Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
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Business Goal
Date: 2023/09/15
Dataset: Sales quantity of a certain brand from January to December 2022 and from January to September 2023.
Please describe what you observe (no specific presentation format required). Among your observations, identify at least three valuable insights and explain why you consider them valuable.
If more resources were available to you (including time, information, etc.), what would you need, and what more could you achieve?
Metadata of the file Data Period: January 2022 - September 2023 Data Fields: - item - store_id - sales of each month
Metadata of the file Data Period: January 2022 - September 2023 Data Fields: - item - store_id - sales of each month
Sample question & answer 1. Product insights: identify the product sales analysis, such as BCG matrix 2. Store insights: identify the sales performance of the sales 3. Supply chain insights: identify the demand 4. Time series forecasting: identify tread, seasonality
From 2019 to 2023, the sales of fresh produce from online sales channels have increased from 0.7 percent to amost three percent of sales from all channels, constituting an increase of about 2.7 percent dollar sales share.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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This table contains 18 series, with data for years 1946 - 1991 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Components (3 items: Production; Sales; Factory stocks); Standard Classification of Goods (SCG) (6 items: Washing machines; Clothes dryers; Ranges; Small ranges (under 71 centimetres); ...).
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Graph and download economic data for Final Sales of Domestic Product (FINSAL) from Q1 1947 to Q1 2025 about final sales, domestic, production, sales, GDP, and USA.
In 2023, traditional grocery stores had the highest sales share of fresh produce in the U.S. by far, accounting for over 40 percent produce sales. Internet sales of fresh produce accounted for only 2.5 percent of sales.
Although the sales value for organic produce has been growing every year in the U.S. since 2019, conventional produce still has a sales value over seven times higher than organic. Organic sales in 2023 amounted to about *** billion U.S. dollars, whereas conventional produce sales reached **** billion U.S. dollars.
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Graph and download economic data for Average Weekly Earnings of Production Employees: Retail Trade in Grand Rapids-Wyoming-Kentwood, MI (MSA) (SMU26243404200000030) from Jan 2011 to May 2025 about Grand Rapids, MI, earnings, retail trade, production, sales, retail, employment, and USA.
Explore data on domestic sales and production of cement in Saudi Arabia with the SAMA Annual dataset. Find valuable insights and trends to help inform your decisions in the cement industry.
Domestic Sales, Cement, Production, Sales, SAMA Annual Saudi ArabiaFollow data.kapsarc.org for timely data to advance energy economics research..Unit :In thousand tonsIt represents the production and sales of 10 companies , 15 companies , and 17 companies after 2017.
The provided dataset appears to be a sales dataset from a company called "**T-Mart.**" The dataset contains various columns with information about the sales transactions, including the date of the transaction, product details, quantity, sales type, location, payment mode, product category, unit of measurement (UOM), purchase price, and some additional labels and counts.
Based on the given information, here's a brief description of the dataset:
The "T-Mart" sales dataset captures sales transactions with details such as the transaction date, unique product identifier (PRODUCT ID), quantity sold, sales type (Direct Sales, Online, etc.), sales location (e.g., California, Alabama), payment mode (Cash, Online), product details (PRODUCT, CATEGORY, UOM), purchase price, and some additional label-based information.
This dataset provides insights into various aspects of the company's sales operations, including the distribution of sales across different categories, products, and locations, as well as information about the payment modes used for transactions.
Analyzing this dataset can help identify trends, popular products, sales performance by location, and preferred payment methods. It's essential for understanding the company's sales dynamics and making informed business decisions.
This dataset appears to be rich in information, and with the right data visualization techniques, we can uncover valuable insights that can be used for strategic planning and optimizing sales strategies.
