This is a spreadsheet of 1 of 10 companies in the shoe industry. Highlighting COGS, Total Revenue, Market share and Industry share.

The annual Retail store data CD-ROM is an easy-to-use tool for quickly discovering retail trade patterns and trends. The current product presents results from the 1999 and 2000 Annual Retail Store and Annual Retail Chain surveys. This product contains numerous cross-classified data tables using the North American Industry Classification System (NAICS). The data tables provide access to a wide range of financial variables, such as revenues, expenses, inventory, sales per square footage (chain stores only) and the number of stores. Most data tables contain detailed information on industry (as low as 5-digit NAICS codes), geography (Canada, provinces and territories) and store type (chains, independents, franchises). The electronic product also contains survey metadata, questionnaires, information on industry codes and definitions, and the list of retail chain store respondents.

1.Introduction

Sales data collection is a crucial aspect of any manufacturing industry as it provides valuable insights about the performance of products, customer behaviour, and market trends. By gathering and analysing this data, manufacturers can make informed decisions about product development, pricing, and marketing strategies in Internet of Things (IoT) business environments like the dairy supply chain.

One of the most important benefits of the sales data collection process is that it allows manufacturers to identify their most successful products and target their efforts towards those areas. For example, if a manufacturer could notice that a particular product is selling well in a certain region, this information could be utilised to develop new products, optimise the supply chain or improve existing ones to meet the changing needs of customers.

This dataset includes information about 7 of MEVGAL’s products [1]. According to the above information the data published will help researchers to understand the dynamics of the dairy market and its consumption patterns, which is creating the fertile ground for synergies between academia and industry and eventually help the industry in making informed decisions regarding product development, pricing and market strategies in the IoT playground. The use of this dataset could also aim to understand the impact of various external factors on the dairy market such as the economic, environmental, and technological factors. It could help in understanding the current state of the dairy industry and identifying potential opportunities for growth and development.

1. Citation

Please cite the following papers when using this dataset:

I. Siniosoglou, K. Xouveroudis, V. Argyriou, T. Lagkas, S. K. Goudos, K. E. Psannis and P. Sarigiannidis, "Evaluating the Effect of Volatile Federated Timeseries on Modern DNNs: Attention over Long/Short Memory," in the 12th International Conference on Circuits and Systems Technologies (MOCAST 2023), April 2023, Accepted

1. Dataset Modalities

The dataset includes data regarding the daily sales of a series of dairy product codes offered by MEVGAL. In particular, the dataset includes information gathered by the logistics division and agencies within the industrial infrastructures overseeing the production of each product code. The products included in this dataset represent the daily sales and logistics of a variety of yogurt-based stock. Each of the different files include the logistics for that product on a daily basis for three years, from 2020 to 2022.

3.1 Data Collection

The process of building this dataset involves several steps to ensure that the data is accurate, comprehensive and relevant.

The first step is to determine the specific data that is needed to support the business objectives of the industry, i.e., in this publication’s case the daily sales data.

Once the data requirements have been identified, the next step is to implement an effective sales data collection method. In MEVGAL’s case this is conducted through direct communication and reports generated each day by representatives & selling points.

It is also important for MEVGAL to ensure that the data collection process conducted is in an ethical and compliant manner, adhering to data privacy laws and regulation. The industry also has a data management plan in place to ensure that the data is securely stored and protected from unauthorised access.

The published dataset is consisted of 13 features providing information about the date and the number of products that have been sold. Finally, the dataset was anonymised in consideration to the privacy requirement of the data owner (MEVGAL).

