services, as a natural part of sustainable development. The Center has been instrumental for the development and adoption the life cycle perspective in Swedish companies and has made important contributions to international standardization in the life cycle field. More information about the Center, see www.lifecyclecenter.se. The Swedish Life Cycle Center owns the CPM LCA Database, which is today maintained by Environmental Systems Analysis at the Department of Energy and Environment at Chalmers University of Technology. (ii) All LCI datasets can be viewed in in three formats: the SPINE format, a format compatible with the ISO/TS 14048 LCA data documentation format criteria, and in the ILCD format. Three impact assessment models: EPS, EDIP, and ECO-Indicator, can be viewed in the IA98 format. Also a simple IA calculator is provided where the environmental impact of each LCI dataset can be calculated based on the three different IA methods. (iii) unknown (iv) unknown

  11. A

    Boston Buildings Inventory

    • data.boston.gov
    csv, pdf, xlsx
    Updated May 5, 2020
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    Environment Department (2020). Boston Buildings Inventory [Dataset]. https://data.boston.gov/dataset/boston-buildings-inventory
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    csv(15969), pdf(4952544), csv(17176), xlsx(90559), csv(47663162), csv(2868)Available download formats
    Dataset updated
    May 5, 2020
    Dataset authored and provided by
    Environment Department
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Boston
    Description

    This dataset pulls from many different data sources to identify individual building characteristics of all buildings in Boston. It also identifies high-potential retrofit options to reduce carbon emissions in multifamily buildings, using the best available data and assumptions from building experts.

    Building characteristics will require on-site verification before an owner can act on them.

    Find out more about carbon targets for Boston's existing large buildings.

  12. China CN: Wholesale & Retail Inventory: Total

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China CN: Wholesale & Retail Inventory: Total [Dataset]. https://www.ceicdata.com/en/china/wholesale-and-retail-inventory-above-designated-size-enterprise/cn-wholesale--retail-inventory-total
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2007 - Dec 1, 2018
    Area covered
    China
    Variables measured
    Domestic Trade
    Description

    China Wholesale & Retail Inventory: Total data was reported at 4,211.718 RMB bn in 2018. This records a decrease from the previous number of 4,339.700 RMB bn for 2017. China Wholesale & Retail Inventory: Total data is updated yearly, averaging 1,536.815 RMB bn from Dec 1998 (Median) to 2018, with 21 observations. The data reached an all-time high of 4,339.700 RMB bn in 2017 and a record low of 352.760 RMB bn in 2004. China Wholesale & Retail Inventory: Total data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Wholesale and Retail Inventory: Above Designated Size Enterprise.

  13. O

    Asset Inventory: Austin Open Data Portal

    • data.austintexas.gov
    • datahub.austintexas.gov
    application/rdfxml +5
    Updated Jul 5, 2025
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    (2025). Asset Inventory: Austin Open Data Portal [Dataset]. https://data.austintexas.gov/City-Government/Asset-Inventory-Austin-Open-Data-Portal/my8q-n4hf
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    csv, tsv, application/rssxml, application/rdfxml, json, xmlAvailable download formats
    Dataset updated
    Jul 5, 2025
    Description

    This asset is a derived view based on the system dataset 'Site Analytics: Asset Inventory' which is automatically generated by the data management platform and provides a comprehensive inventory of all assets on this site. This asset has been filtered to present an overview of the various types of data that are classified as public and have been published on the City of Austin Open Data Portal (data.austintexas.gov) by departmental data owners.

    The columns of the Asset Inventory dataset contain information about every asset. These include metadata fields (e.g., Name, Description, and Category), as well as statistics, such as the number of visits, row count, column count, and downloads. This asset is updated at least once per day to sync any changes, additional assets, or removed assets.

