1) Data Introduction • The Power BI Sample Data is a financial sample dataset provided for Power BI practice and data visualization exercises that includes a variety of financial metrics and transaction information, including sales, profits, and expenses.

2) Data Utilization (1) Power BI Sample Data has characteristics that: • This dataset consists of numerical and categorical variables such as transaction date, region, product category, sales, profit, and cost, optimized for aggregation, analysis, and visualization. (2) Power BI Sample Data can be used to: • Revenue and Revenue Analysis: Analyze sales and profit data by region, product, and period to understand business performance and trends. • Power BI Dashboard Practice: Utilize a variety of financial metrics and transaction data to design and practice dashboards, reports, visualization charts, and more directly at Power BI.

Company Datasets for valuable business insights!

Discover new business prospects, identify investment opportunities, track competitor performance, and streamline your sales efforts with comprehensive Company Datasets.

These datasets are sourced from top industry providers, ensuring you have access to high-quality information:

• Owler: Gain valuable business insights and competitive intelligence. -AngelList: Receive fresh startup data transformed into actionable insights. -CrunchBase: Access clean, parsed, and ready-to-use business data from private and public companies. -Craft.co: Make data-informed business decisions with Craft.co's company datasets. -Product Hunt: Harness the Product Hunt dataset, a leader in curating the best new products.

We provide fresh and ready-to-use company data, eliminating the need for complex scraping and parsing. Our data includes crucial details such as:

• Company name;
• Size;
• Founding date;
• Location;
• Industry;
• Revenue;
• Employee count;
• Competitors.

You can choose your preferred data delivery method, including various storage options, delivery frequency, and input/output formats.

Receive datasets in CSV, JSON, and other formats, with storage options like AWS S3 and Google Cloud Storage. Opt for one-time, monthly, quarterly, or bi-annual data delivery.

With Oxylabs Datasets, you can count on:

• Fresh and accurate data collected and parsed by our expert web scraping team.
• Time and resource savings, allowing you to focus on data analysis and achieving your business goals.
• A customized approach tailored to your specific business needs.
• Legal compliance in line with GDPR and CCPA standards, thanks to our membership in the Ethical Web Data Collection Initiative.

Pricing Options:

Standard Datasets: choose from various ready-to-use datasets with standardized data schemas, priced from $1,000/month.

Custom Datasets: Tailor datasets from any public web domain to your unique business needs. Contact our sales team for custom pricing.

Experience a seamless journey with Oxylabs:

• Understanding your data needs: We work closely to understand your business nature and daily operations, defining your unique data requirements.
• Developing a customized solution: Our experts create a custom framework to extract public data using our in-house web scraping infrastructure.
• Delivering data sample: We provide a sample for your feedback on data quality and the entire delivery process.
• Continuous data delivery: We continuously collect public data and deliver custom datasets per the agreed frequency.

Unlock the power of data with Oxylabs' Company Datasets and supercharge your business insights today!

Global Power BI Consulting Service market size 2025 was XX Million. Power BI Consulting Service Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

Warning: Large file size (over 1GB). Each monthly data set is large (over 4 million rows), but can be viewed in standard software such as Microsoft WordPad (save by right-clicking on the file name and selecting 'Save Target As', or equivalent on Mac OSX). It is then possible to select the required rows of data and copy and paste the information into another software application, such as a spreadsheet. Alternatively, add-ons to existing software, such as the Microsoft PowerPivot add-on for Excel, to handle larger data sets, can be used. The Microsoft PowerPivot add-on for Excel is available from Microsoft http://office.microsoft.com/en-gb/excel/download-power-pivot-HA101959985.aspx Once PowerPivot has been installed, to load the large files, please follow the instructions below. Note that it may take at least 20 to 30 minutes to load one monthly file. 1. Start Excel as normal 2. Click on the PowerPivot tab 3. Click on the PowerPivot Window icon (top left) 4. In the PowerPivot Window, click on the "From Other Sources" icon 5. In the Table Import Wizard e.g. scroll to the bottom and select Text File 6. Browse to the file you want to open and choose the file extension you require e.g. CSV Once the data has been imported you can view it in a spreadsheet. What does the data cover? General practice prescribing data is a list of all medicines, dressings and appliances that are prescribed and dispensed each month. A record will only be produced when this has occurred and there is no record for a zero total. For each practice in England, the following information is presented at presentation level for each medicine, dressing and appliance, (by presentation name): - the total number of items prescribed and dispensed - the total net ingredient cost - the total actual cost - the total quantity The data covers NHS prescriptions written in England and dispensed in the community in the UK. Prescriptions written in England but dispensed outside England are included. The data includes prescriptions written by GPs and other non-medical prescribers (such as nurses and pharmacists) who are attached to GP practices. GP practices are identified only by their national code, so an additional data file - linked to the first by the practice code - provides further detail in relation to the practice. Presentations are identified only by their BNF code, so an additional data file - linked to the first by the BNF code - provides the chemical name for that presentation.