File

Period

Number of Samples (days)

product 1 2020.xlsx

01/01/2020–31/12/2020

363

product 1 2021.xlsx

01/01/2021–31/12/2021

364

product 1 2022.xlsx

01/01/2022–31/12/2022

365

product 2 2020.xlsx

01/01/2020–31/12/2020

363

product 2 2021.xlsx

01/01/2021–31/12/2021

364

product 2 2022.xlsx

01/01/2022–31/12/2022

365

product 3 2020.xlsx

01/01/2020–31/12/2020

363

product 3 2021.xlsx

01/01/2021–31/12/2021

364

product 3 2022.xlsx

01/01/2022–31/12/2022

365

product 4 2020.xlsx

01/01/2020–31/12/2020

363

product 4 2021.xlsx

01/01/2021–31/12/2021

364

product 4 2022.xlsx

01/01/2022–31/12/2022

364

product 5 2020.xlsx

01/01/2020–31/12/2020

363

product 5 2021.xlsx

01/01/2021–31/12/2021

364

product 5 2022.xlsx

01/01/2022–31/12/2022

365

product 6 2020.xlsx

01/01/2020–31/12/2020

362

product 6 2021.xlsx

01/01/2021–31/12/2021

364

product 6 2022.xlsx

01/01/2022–31/12/2022

365

product 7 2020.xlsx

01/01/2020–31/12/2020

362

product 7 2021.xlsx

01/01/2021–31/12/2021

364

product 7 2022.xlsx

01/01/2022–31/12/2022

365

3.2 Dataset Overview

The following table enumerates and explains the features included across all of the included files.

Feature

Description

Unit

Day

day of the month

-

Month

Month

-

Year

Year

-

daily_unit_sales

Daily sales - the amount of products, measured in units, that during that specific day were sold

units

previous_year_daily_unit_sales

Previous Year’s sales - the amount of products, measured in units, that during that specific day were sold the previous year

units

percentage_difference_daily_unit_sales

The percentage difference between the two above values

%

daily_unit_sales_kg

The amount of products, measured in kilograms, that during that specific day were sold

kg

previous_year_daily_unit_sales_kg

Previous Year’s sales - the amount of products, measured in kilograms, that during that specific day were sold, the previous year

kg

percentage_difference_daily_unit_sales_kg

The percentage difference between the two above values

kg

daily_unit_returns_kg

The percentage of the products that were shipped to selling points and were returned

%

previous_year_daily_unit_returns_kg

The percentage of the products that were shipped to selling points and were returned the previous year

%

points_of_distribution

The amount of sales representatives through which the product was sold to the market for this year

previous_year_points_of_distribution

The amount of sales representatives through which the product was sold to the market for the same day for the previous year

Table 1 – Dataset Feature Description

1. Structure and Format

4.1 Dataset Structure

The provided dataset has the following structure:

Where:

Name

Type

Property

Readme.docx

Report

A File that contains the documentation of the Dataset.

product X

Folder

A folder containing the data of a product X.

product X YYYY.xlsx

Data file

An excel file containing the sales data of product X for year YYYY.

Table 2 - Dataset File Description

1. Acknowledgement

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 957406 (TERMINET).

References

[1] MEVGAL is a Greek dairy production company

This CD-ROM product is an authoritative reference source of 15 key financial ratios by industry groupings compiled from the North American Industry Classification System (NAICS 2007). It is based on up-to-date, reliable and comprehensive data on Canadian businesses, derived from Statistics Canada databases of financial statements for three reference years. The CD-ROM enables users to compare their enterprise's performance to that of their industry and to address issues such as profitability, efficiency and business risk. Financial Performance Indicators can also be used for inter-industry comparisons. Volume 1 covers large enterprises in both the financial and non-financial sectors, at the national level, with annual operating revenue of $25 million or more. Volume 2 covers medium-sized enterprises in the non-financial sector, at the national level, with annual operating revenue of $5 million to less than $25 million. Volume 3 covers small enterprises in the non-financial sector, at the national, provincial, territorial, Atlantic region and Prairie region levels, with annual operating revenue of $30,000 to less than $5 million. Note: FPICB has been discontinued as of 2/23/2015. Statistics Canada continues to provide information on Canadian businesses through alternative data sources. Information on specific financial ratios will continue to be available through the annual Financial and Taxation Statistics for Enterprises program: CANSIM table 180-0003 ; the Quarterly Survey of Financial Statements: CANSIM tables 187-0001 and 187-0002 ; and the Small Business Profiles, which present financial data for small businesses in Canada, available on Industry Canada's website: Financial Performance Data.