    Data provided by: Tyler Technologies Creation date of data source: November 1, 2022

    *City of Austin Open Data Terms of Use – https://data.austintexas.gov/stories/s/ranj-cccq

  14. O

    Online Inventory Management Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated May 23, 2025
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    Data Insights Market (2025). Online Inventory Management Software Report [Dataset]. https://www.datainsightsmarket.com/reports/online-inventory-management-software-1369628
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    May 23, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The online inventory management software market, currently valued at $1661 million in 2025, is projected to experience robust growth, driven by the increasing adoption of cloud-based solutions and the expanding e-commerce sector. Businesses of all sizes are seeking streamlined inventory management to optimize operations, reduce costs, and improve efficiency. The demand for real-time inventory tracking, automated ordering, and integrated sales channels fuels this growth. Key market drivers include the need for enhanced supply chain visibility, improved forecasting accuracy, and reduced manual errors associated with traditional inventory methods. The trend towards mobile accessibility and integration with other business software further contributes to market expansion. While challenges such as initial implementation costs and the need for robust cybersecurity measures exist, the long-term benefits of improved inventory control and data-driven decision-making outweigh these concerns. Competition within the market is fierce, with established players like QuickBooks and Xero competing alongside specialized solutions like Fishbowl and Cin7. The market's continued growth trajectory indicates significant opportunity for both established vendors and emerging players. The forecast period of 2025-2033 anticipates a Compound Annual Growth Rate (CAGR) of 7.7%, signifying a consistent upward trend. This growth will be propelled by several factors, including the rising adoption of omnichannel retailing strategies, the increasing integration of artificial intelligence and machine learning for predictive inventory analysis, and a growing demand for specialized inventory management solutions catering to niche industries like retail, manufacturing, and healthcare. The market segmentation, while not explicitly detailed, likely encompasses solutions categorized by business size (SMB vs. Enterprise), industry vertical, and deployment model (cloud-based vs. on-premise). Regional variations in adoption rates will also shape the market landscape, with North America and Europe anticipated as key markets due to their established technological infrastructure and strong e-commerce presence. Strategic partnerships and acquisitions are anticipated to further consolidate the market, leading to a landscape dominated by key players with comprehensive and scalable solutions.

  15. S

    Stock Control Software Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Mar 20, 2025
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    Market Research Forecast (2025). Stock Control Software Report [Dataset]. https://www.marketresearchforecast.com/reports/stock-control-software-41701
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    doc, ppt, pdfAvailable download formats
    Dataset updated
    Mar 20, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global stock control software market is experiencing robust growth, driven by the increasing need for efficient inventory management across diverse industries. The rising adoption of cloud-based solutions, coupled with the expanding e-commerce landscape and the demand for real-time inventory visibility, are key factors fueling this expansion. Small and medium-sized enterprises (SMEs) represent a significant portion of the market, seeking cost-effective and scalable solutions to optimize their supply chains. Large enterprises, on the other hand, are investing in sophisticated stock control software to improve operational efficiency, reduce costs, and enhance their decision-making capabilities. The market is segmented by deployment (on-cloud and on-premise) and user type (large enterprises and SMEs), with the cloud-based segment demonstrating faster growth due to its flexibility and accessibility. Geographic growth is diverse, with North America and Europe currently holding significant market share, but the Asia-Pacific region is poised for substantial expansion driven by rapid economic development and increasing digitalization. Competitive pressures are intense, with numerous established players and emerging startups vying for market share. This competitive environment fosters innovation and drives the development of new features, such as advanced analytics and integration with other enterprise resource planning (ERP) systems. The overall market trajectory suggests continued growth over the next decade, propelled by ongoing technological advancements and the expanding demand for efficient inventory management across global markets. While on-premise solutions still hold a share, the shift toward cloud-based solutions is undeniable, driven by cost savings, accessibility, and scalability. The integration of AI and machine learning capabilities into stock control software is further enhancing its utility, predicting demand, optimizing ordering, and minimizing waste. However, challenges remain, including data security concerns, the need for robust integration with existing systems, and the potential for high implementation costs for complex solutions within larger organizations. The market's future hinges on addressing these challenges through the development of secure, user-friendly, and cost-effective solutions tailored to diverse business needs across various industries and geographic locations. Continuous innovation and adaptation to evolving business practices will be crucial for success in this dynamic market.