This data contains Q and A, Key Influencers, Map, Matrix, Dashboard

The Archive''s soil specimens are invaluable time capsules for assessing temporal changes in soil properties. Physical samples are a basic element for reference, study, and experimentation in research. There is an urgent need for better integrating these physical objects into the digital research data ecosystem, both in a global and in an interdisciplinary context to support scientific reuse. The CREA collection, located at the Experimental Farm of Fagna, Scarperia (FI), stores specimens and associated metadata. It covers all major agricultural and forestry soil landscapes in Italy for organic and mineral horizons. Parameters include water impedance, rooting depth, stoniness, Coarse fraction, particle size, pH, organic carbon, and total carbonates, World Reference Base classification. Part of collected samples was recently received and is temporarily stored unordered. With the present work, a tool was developed to expose both metadata, digital research data, displacement to support FAIR principles. The tool was developed by means of Ms Power BI. The original local Ms Access database was stored on the cloud and connected to the tool to allow automatic updates. Geographic and semantic queries are graphically implemented through drop-down menus and pie charts on administrative units- Soil districts- European Environments- Land use- WRB- and Project. The tool expose data collected by 13 different projects from 1986 to 2017. Contains 13,231 analyzed observations (pedological profiles, minipits, or augerings) for a total of 33,523 samples. Soil properties resulted in ranging for Clay 0.1-93.5 (29,9 average)- Sand 0.0-99.4 (17.9), pH (water) 3.9-9.7 (7.5) - Organic carbon 0.0-53.4 (7.8) - Total carbonates 0.0-91.4 (5.5) for the whole dataset. Textural composition of every Reference Soil Group (24 out of 32) is presented as Bar Histogram. A navigation panel allows to preview the site location and storing collocation. Although samples access is restricted, data and storing displacement are exposed to support use of the data and specimen''s reuse. The developed tool represents a first attempt to expose both metadata, soil data and filtering capabilities.

📌**Context**

The Healthcare Workforce Mental Health Dataset is designed to explore workplace mental health challenges in the healthcare industry, an environment known for high stress and burnout rates.

This dataset enables users to analyze key trends related to:

💠 Workplace Stressors: Examining the impact of heavy workloads, poor work environments, and emotional demands.

💠 Mental Health Outcomes: Understanding how stress and burnout influence job satisfaction, absenteeism, and turnover intention.

💠 Educational & Analytical Applications: A valuable resource for data analysts, students, and career changers looking to practice skills in data exploration and data visualization.

To help users gain deeper insights, this dataset is fully compatible with a Power BI Dashboard, available as part of a complete analytics bundle for enhanced visualization and reporting.

📌**Source**

This dataset was synthetically generated using the following methods:

💠 Python & Data Science Techniques: Probabilistic modeling to simulate realistic data distributions. Industry-informed variable relationships based on healthcare workforce studies.

💠 Guidance & Validation Using AI (ChatGPT): Assisted in refining dataset realism and logical mappings.

💠 Industry Research & Reports: Based on insights from WHO, CDC, OSHA, and academic studies on workplace stress and mental health in healthcare settings.

📌**Inspiration**

This dataset was inspired by ongoing discussions in healthcare regarding burnout, mental health, and staff retention. The goal is to bridge the gap between raw data and actionable insights by providing a structured, analyst-friendly dataset.

For those who want a ready-to-use reporting solution, a Power BI Dashboard Template is available, designed for interactive data exploration, workforce insights, and stress factor analysis.

📌**Important Note** This dataset is synthetic and intended for educational purposes only. It is not real-world employee data and should not be used for actual decision-making or policy implementation.

Socio-economic dashboard depicting Employment and Job Creation. Unemployment Rate (Province, Year, Qtr, Rate [percentage])Unemployment Rate by population group (Province, Year, Population Group, Rate [percentage])Unemployment Rate by gender (Province, Year, gender, Rate [percentage])Youth Unemployment Rate (Province, Year, Age cohorts, Rate [percentage])% Employment in formal and informal sectors (Province, Year, Sectors incl Agriculture, Sectors excl Agriculture, Private Households (domestic work), Rate [percentage])Labour particpation Rate (Province, Year, labour particpation Rate [percentage])Publication Date13 March 2022LineageData is sourced from Stats SA Quarterly Labour Force Surveys. Data is transformed into a BI format and quality assured. Data is consumed by a dashboard created in Power BI. Six reports exist for this dashboard:Unemployment RateUnemployment Rate by population groupUnemployment Rate by genderYouth Unemployment Rate % Employment in formal and informal sectorsLabour particpation RateData SourceData from Stats SA; Labour force surveys and Quarterly Labour Force Surveys 2017 – 2021Dynamic dashboard reflecting the Outcome Indicator Release - Outcome Indicator: Unemployment rateUnemployment rate by population in WCUnemployment rate by gender in WCYouth unemployment ratePercentage of employed people working in the informal sector, including domestic work in WCLabour participation rate

Comprehensive dataset of 130 Power stations in Colombia as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 1,245 Power stations in Germany as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 434 Power stations in Thailand as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 236 Power stations in Netherlands as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 216 Power stations in Switzerland as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 305 Power stations in Finland as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 625 Power stations in Iran as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 765 Power stations in Spain as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 1,564 Power stations in Indonesia as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 0 Electricity boards in Germany as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.