About Dataset The dataset contains information about sales transactions, including details such as the customer's age, gender, location, and the products sold. The dataset includes data on both the cost of the product and the revenue generated from its sale, allowing for calculations of profit and profit margins. The dataset includes information on customer age and gender, which could be used to analyze purchasing behavior across different demographic groups. The dataset likely includes both numeric and categorical data, which would require different types of analysis and visualization techniques. Overall, the dataset appears to provide a comprehensive view of sales transactions, with the potential for analysis at multiple levels, including by product, customer, and location. But it does not contain any useful information or insights for decision makers. - After understanding the dataset. - I cleaned it and add some columns & calculations like (Net profit, Age Status). - Making a model in Power Pivot, calculate some measures like (Total profit, COGS, Total revenues) and Making KPIS Model. - Then asked some questions: About Distribution What are the total revenues and profits? What is the best-selling country in terms of revenue? What are the five best-selling states in terms of revenue? What are the five lowest-selling states in terms of revenues? What is the position of age in relation to revenues? About profitability What are the total revenues and profits? Monthly position in terms of revenues and profits? Months position in terms of COGS? What are the top category-selling in terms of revenues & Profit? What are the three best-selling sub-category in terms of profit? About KPIS Explain to me each salesperson's position in terms of Target

• Then Answering that questions, analysis the data and Visualize with Dashboards.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Success.ai’s Ecommerce Store Data for the APAC E-commerce Sector provides a reliable and accurate dataset tailored for businesses aiming to connect with e-commerce professionals and organizations across the Asia-Pacific region. Covering roles and businesses involved in online retail, marketplace management, logistics, and digital commerce, this dataset includes verified business profiles, decision-maker contact details, and actionable insights.

With access to continuously updated, AI-validated data and over 700 million global profiles, Success.ai ensures your outreach, market analysis, and partnership strategies are effective and data-driven. Backed by our Best Price Guarantee, this solution helps you excel in one of the world’s fastest-growing e-commerce markets.

Why Choose Success.ai’s Ecommerce Store Data?

1. Verified Profiles for Precision Engagement

   • Access verified profiles, business locations, employee counts, and decision-maker details for e-commerce businesses across APAC.
   • AI-driven validation ensures 99% accuracy, improving engagement rates and reducing outreach inefficiencies.

2. Comprehensive Coverage of the APAC E-commerce Sector

   • Includes businesses from major e-commerce hubs such as China, India, Japan, South Korea, Australia, and Southeast Asia.
   • Gain insights into regional e-commerce trends, digital transformation efforts, and logistics innovations.

3. Continuously Updated Datasets

   • Real-time updates ensure that business profiles, employee roles, and operational insights remain accurate and relevant.
   • Stay aligned with dynamic market conditions and emerging opportunities in the APAC region.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Access business profiles for e-commerce professionals and organizations across APAC.
• Firmographic Insights: Gain detailed information, including business locations, employee counts, and operational details.
• Decision-maker Profiles: Connect with key e-commerce leaders, managers, and strategists driving online retail innovation.
• Industry Trends: Understand emerging e-commerce trends, consumer behavior, and market dynamics in the APAC region.

Key Features of the Dataset:

1. Comprehensive E-commerce Business Profiles

   • Identify and connect with businesses specializing in online retail, marketplace management, and digital commerce logistics.
   • Target decision-makers involved in supply chain optimization, digital marketing, and platform development.

2. Advanced Filters for Precision Campaigns

   • Filter businesses and professionals by industry focus (fashion, electronics, grocery), geographic location, or employee size.
   • Tailor campaigns to address specific goals, such as promoting technology adoption, enhancing customer engagement, or expanding supply chains.

3. Regional and Sector-specific Insights

   • Leverage data on APAC’s fast-growing e-commerce markets, consumer purchasing trends, and regional challenges.
   • Refine your marketing strategies and outreach efforts to align with market priorities.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Outreach

   • Promote e-commerce solutions, logistics services, or digital commerce tools to businesses and professionals in the APAC region.
   • Use verified contact data for multi-channel outreach, including email, phone, and social media campaigns.