  16. Long-term tree inventory dataset from the permanent sampling plot in the...

    • gbif.org
    Updated Aug 20, 2021
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    Olga V. Smirnova; Maxim V. Bobrovsky; Roman V. Popadiouk; Maxim P. Shashkov; Larisa G. Khanina; Natalya V. Ivanova; Vladimir N. Shanin; Miroslav N. Stamenov; Sergey I. Chumachenko; Olga V. Smirnova; Maxim V. Bobrovsky; Roman V. Popadiouk; Maxim P. Shashkov; Larisa G. Khanina; Natalya V. Ivanova; Vladimir N. Shanin; Miroslav N. Stamenov; Sergey I. Chumachenko (2021). Long-term tree inventory dataset from the permanent sampling plot in the broadleaved forest of European Russia [Dataset]. http://doi.org/10.15468/mu99hf
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    Dataset updated
    Aug 20, 2021
    Dataset provided by
    Global Biodiversity Information Facilityhttps://www.gbif.org/
    State Nature Reserve "Kaluzhskie Zaseki"
    Authors
    Olga V. Smirnova; Maxim V. Bobrovsky; Roman V. Popadiouk; Maxim P. Shashkov; Larisa G. Khanina; Natalya V. Ivanova; Vladimir N. Shanin; Miroslav N. Stamenov; Sergey I. Chumachenko; Olga V. Smirnova; Maxim V. Bobrovsky; Roman V. Popadiouk; Maxim P. Shashkov; Larisa G. Khanina; Natalya V. Ivanova; Vladimir N. Shanin; Miroslav N. Stamenov; Sergey I. Chumachenko
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This occurrence dataset provides primary data on repeated tree measurement of two inventories on the permanent sampling plot (8.8 ha) established in the old-growth polydominant broadleaved forest stand in the “Kaluzhskie Zaseki” State Nature Reserve (center of the European part of Russian Federation). The time span between the inventories was 30 years, and a total of more than 11 000 stems were included in the study (11 tree species and 3 genera). During the measurements, the tree species (for some trees only genus was determined), stem diameter at breast height of 1.3 m (DBH), and life status were recorded for every individual stem, and some additional attributes were determined for some trees. Field data were digitized and compiled into the PostgreSQL database. Deep data cleaning and validation (with documentation of changes) has been performed before data standardization according to the Darwin Core standard.

    Представлены первичные данные двух перечетов деревьев, выполненных на постоянной пробной площади (8.8 га), заложенной в старовозрастном полидоминантном широколиственном лесу в заповеднике “Калужские засеки”. Перечеты выполнены с разницей в 30 лет, всего исследовано более 11 000 учетных единиц (деревья 11-ти видов и 3-х родов). Для каждой учетной единицы определяли вид, диаметр на высоте 1.3 м и статус, для части деревьев также измеряли дополнительные характеристики. Все полевые данные были оцифрованы и организованы в базу данных в среде PostgreSQL. Перед стандартизацией данных в соответствии с Darwin Core выполнена их тщательная проверка, все внесенные изменения документированы.

  17. d

    Enterprise Dataset Inventory

    • catalog.data.gov
    • opendata.dc.gov
    • +1more
    Updated Feb 4, 2025
    + more versions
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    Office of the Chief Technology Officer (2025). Enterprise Dataset Inventory [Dataset]. https://catalog.data.gov/dataset/enterprise-dataset-inventory-062ac
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    Office of the Chief Technology Officer
    Description

    Mayor's Order 2017-115 establishes a comprehensive data policy for the District government. The data created and managed by the District government are valuable assets and are independent of the information systems in which the data reside. As such, the District government shall: maintain an inventory of its enterprise datasets; classify enterprise datasets by level of sensitivity; regularly publish the inventory, including the classifications, as an open dataset; and strategically plan and manage its investment in data.The greatest value from the District’s investment in data can only be realized when enterprise datasets are freely shared among District agencies, with federal and regional governments, and with the public to the fullest extent consistent with safety, privacy, and security. For more information, please visit https://opendata.dc.gov/pages/edi-overview. Previous years of EDI can be found on Open Data.

  18. I

    Inventory Control System Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Jan 31, 2025
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    Market Research Forecast (2025). Inventory Control System Report [Dataset]. https://www.marketresearchforecast.com/reports/inventory-control-system-15281
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    doc, pdf, pptAvailable download formats
    Dataset updated
    Jan 31, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Market Overview The global inventory control system market is projected to reach USD 5.5 billion by 2033, exhibiting a CAGR of 4.6% from 2025 to 2033. The growing need for efficient inventory management in various industries, including retail, manufacturing, and healthcare, is driving market growth. The increasing adoption of cloud-based inventory control systems and the rise of e-commerce are further propelling market expansion. Market Segments The market is segmented based on type (on-premise, cloud-based) and application (large enterprises, SMEs). On-premise systems are primarily deployed within an organization's infrastructure, while cloud-based systems are hosted on third-party servers and accessed over the internet. Large enterprises are expected to hold a significant market share due to their complex inventory management requirements and ability to invest in advanced systems. However, SMEs are projected to witness faster growth as they seek affordable and scalable inventory management solutions. Key players in the market include Oracle, Clear Spider, TrackVia, Monday, TradeGecko, SAP, KCSI, Zoho Inventory, and InFlow Inventory Software.

