This dataset is about books. It has 1 row and is filtered where the book is Pro Power BI Desktop : Free Interactive Data Analysis with Microsoft Power BI. It features 7 columns including author, publication date, language, and book publisher.

This Rio Grande and Pecos River Water Operations Dashboard was created using the Microsoft Power BI application and is currently available to the public. This dashboard was created to provide real time data of the Rio Grande and Pecos rivers and reservoirs for water operation managers to assist in monitoring and making decisions. Data includes 15-minute water flow data and reservoir elevation and storage data from the U.S. Geological Survey, Colorado Department of Water Resources, and U.S. Bureau of Reclamation. The water operations dashboard is in an easy to navigate format that allows the user to clearly view current river and reservoir data at a single website to help make operations, management, and planning decisions.

Power BI Consulting Service Market Outlook

The global Power BI Consulting Service market size was valued at approximately $1.2 billion in 2023 and is projected to reach around $4.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 16.3% during the forecast period. This substantial growth is driven by the increasing adoption of business intelligence and data analytics tools across numerous industries.

One of the primary growth factors for the Power BI Consulting Service market is the escalating demand for data-driven decision-making across various sectors. As organizations increasingly recognize the value of business intelligence tools in extracting actionable insights from raw data, the need for skilled consultants to implement and manage these tools has surged. Moreover, the proliferation of big data and the rising importance of data visualization techniques are further propelling market growth. Companies are looking to leverage Power BI's robust capabilities to transform complex data sets into intuitive and interactive dashboards, thereby enhancing their strategic decision-making processes.

Another significant driver for the market is the rapid digital transformation and the shift towards cloud-based solutions. With the advent of cloud computing, enterprises of all sizes are investing heavily in cloud infrastructure, which offers flexibility, scalability, and cost-effectiveness. Power BI, with its seamless integration with various cloud services and platforms, is becoming a go-to solution for businesses aiming to modernize their data strategies. Consequently, the demand for consultancy services to assist in the smooth adoption and integration of Power BI into existing IT ecosystems is on the rise.

The increasing trend of remote work and the need for real-time data access and collaboration have also contributed to market expansion. As businesses adapt to the new normal brought about by the COVID-19 pandemic, there is a growing requirement for tools that facilitate remote collaboration and instant data sharing. Power BI's capability to provide real-time analytics and its ease of use make it an attractive option for businesses looking to maintain productivity and efficiency in a distributed work environment. This has led to heightened demand for consulting services to ensure that organizations can effectively leverage Power BI to meet their dynamic needs.

Regionally, North America is expected to hold a dominant position in the Power BI Consulting Service market, driven by the presence of numerous technology giants and high adoption rates of advanced analytics tools. However, the Asia Pacific region is anticipated to witness the fastest growth, attributed to the burgeoning IT sector and increasing digital initiatives by governments and businesses. European markets, with their focus on regulatory compliance and data protection, also present significant opportunities for growth in the Power BI consulting domain.

In the realm of business intelligence, Win-Loss Analysis Service is gaining traction as a crucial tool for organizations striving to understand their competitive positioning. This service involves a detailed examination of past business deals, identifying factors that contributed to wins and losses. By leveraging insights from Win-Loss Analysis, companies can refine their strategies, enhance customer engagement, and improve their overall sales effectiveness. The integration of such analysis with Power BI enables businesses to visualize patterns and trends, offering a comprehensive view of market dynamics. As organizations seek to optimize their decision-making processes, the demand for Win-Loss Analysis Service is expected to rise, complementing the growth of Power BI consulting services.

Service Type Analysis

The Power BI Consulting Service market can be segmented by service type into Implementation, Training, Support, and Maintenance. Among these, the implementation segment is expected to hold the largest market share during the forecast period. The increasing complexity of data environments and the need for customized solutions are driving the demand for implementation services. Organizations often require expert assistance to configure and deploy Power BI according to their specific requirements, ensuring that the tool integrates seamlessly with existing systems and processes.

Training services are also gaining prominence as businesses strive to empower thei

Exploring Online Sales Data with Power BI !!