2. Partnership Development and Vendor Collaboration

   • Build relationships with e-commerce marketplaces, logistics providers, and payment solution companies seeking strategic partnerships.
   • Foster collaborations that drive operational efficiency, enhance customer experiences, or expand market reach.

3. Market Research and Competitive Analysis

   • Analyze regional e-commerce trends, consumer preferences, and logistics challenges to refine product offerings and business strategies.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the e-commerce industry recruiting for roles in operations, logistics, and digital marketing.
   • Provide workforce optimization platforms or training solutions tailored to the digital commerce sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce store data at competitive prices, ensuring strong ROI for your marketing, sales, and strategic initiatives.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics platforms, or market...

This dataset contains a list of sales and movement data by item and department appended monthly. Update Frequency : Monthly

The extent to which individual businesses in Great Britain experienced actual changes in their sales.

Analyzing Coffee Shop Sales: Excel Insights 📈

In my first Data Analytics Project, I Discover the secrets of a fictional coffee shop's success with my data-driven analysis. By Analyzing a 5-sheet Excel dataset, I've uncovered valuable sales trends, customer preferences, and insights that can guide future business decisions. 📊☕

DATA CLEANING 🧹

• REMOVED DUPLICATES OR IRRELEVANT ENTRIES: Thoroughly eliminated duplicate records and irrelevant data to refine the dataset for analysis.

• FIXED STRUCTURAL ERRORS: Rectified any inconsistencies or structural issues within the data to ensure uniformity and accuracy.

• CHECKED FOR DATA CONSISTENCY: Verified the integrity and coherence of the dataset by identifying and resolving any inconsistencies or discrepancies.

DATA MANIPULATION 🛠️

• UTILIZED LOOKUPS: Used Excel's lookup functions for efficient data retrieval and analysis.

• IMPLEMENTED INDEX MATCH: Leveraged the Index Match function to perform advanced data searches and matches.

• APPLIED SUMIFS FUNCTIONS: Utilized SumIFs to calculate totals based on specified criteria.

• CALCULATED PROFITS: Used relevant formulas and techniques to determine profit margins and insights from the data.

PIVOTING THE DATA 𝄜

• CREATED PIVOT TABLES: Utilized Excel's PivotTable feature to pivot the data for in-depth analysis.

• FILTERED DATA: Utilized pivot tables to filter and analyze specific subsets of data, enabling focused insights. Specially used in “PEAK HOURS” and “TOP 3 PRODUCTS” charts.

VISUALIZATION 📊

• KEY INSIGHTS: Unveiled the grand total sales revenue while also analyzing the average bill per person, offering comprehensive insights into the coffee shop's performance and customer spending habits.

• SALES TREND ANALYSIS: Used Line chart to compute total sales across various time intervals, revealing valuable insights into evolving sales trends.

• PEAK HOUR ANALYSIS: Leveraged Clustered Column chart to identify peak sales hours, shedding light on optimal operating times and potential staffing needs.

• TOP 3 PRODUCTS IDENTIFICATION: Utilized Clustered Bar chart to determine the top three coffee types, facilitating strategic decisions regarding inventory management and marketing focus.

*I also used a Timeline to visualize chronological data trends and identify key patterns over specific times.

While it's a significant milestone for me, I recognize that there's always room for growth and improvement. Your feedback and insights are invaluable to me as I continue to refine my skills and tackle future projects. I'm eager to hear your thoughts and suggestions on how I can make my next endeavor even more impactful and insightful.

THANKS TO: WsCube Tech Mo Chen Alex Freberg

TOOLS USED: Microsoft Excel

DataAnalytics #DataAnalyst #ExcelProject #DataVisualization #BusinessIntelligence #SalesAnalysis #DataAnalysis #DataDrivenDecisions

The global market size of Coffee Shop is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Coffee Shop Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Coffee Shop industry. The key insights of the report:
1.The report provides key statistics on the market status of the Coffee Shop manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Coffee Shop industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Coffee Shop Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Coffee Shop as well as some small players.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Coffee Shop market
* Product Type I
* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
* Application II
* Application III

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
* Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and non-economic aspects
* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.