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Graph and download economic data for Manufacturers Sales (MNFCTRSMSA) from Jan 1992 to Apr 2025 about sales, manufacturing, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset provides values for MANUFACTURING SALES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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China Industrial Enterprise: Product Sales Ratio data was reported at 98.100 % in 2018. This stayed constant from the previous number of 98.100 % for 2017. China Industrial Enterprise: Product Sales Ratio data is updated yearly, averaging 98.010 % from Dec 1999 (Median) to 2018, with 20 observations. The data reached an all-time high of 98.180 % in 2006 and a record low of 97.150 % in 1999. China Industrial Enterprise: Product Sales Ratio data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BF: Industrial Financial Data.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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Annual estimates for UK manufacturers' sales by product covered by the ProdCom survey.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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Explore our extensive Amazon Product Dataset, featuring detailed information on prices, ratings, sales volume, and more.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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China Tap Water Production & Supply: Product Sales Ratio data was reported at 97.150 % in Aug 2011. This records an increase from the previous number of 96.860 % for Jul 2011. China Tap Water Production & Supply: Product Sales Ratio data is updated monthly, averaging 96.890 % from Feb 2009 (Median) to Aug 2011, with 29 observations. The data reached an all-time high of 97.610 % in May 2009 and a record low of 95.870 % in Feb 2009. China Tap Water Production & Supply: Product Sales Ratio data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Utility Sector – Table CN.RCA: Financial Data: Water Production and Supply: Tap Water Production and Supply.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The tables presents indices (2005=100) and changes on twelve months previously (%) of production, turnover and orders in industry (excluding construction), by sector of industry.
Data available: January 2000 till December 2012
Table has been discontinued as from 22 March 2013 due to change of the base year from 2005 to 2010. Statistics Netherlands has started a new table, Industry; production, sales and orders, changes and index (2010 = 100). For more information see sections 3 and 4.
Status of the figures: Production: three most recent months: Provisional. The figures within a reporting year are revised provisional figures until publication in December of the year concerned. Turnover: three most recent months: Provisional. Orders: three most recent months: Provisional.
Changes as of 8 July 2011. Due to new regulations (European System for National Accounts, 2010, Balance of Payments Manual 6) for National Accounts and Balance of Payment, the turnover definition has been adapted. These results in adjustments in production index and other short term statistics. The adaptation of the turnover definition is related to a change in registration of enterprises that (partially) contract out of their production abroad. The adjustment means that goods deal with foreign subsidiaries of Dutch parent companies do count for Dutch production. Goods dealt with in the Netherlands by Dutch subsidiaries of foreign parent companies that remain property of these parent companies do no longer count as Dutch production. However, they count as export of services for the sum that has been added to value in the Netherlands. Until December 2009, index figures for manufacturing turnover are based on the previous turnover definition. From January 2010 onwards, the turnover figures are based on the new turnover definition. Therefore, turnover changes 2010 on 2009 are not accurate.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset supports the article entitled "Effects of Customer Reviews on Product Sales of Strong Brands: A Qualitative Comparative Analysis."
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Graph and download economic data for Production, Sales, Work Started and Orders: Production Volume: Economic Activity: Industry (Except Construction) for OECD (OECDPRINTO01IXOBSAM) from Jan 1975 to Mar 2024 about OECD Europe, Europe, construction, and production.
Total fresh produce sales in the U.S. have increased since 2019. The increase for the total department is about 8.7 billion U.S. dollars, sales value of 75.8 billion U.S. dollar as of May 2022. This includes all sales outlets.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Retail Sales in the United States decreased 0.90 percent in May of 2025 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
Business Goal
Date: 2023/09/15
Dataset: Sales quantity of a certain brand from January to December 2022 and from January to September 2023.
Please describe what you observe (no specific presentation format required). Among your observations, identify at least three valuable insights and explain why you consider them valuable.
If more resources were available to you (including time, information, etc.), what would you need, and what more could you achieve?
Metadata of the file Data Period: January 2022 - September 2023 Data Fields: - item - store_id - sales of each month
Metadata of the file Data Period: January 2022 - September 2023 Data Fields: - item - store_id - sales of each month
Sample question & answer 1. Product insights: identify the product sales analysis, such as BCG matrix 2. Store insights: identify the sales performance of the sales 3. Supply chain insights: identify the demand 4. Time series forecasting: identify tread, seasonality