Another productive day diving into online sales dataset! Here’s a roundup of the insights I uncovered today:

Revenue by Category: Analyzed revenue distribution across different product categories to identify high-performing sectors.

Revenue by Sub-Category: Drilled down into sub-categories for a more granular view of revenue streams.

Revenue by Payment Mode: Examined revenue patterns based on payment methods to understand customer preferences.

Revenue by State: Mapped out revenue by state to pinpoint geographical strengths and opportunities.

Profit by Category: Evaluated profitability across product categories to assess which categories yield the highest profit margins.

Profit by Sub-Category: Explored profit levels at a sub-category level to identify the most profitable segments.

Profit by Payment Mode: Analyzed profit distribution across different payment methods.

Top 5 States by Revenue and Profit: Highlighted the top 5 states driving the most revenue and profit, offering insights into regional performance.

Sales Map by State: Visualized sales data on a map to provide a geographical perspective on sales distribution.

Total Quantity, Revenue, and Profit: Aggregated data to give an overview of total quantities sold, overall revenue, and total profit.

Filter by Category: Added a filter functionality to focus on specific categories and refine data analysis.

The Business Intelligence (BI) analysis tools market is experiencing robust growth, driven by the increasing need for data-driven decision-making across diverse sectors. The market, estimated at $50 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $120 billion by 2033. This expansion is fueled by several key factors. Firstly, the proliferation of big data and the need for efficient analysis to extract actionable insights is paramount for businesses of all sizes. Secondly, the rising adoption of cloud-based BI solutions offers scalability, cost-effectiveness, and enhanced accessibility, contributing significantly to market growth. Thirdly, advancements in artificial intelligence (AI) and machine learning (ML) are integrating seamlessly into BI tools, enabling more sophisticated predictive analytics and automated reporting. The enterprise segment currently dominates the market, followed by the banking and government sectors, with increasing adoption across other industries. Popular BI tools like Tableau, Power BI, QlikView, and others cater to diverse needs, from self-service reporting to complex enterprise-wide analytics. However, challenges remain, including data security concerns, the complexity of implementation, and the need for skilled professionals to effectively utilize these powerful tools. Despite these challenges, the future of the BI analysis tools market appears bright. The continued digital transformation across industries, coupled with the increasing availability of affordable and user-friendly tools, will propel further growth. The market will likely witness increased competition, innovation in areas like embedded analytics and augmented analytics, and further geographical expansion, particularly in developing economies in Asia Pacific and Africa. The trend towards personalized dashboards and mobile-accessible BI will also shape the market landscape in the coming years. The shift towards cloud-based solutions and the integration of AI will continue to be significant drivers of this growth, ensuring that BI analysis tools remain a crucial element for businesses navigating the complexities of the data-driven economy.

This project focuses on data mapping, integration, and analysis to support the development and enhancement of six UNCDF operational applications: OrgTraveler, Comms Central, Internal Support Hub, Partnership 360, SmartHR, and TimeTrack. These apps streamline workflows for travel claims, internal support, partnership management, and time tracking within UNCDF.Key Features and Tools:Data Mapping for Salesforce CRM Migration: Structured and mapped data flows to ensure compatibility and seamless migration to Salesforce CRM.Python for Data Cleaning and Transformation: Utilized pandas, numpy, and APIs to clean, preprocess, and transform raw datasets into standardized formats.Power BI Dashboards: Designed interactive dashboards to visualize workflows and monitor performance metrics for decision-making.Collaboration Across Platforms: Integrated Google Collab for code collaboration and Microsoft Excel for data validation and analysis.

Dataset

This dataset was created by Aasim Parwez

Contents

From 2016 to 2018, we surveyed the world’s largest natural history museum collections to begin mapping this globally distributed scientific infrastructure. The resulting dataset includes 73 institutions across the globe. It has:

• Basic institution data for the 73 contributing institutions, including estimated total collection sizes, geographic locations (to the city) and latitude/longitude, and Research Organization Registry (ROR) identifiers where available.

• Resourcing information, covering the numbers of research, collections and volunteer staff in each institution.

• Indicators of the presence and size of collections within each institution broken down into a grid of 19 collection disciplines and 16 geographic regions.