Success.ai’s Ecommerce Market Data for South-east Asia E-commerce Contacts provides a robust and accurate dataset tailored for businesses and organizations looking to connect with professionals in the fast-growing e-commerce industry across South-east Asia. Covering roles such as e-commerce managers, digital strategists, logistics experts, and online marketplace leaders, this dataset offers verified contact details, professional insights, and actionable market data.

With access to over 170 million verified profiles globally, Success.ai ensures your outreach, marketing, and research strategies are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution empowers you to excel in one of the world’s most dynamic e-commerce regions.

Why Choose Success.ai’s Ecommerce Market Data?

1. Verified Contact Data for Precision Outreach

   • Access verified work emails, phone numbers, and LinkedIn profiles of e-commerce professionals across South-east Asia.
   • AI-driven validation ensures 99% accuracy, reducing communication inefficiencies and enhancing engagement rates.

2. Comprehensive Coverage of South-east Asia’s E-commerce Market

   • Includes professionals from key e-commerce hubs such as Singapore, Indonesia, Thailand, Vietnam, Malaysia, and the Philippines.
   • Gain insights into regional consumer trends, logistics challenges, and online marketplace dynamics.

3. Continuously Updated Datasets

   • Real-time updates capture changes in professional roles, company expansions, and market conditions.
   • Stay aligned with industry trends and emerging opportunities in South-east Asia’s e-commerce sector.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 170M+ Verified Global Profiles: Engage with e-commerce professionals and decision-makers across South-east Asia.
• Verified Contact Details: Gain work emails, phone numbers, and LinkedIn profiles for precision targeting.
• Regional Insights: Understand key trends in e-commerce, logistics, and consumer preferences in South-east Asia.
• Leadership Insights: Connect with online marketplace leaders, logistics managers, and digital marketing professionals driving innovation in the sector.

Key Features of the Dataset:

1. Comprehensive Professional Profiles in E-commerce

   • Identify and connect with professionals managing e-commerce platforms, online marketplaces, and logistics operations.
   • Target individuals responsible for digital marketing, supply chain management, and e-commerce strategies.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (apparel, electronics, food delivery), geographic location, or job function.
   • Tailor campaigns to align with specific business goals, such as logistics optimization, consumer engagement, or market entry.

3. Regional and Market-specific Insights

   • Leverage data on e-commerce trends, regional consumer behaviors, and logistics challenges unique to South-east Asia.
   • Refine marketing strategies and business plans based on actionable insights from the region.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Digital Outreach

   • Promote e-commerce solutions, logistics services, or online marketing tools to professionals in South-east Asia’s e-commerce industry.
   • Use verified contact data for multi-channel outreach, including email, phone, and digital campaigns.

2. Market Research and Competitive Analysis

   • Analyze e-commerce trends and consumer preferences across South-east Asia to refine product offerings and marketing strategies.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

3. Partnership Development and Vendor Collaboration

   • Build relationships with e-commerce platforms, logistics providers, and digital marketing agencies exploring strategic partnerships.
   • Foster collaborations that enhance consumer experiences, improve delivery efficiency, or expand market reach.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the e-commerce industry seeking candidates for logistics, digital marketing, and platform management roles.
   • Provide workforce optimization platforms or training solutions tailored to the sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce market data at competitive prices, ensuring strong ROI for your marketing, sales, and business development initiatives.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics ...