  19. Drug Inventory Management Software Market Report | Global Forecast From 2025...

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 12, 2024
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    Dataintelo (2024). Drug Inventory Management Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/drug-inventory-management-software-market
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    csv, pdf, pptxAvailable download formats
    Dataset updated
    Sep 12, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Drug Inventory Management Software Market Outlook



    The global Drug Inventory Management Software market size was valued at approximately USD 3.2 billion in 2023 and is expected to reach USD 7.6 billion by 2032, growing at a CAGR of 10.2% during the forecast period. The market growth is primarily driven by increasing demand for streamlined operations in healthcare facilities, enhanced regulatory compliance, and the proliferation of modern technologies.



    One of the primary growth factors for the Drug Inventory Management Software market is the escalating need for efficient management of drug inventories in healthcare facilities. Hospitals, pharmacies, and clinics are experiencing rising patient volumes, which necessitates the adoption of sophisticated software solutions to track and manage drug stocks efficiently. Furthermore, the healthcare sector is under continuous pressure to reduce medication errors and ensure timely availability of essential drugs, thereby fueling the demand for inventory management systems.



    Another key driver is the growing emphasis on regulatory compliance. Governments and healthcare authorities across the globe are imposing stringent regulations to ensure the safety and efficacy of drugs. This has led to an increased adoption of inventory management software that can help healthcare providers adhere to these regulations by maintaining accurate records and providing real-time tracking of drug inventories. Additionally, the integration of advanced technologies such as artificial intelligence and machine learning in these systems is further enhancing their efficiency and reliability.



    The rising trend of digital transformation in the healthcare sector is also significantly contributing to market growth. The adoption of cloud-based solutions is on the rise due to their scalability, cost-effectiveness, and ease of use. Cloud-based drug inventory management software allows healthcare providers to access data from remote locations, facilitating better inventory control and decision-making processes. Moreover, the integration of Internet of Things (IoT) devices with inventory management systems is enabling real-time monitoring and automated restocking, further boosting market growth.



    Regionally, North America holds a dominant share in the Drug Inventory Management Software market, driven by the presence of advanced healthcare infrastructure, high adoption of technological innovations, and stringent regulatory frameworks. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, attributed to the rapidly growing healthcare sector, increasing investment in healthcare IT, and rising awareness about the benefits of inventory management solutions.



    Component Analysis



    The Drug Inventory Management Software market by component is bifurcated into software and services. The software segment is expected to hold the largest market share during the forecast period. This can be attributed to the increasing adoption of advanced software solutions that offer comprehensive functionalities such as tracking, forecasting, inventory optimization, and regulatory compliance. These software systems are designed to cater to the specific needs of healthcare providers, ensuring efficient and accurate management of drug inventories.



    Within the software segment, the demand for cloud-based software solutions is surging due to their numerous advantages over traditional on-premises systems. Cloud-based solutions offer greater flexibility, scalability, and cost-efficiency, enabling healthcare providers to manage their inventories more effectively. Additionally, cloud solutions facilitate seamless integration with other healthcare systems, enhancing overall operational efficiency.



    The services segment, although smaller in market size compared to software, is expected to grow at a significant rate during the forecast period. This growth is driven by the increasing need for implementation, training, and support services associated with drug inventory management software. Healthcare providers are seeking professional services to ensure the successful deployment and optimal utilization of these systems. Furthermore, the rising trend of outsourcing IT services in the healthcare sector is contributing to the growth of the services segment.