• Measures of the depth and breadth of individual researcher experience across the same disciplines and geographic regions.

This dataset contains the data (raw and processed) collected for the survey, and specifications for the schema used to store the data. It includes:

1. A diagram of the MySQL database schema.
2. A SQL dump of the MySQL database schema, excluding the data.
3. A SQL dump of the MySQL database schema with all data. This may be imported into an instance of MySQL Server to create a complete reconstruction of the database.
4. Raw data from each database table in CSV format.
5. A set of more human-readable views of the data in CSV format. These correspond to the database tables, but foreign keys are substituted for values from the linked tables to make the data easier to read and analyse.
6. A text file containing the definitions of the size categories used in the collection_unit table.

The global collections data may also be accessed at https://rebrand.ly/global-collections. This is a preliminary dashboard, constructed and published using Microsoft Power BI, that enables the exploration of the data through a set of visualisations and filters. The dashboard consists of three pages:

Institutional profile: Enables the selection of a specific institution and provides summary information on the institution and its location, staffing, total collection size, collection breakdown and researcher expertise.

Overall heatmap: Supports an interactive exploration of the global picture, including a heatmap of collection distribution across the discipline and geographic categories, and visualisations that demonstrate the relative breadth of collections across institutions and correlations between collection size and breadth. Various filters allow the focus to be refined to specific regions and collection sizes.

Browse: Provides some alternative methods of filtering and visualising the global dataset to look at patterns in the distribution and size of different types of collections across the global view.

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.

Diabetes Analytics Dashboard – Power BI 🩺📊 This practice dashboard is built for Data Analytics, Data Visualization, and Data Science learning. It provides meaningful insights into diabetes risk factors using interactive visuals and advanced analytics.

🔹 Key Metrics – Total patients, BMI, glucose, blood pressure, and insulin levels. 🔹 Diabetes Risk Segmentation – Categorized into High, Medium, and Low risk groups. 🔹 Trends & Distribution – Glucose vs. Age, BMI categories, and Blood Pressure analysis. 🔹 Correlation Analysis – Exploring the relationships between glucose, BMI, and diabetes risk. 🔹 Gauge & Pie Charts – Visualizing risk percentage, BMI distribution, and glucose levels. 🔹 Interactive Filters & Drilldowns – Allowing deeper exploration of specific patient groups. 🔹 Predictive Insights – Identifying potential risk patterns through visual analytics.

This project helps in understanding data-driven healthcare insights using Power BI. Thanks to Kaggle for the dataset!

Introduction

Power BI Statistics: By 2024, Microsoft Power BI solidified an exalted rank among BI platforms, offering organisations an exquisite toolset for data visualisation, analysis, and decision-making. With its highly intuitive UI and integration options, Power BI has truly become the big gun in any organisation seeking to leverage the power of data-driven insight.

This article tries to draw a picture of Power BI statistics in 2024, describing its market share, Market size, etc.

The Power BI consulting services market is experiencing robust growth, driven by the increasing adoption of cloud-based business intelligence (BI) solutions and the rising demand for data-driven decision-making across various industries. The market's expansion is fueled by several key factors: the need for organizations to extract actionable insights from their vast data repositories, the user-friendliness and versatility of Power BI, and the growing availability of skilled consultants specializing in Power BI implementation and optimization. While the exact market size for 2025 is unavailable, a reasonable estimate, considering the typical growth trajectory of similar technology consulting markets and the documented CAGR (let's assume a conservative CAGR of 15% based on industry averages), would place the market value in the range of $3 billion to $4 billion. This growth is expected to continue throughout the forecast period (2025-2033), propelled by the ongoing digital transformation initiatives undertaken by businesses globally. The market is segmented by service type (online and offline) and application (large enterprises and SMEs), with large enterprises currently dominating the market share due to their greater resources and complex data needs. However, the SME segment shows significant potential for future growth as they increasingly recognize the value of data-driven insights and adopt cost-effective BI solutions. Geographical regions like North America and Europe are currently leading the market, but Asia-Pacific presents a significant growth opportunity in the coming years due to its rapidly expanding digital economy and increasing adoption of cloud technologies. Market restraints include the shortage of skilled Power BI consultants, the complexity of integrating Power BI with existing systems, and the initial investment costs associated with implementation. However, these challenges are being addressed by increased training initiatives, the development of streamlined integration tools, and the emergence of affordable cloud-based Power BI solutions. The competitive landscape is characterized by a mix of large multinational consulting firms and specialized Power BI consulting boutiques. The success of individual firms depends on their ability to offer specialized expertise, effective implementation strategies, and strong client relationships. The market is poised for continued strong growth, with the potential for even higher CAGRs in the years to come as more organizations adopt Power BI to improve their business outcomes.