SIBS provides statistical information on strategic decisions, innovation activities and operational tactics used by Canadian enterprises. The survey also collects information on enterprise involvement in global value chains. The data was collected from January 2007 - December 2009. The questions address the following themes: Business strategies and monitoring Enterprise structure Operational activities Relocation of business activities Sales activities Business practices and relationships with suppliers Advanced technology use Product / process / marketing / organizational innovations Production performance management Human resources management Main product and market structure Government support programs Obstacles to innovation

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

The global market size of Mining Laboratory Automation Solutions is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Mining Laboratory Automation Solutions Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Mining Laboratory Automation Solutions industry. The key insights of the report:
1.The report provides key statistics on the market status of the Mining Laboratory Automation Solutions manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Mining Laboratory Automation Solutions industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Mining Laboratory Automation Solutions Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Mining Laboratory Automation Solutions as well as some small players. At least 12 companies are included:
* FLSmidth
* Bruker
* ROCKLABS
* Thermo Fisher Scientific
* GE Energy
* Datech Scientific Limited
For complete companies list, please ask for sample pages.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Mining Laboratory Automation Solutions market
* Automated Analyzers and Sample Preparation Equipment
* Container Laboratory
* Laboratory Information Management Systems (LIMS)
* Robotics
For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Mining Companies
* Laboratories

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
* Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and non-economic aspects
* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Business licenses issued by the Department of Business Affairs and Consumer Protection in the City of Chicago from 2002 to the present. This dataset contains a large number of records/rows of data and may not be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Notepad or Wordpad, to view and search.

Data fields requiring description are detailed below.

APPLICATION TYPE: ‘ISSUE’ is the record associated with the initial license application. ‘RENEW’ is a subsequent renewal record. All renewal records are created with a term start date and term expiration date. ‘C_LOC’ is a change of location record. It means the business moved. ‘C_CAPA’ is a change of capacity record. Only a few license types may file this type of application. ‘C_EXPA’ only applies to businesses that have liquor licenses. It means the business location expanded. 'C_SBA' is a change of business activity record. It means that a new business activity was added or an existing business activity was marked as expired.

LICENSE STATUS: ‘AAI’ means the license was issued. ‘AAC’ means the license was cancelled during its term. ‘REV’ means the license was revoked. 'REA' means the license revocation has been appealed.

LICENSE STATUS CHANGE DATE: This date corresponds to the date a license was cancelled (AAC), revoked (REV) or appealed (REA).

Business License Owner information may be accessed at: https://data.cityofchicago.org/dataset/Business-Owners/ezma-pppn. To identify the owner of a business, you will need the account number or legal name, which may be obtained from this Business Licenses dataset.

Data Owner: Business Affairs and Consumer Protection. Time Period: January 1, 2002 to present. Frequency: Data is updated daily.

Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

Application and use cases

1 )Market Analysis: Evaluate overall trends and regional variations in car sales to assess manufacturer performance, model preferences, and demographic insights. 2) Seasonal Patterns and Competitor Analysis: Investigate seasonal and cyclical patterns in sales. 3) Forecasting and Predictive Analysis Use historical data for forecasting and predict future market trends. Support marketing, advertising, and investment decisions based on insights. 4) Supply Chain and Inventory Optimization: Provide valuable data for stakeholders in the automotive industry.

This statistic depicts the sales of the H&M Group worldwide from 2006 to 2024. In the fiscal year 2024, global net sales of the H&M Group amounted to about 234 billion Swedish kronor. H&MH&M offers a broad and varied range of fashion including collections for women, men, teenagers and children. The range also includes sportswear, underwear, shoes, accessories and cosmetics, as well as home textiles and decorations from H&M Home.Germany is H&M's largest market. In 2024, over 35 billion Swedish kronor were generated from that country alone. The company operates roughly 4,253 stores worldwide and employs approximately 97,710 people. H&M dropped out of the top ten most valuable apparel brands in the world as of 2023.H&M aims to be a more sustainable choice for today’s increasingly aware customers. To this end, H&M’s investments in social improvements and reduced environmental impact extend throughout the product life cycle – from responsible use of natural resources to ensuring good working conditions at suppliers’ factories. Sustainability work is thoroughly integrated into the business, not only because it is an investment in the customer offering,but also because it is vital to the group’s long-term growth and development. However, there have been questions raised as to how effective and trustworthy H&M's sustainability practices really are.