    Moreover, the continuous advancements in software technologies are propelling the development of innovative features and functionalities in drug inventory management systems. Companies are investing in research and developm

  20. I

    Inventory Tracking Software Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Feb 10, 2025
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    Archive Market Research (2025). Inventory Tracking Software Report [Dataset]. https://www.archivemarketresearch.com/reports/inventory-tracking-software-48716
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Feb 10, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global inventory tracking software market is anticipated to experience substantial growth in the coming years, driven by the increasing adoption of digital technologies and the need for real-time inventory visibility. The market size is expected to reach USD XX million by 2033, with a CAGR of XX during the forecast period. Key drivers include the rising demand for efficient inventory management, the proliferation of e-commerce, and the need for improved supply chain optimization. Segmentation analysis reveals that web-based software holds a significant market share due to its accessibility and cost-effectiveness. DSM software and CRM software are also witnessing strong growth, driven by the demand for advanced inventory management capabilities. Regionally, North America and Europe are prominent markets due to the presence of mature industries and high adoption of technology. Asia Pacific and the Middle East & Africa are emerging markets with significant growth potential. Prominent companies in the market include Cox Automotive, CDK Global, Reynolds and Reynolds, RouteOne, and Dominion Enterprises. These players are focusing on innovation, strategic acquisitions, and partnerships to expand their offerings and meet the evolving needs of customers.

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willian oliveira (2025). Grocery Inventory [Dataset]. http://doi.org/10.34740/kaggle/dsv/11053760
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Grocery Inventory

Sales Dataset Inventory and Sales Data for Grocery Store Management.

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CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Mar 16, 2025
Dataset provided by
Kaggle
Authors
willian oliveira
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Description

this graph was created in R and Canva :

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F1a47e2e6e4836b86b065441359d5c9f0%2Fgraph1.gif?generation=1742159161939732&alt=media" alt=""> https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F87de025c5703cb69483764c4fc9c58ab%2Fgraph2.gif?generation=1742159169346925&alt=media" alt=""> https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Fddf5001438c97c8c030333261685849b%2Fgraph3.png?generation=1742159174793142&alt=media" alt="">

The dataset offers a comprehensive view of grocery inventory, covering 990 products across multiple categories such as Grains & Pulses, Beverages, Fruits & Vegetables, and more. It includes crucial details about each product, such as its unique identifier (Product_ID), name, category, and supplier information, including Supplier_ID and Supplier_Name. This dataset is particularly valuable for businesses aiming to optimize inventory management, sales tracking, and supply chain efficiency.

Key inventory-related fields include Stock_Quantity, which indicates the current stock level, and Reorder_Level, which determines when a product should be reordered. The Reorder_Quantity specifies how much stock to order when inventory falls below the reorder threshold. Additionally, Unit_Price provides insight into pricing, helping businesses analyze cost trends and profitability.

To manage product flow, the dataset includes dates such as Date_Received, which tracks when the product was added to the warehouse, and Last_Order_Date, marking the most recent procurement. For perishable goods, the Expiration_Date column is critical, allowing businesses to minimize waste by monitoring shelf life. The Warehouse_Location specifies where each product is stored, facilitating efficient inventory handling.

Sales and performance metrics are also included. The Sales_Volume column records the total number of units sold, providing insights into consumer demand. Inventory_Turnover_Rate helps businesses assess how quickly a product sells and is replenished, ensuring better stock management. The dataset also tracks the Status of each product, indicating whether it is Active, Discontinued, or Backordered.

The dataset serves multiple purposes in inventory management, sales performance evaluation, supplier analysis, and product lifecycle tracking. Businesses can leverage this data to refine reorder strategies, ensuring optimal stock levels and avoiding stockouts or excessive inventory. Sales analysis can help identify high-demand products and slow-moving items, enabling better decision-making in pricing and promotions. Evaluating suppliers based on their performance, pricing, and delivery efficiency helps streamline procurement and improve overall supply chain operations.

Furthermore, the dataset can support predictive analytics by employing machine learning techniques to estimate reorder quantities, forecast demand, and optimize stock replenishment. Inventory turnover insights can aid in maintaining a balanced supply, preventing unnecessary overstocking or shortages. By tracking trends in sales, businesses can refine their marketing and distribution strategies, ensuring sustained profitability.

This dataset is designed for educational and demonstration purposes, offering fictional data under the Creative Commons Attribution 4.0 International License. Users are free to analyze, modify, and apply the data while providing proper attribution. Additionally, certain products are marked as discontinued or backordered, reflecting real-world inventory dynamics. Businesses dealing with perishable goods should closely monitor expiration and last order dates to avoid losses due to spoilage.

Overall, this dataset provides a versatile resource for those interested in inventory management, sales analysis, and supply chain optimization. By leveraging the structured data, businesses can make data-driven decisions to enhance operational efficiency and maximize profitability.

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