What is IPGOD?\r

The Intellectual Property Government Open Data (IPGOD) includes over 100 years of registry data on all intellectual property (IP) rights administered by IP Australia. It also has derived information about the applicants who filed these IP rights, to allow for research and analysis at the regional, business and individual level. This is the 2019 release of IPGOD.\r \r \r

How do I use IPGOD?\r

IPGOD is large, with millions of data points across up to 40 tables, making them too large to open with Microsoft Excel. Furthermore, analysis often requires information from separate tables which would need specialised software for merging. We recommend that advanced users interact with the IPGOD data using the right tools with enough memory and compute power. This includes a wide range of programming and statistical software such as Tableau, Power BI, Stata, SAS, R, Python, and Scalar.\r \r \r

IP Data Platform\r

IP Australia is also providing free trials to a cloud-based analytics platform with the capabilities to enable working with large intellectual property datasets, such as the IPGOD, through the web browser, without any installation of software. IP Data Platform\r \r

References\r

\r The following pages can help you gain the understanding of the intellectual property administration and processes in Australia to help your analysis on the dataset.\r \r * Patents\r * Trade Marks\r * Designs\r * Plant Breeder’s Rights\r \r \r

Updates\r

\r

Tables and columns\r

\r Due to the changes in our systems, some tables have been affected.\r \r * We have added IPGOD 225 and IPGOD 325 to the dataset!\r * The IPGOD 206 table is not available this year.\r * Many tables have been re-built, and as a result may have different columns or different possible values. Please check the data dictionary for each table before use.\r \r

Data quality improvements\r

\r Data quality has been improved across all tables.\r \r * Null values are simply empty rather than '31/12/9999'.\r * All date columns are now in ISO format 'yyyy-mm-dd'.\r * All indicator columns have been converted to Boolean data type (True/False) rather than Yes/No, Y/N, or 1/0.\r * All tables are encoded in UTF-8.\r * All tables use the backslash \ as the escape character.\r * The applicant name cleaning and matching algorithms have been updated. We believe that this year's method improves the accuracy of the matches. Please note that the "ipa_id" generated in IPGOD 2019 will not match with those in previous releases of IPGOD.

Section and Beat Outline for Power BI maps

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

This Power BI dashboard shows the COVID-19 vaccination rate by key demographics including age groups, race and ethnicity, and sex for Tempe zip codes.Data Source: Maricopa County GIS Open Data weekly count of COVID-19 vaccinations. The data were reformatted from the source data to accommodate dashboard configuration. The Maricopa County Department of Public Health (MCDPH) releases the COVID-19 vaccination data for each zip code and city in Maricopa County at ~12:00 PM weekly on Wednesdays via the Maricopa County GIS Open Data website (https://data-maricopa.opendata.arcgis.com/). More information about the data is available on the Maricopa County COVID-19 Vaccine Data page (https://www.maricopa.gov/5671/Public-Vaccine-Data#dashboard). The dashboard’s values are refreshed at 3:00 PM weekly on Wednesdays. The most recent date included on the dashboard is available by hovering over the last point on the right-hand side of each chart. Please note that the times when the Maricopa County Department of Public Health (MCDPH) releases weekly data for COVID-19 vaccines may vary. If data are not released by the time of the scheduled dashboard refresh, the values may appear on the dashboard with the next data release, which may be one or more days after the last scheduled release.Dates: Updated data shows publishing dates which represents values from the previous calendar week (Sunday through Saturday). For more details on data reporting, please see the Maricopa County COVID-19 data reporting notes at https://www.maricopa.gov/5460/Coronavirus-Disease-2019.

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.

Burundi BI: Renewable Electricity Output: % of Total Electricity Output data was reported at 82.709 % in 2015. This records an increase from the previous number of 80.719 % for 2014. Burundi BI: Renewable Electricity Output: % of Total Electricity Output data is updated yearly, averaging 98.099 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 98.529 % in 1991 and a record low of 80.719 % in 2014. Burundi BI: Renewable Electricity Output: % of Total Electricity Output data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Burundi – Table BI.World Bank.WDI: Environmental: Energy Production and Consumption. Renewable electricity is the share of electrity generated by renewable power plants in total electricity generated by all types of plants.;IEA Statistics © OECD/IEA 2018 (https://www.iea.org/data-and-statistics), subject to https://www.iea.org/terms/;Weighted average;Restricted use: Please contact the International Energy Agency for third-party use of these data.

The Business Analytics Tools market is experiencing robust growth, driven by the increasing need for data-driven decision-making across diverse industries. The market, estimated at $50 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $150 billion by 2033. This expansion is fueled by several key factors. Firstly, the proliferation of big data and the need for efficient tools to analyze this data are creating significant demand. Secondly, the rising adoption of cloud-based solutions is contributing to accessibility and scalability, making these tools more affordable and user-friendly for businesses of all sizes. Finally, the growing emphasis on data security and compliance is pushing organizations to adopt sophisticated analytics tools that offer robust security features. Leading players like QlikView, Power BI, Tableau, and others are actively innovating and expanding their offerings to cater to this growing market. The market is segmented based on deployment (cloud, on-premise), industry (BFSI, healthcare, retail), and functionality (predictive analytics, descriptive analytics). Competition is fierce, with established players constantly innovating and newer entrants striving to carve a niche for themselves. Despite the positive outlook, several challenges persist. The complexity of implementing and integrating these tools can hinder adoption, particularly for smaller businesses with limited technical expertise. Data integration challenges and the need for skilled professionals to manage and interpret the insights generated also pose significant barriers. Furthermore, concerns surrounding data privacy and security remain paramount, requiring robust solutions and adherence to stringent regulations. Despite these restraints, the long-term growth prospects remain strong, fueled by the ever-increasing importance of data analytics in shaping business strategies and achieving competitive advantage. The market is expected to witness further consolidation as major players acquire smaller companies to enhance their product portfolios and expand their market reach.

The ckanext-power-bi extension for CKAN integrates Power BI reports into CKAN resources. It introduces a new "Power BI" resource view, allowing users to embed and view Power BI reports directly within CKAN. The extension is designed to generate embed tokens with "View" permissions only, restricting interaction to viewing existing report bookmarks without edit capabilities. Key Features: Power BI Report Embedding: Enables embedding Power BI reports into CKAN resources, providing an interactive data visualization experience for CKAN users. View-Only Permissions: Generates embed tokens with "View" permissions, ensuring users can only view and interact with pre-existing report bookmarks and not modify the reports themselves. This means features such as editing are disabled and the experience is limited to viewing. Workspace ID Configuration: Requires the Power BI Workspace ID (Group ID) to correctly connect and display the desired reports. Optional Organization Name Configuration: Allows specifying the Azure organization (tenant) name, intended for possible future Power BI API enhancements (currently unused). i18n Support: Supports Power BI's Multiple-Language Reports feature, allowing the appropriate language to be displayed based on the user's CKAN locale. Provides configurations to facilitate the use of alternate i18n methods if internal translation is needed. MSI Authentication: Leverages ManagedIdentityCredential (MSI) to authenticate with Azure, simplifying authentication in Azure environments using system-assigned managed identities. Technical Integration: The extension integrates into CKAN by adding a new resource view type. It requires configuration settings in CKAN's config file (.ini) to specify the Power BI Workspace ID and optionally the organization name, as well as enabling the plugin in the ckan.plugins setting. It utilizes the Azure Identity library to handle authentication. Benefits & Impact: By integrating Power BI reports directly into CKAN, this extension enhances data accessibility and usability. Users can view and interact with data visualizations without leaving the CKAN environment, fostering a more seamless data exploration experience.