This dataset contains the essential files for conducting a dynamic stock market analysis using Power BI. The data is sourced from Yahoo Finance and includes historical stock prices, which can be dynamically updated by adding new stock codes to the provided Excel sheet.

Files Included: Power BI Report (.pbix): The interactive Power BI report that includes various visualizations such as Candle Charts, Line Charts for Support and Resistance, and Technical Indicators like SMA, EMA, Bollinger Bands, and RSI. The report is designed to provide a comprehensive analysis of stock performance over time.

Stock Data Excel Sheet (.xlsx): This Excel sheet is connected to the Power BI report and allows for dynamic data loading. By adding new stock codes to this sheet, the Power BI report automatically refreshes to include the new data, enabling continuous updates without manual intervention.

Overview and Chart Pages Snapshots for better understanding about the Report.

Key Features: Dynamic Data Loading: Easily update the dataset by adding new stock codes to the Excel sheet. The Power BI report will automatically pull the corresponding data from Yahoo Finance. Comprehensive Visualizations: Analyze stock trends using Candle Charts, identify key price levels with Support and Resistance lines, and explore market behavior through various technical indicators. Interactive Analysis: The Power BI report includes slicers and navigation buttons to switch between different time periods and visualizations, providing a tailored analysis experience. Use Cases: Ideal for financial analysts, traders, or anyone interested in conducting a detailed stock market analysis. Can be used to monitor the performance of individual stocks or compare trends across multiple stocks over time. Tags: Stock Market Power BI Financial Analysis Yahoo Finance Data Visualization

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.

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.

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.

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

What is IPGOD? 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 …Show full descriptionWhat is IPGOD? 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. How do I use IPGOD? 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. IP Data Platform 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 References 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. Patents Trade Marks Designs Plant Breeder’s Rights Updates Tables and columns Due to the changes in our systems, some tables have been affected. We have added IPGOD 225 and IPGOD 325 to the dataset! The IPGOD 206 table is not available this year. 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. Data quality improvements Data quality has been improved across all tables. Null values are simply empty rather than '31/12/9999'. All date columns are now in ISO format 'yyyy-mm-dd'. All indicator columns have been converted to Boolean data type (True/False) rather than Yes/No, Y/N, or 1/0. All tables are encoded in UTF-8. All tables use the backslash \ as the escape character. 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.

This Power BI dashboard provides an in-depth analysis of Nike's US sales performance for 2020-21. It includes key insights on revenue trends, top-selling products, regional performance, customer segmentation, and seasonal variations. The interactive visualizations help identify growth opportunities and areas for improvement. Ideal for business analysts, marketers, and data enthusiasts looking to explore Nike’s sales data effectively.

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.

About Dataset

Spotify Dashboard in Power BI:

The goal of this Power BI Dashboard is to analyze Spotify data to provide insights into track performance, artist popularity, and playlist or chart trends, enabling stakeholders to make data-driven decisions in the music industry.

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.

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.

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.

🌍 Europe B2B Company Dataset | 30M+ Verified Records | Firmographics & API Access Power your sales, marketing, and investment strategies with the most comprehensive global B2B company data—verified, AI-driven, and updated bi-weekly.

The Forager.ai Global Company Dataset delivers 30M+ high-quality firmographic records, covering public and private companies worldwide. Leveraging AI-powered validation and bi-weekly updates, our dataset ensures accuracy, freshness, and depth—making it ideal for sales intelligence, market analysis, and CRM enrichment.

📊 Key Features & Coverage ✅ 30M+ Company Records – The largest, most reliable B2B firmographic dataset available. ✅ Bi-Weekly Updates – Stay ahead with refreshed data every two weeks. ✅ AI-Driven Accuracy – Sophisticated algorithms verify and enrich every record. ✅ Global Coverage – Companies across North America, Europe, APAC, and emerging markets.

📋 Core Data Fields: ✔ Company Name, LinkedIn URL, & Domain ✔ Industries ✔ Job postings, Revenue, Employee Size, Funding Status ✔ Location (HQ + Regional Offices) ✔ Tech Stack & Firmographic Signals ✔ LinkedIn Profile details

🎯 Top Use Cases 🔹 Sales & Lead Generation

Build targeted prospect lists using firmographics (size, industry, revenue).

Enhance lead scoring with technographic insights.

🔹 Market & Competitive Intelligence

Track company growth, expansions, and trends.

Benchmark competitors using real-time private company data.

🔹 Venture Capital & Private Equity

Discover investment opportunities with granular sector-level insights.

Monitor portfolio companies and industry shifts.

🔹 ABM & Marketing Automation

Enrich CRM data for hyper-targeted campaigns.

Power intent data and predictive analytics.

⚡ Delivery & Integration Choose the best method for your workflow:

REST API – Real-time access for developers.

Flat Files (CSV, JSON) – Delivered via S3, Wasabi, Snowflake.

Custom Solutions – Scalable enterprise integrations.

🔒 Data Quality & Compliance 95%+ Field Completeness – Minimize gaps in your analysis.

Ethically Sourced – Compliant with GDPR, CCPA, and global privacy laws.

Transparent Licensing – Clear usage terms for peace of mind.

🚀 Why Forager.ai? ✔ AI-Powered Accuracy – Better data, fewer false leads. ✔ Enterprise-Grade Freshness – Bi-weekly updates keep insights relevant. ✔ Flexible Access – API, bulk files, or custom database solutions. ✔ Dedicated Support – Onboarding and SLA-backed assistance.

Tags: B2B Company Data |LinkedIn Job Postings | Firmographics | Global Business Intelligence | Sales Leads | VC & PE Data | Technographics | CRM Enrichment | API Access | AI-Validated Data

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.

The Business Intelligence (BI) market size was valued at USD 29.42 USD billion in 2023 and is projected to reach USD 53.78 USD billion by 2032, exhibiting a CAGR of 9.0 % during the forecast period. The increasing adoption of cloud-based BI solutions and the growing demand for data-driven insights to improve decision-making are the primary factors driving the market growth. Business intelligence (BI) is the software that feeds on the business data and then presents it in such user-friendly views as reports, dashboard, charts, and graphs. The businesses study the data to obtain actionable insights and inform themselves in decision-making. Business intelligence tools allow users to work with different types of data - historical and current, third-party and in-house, as well as semi-structured data and unstructured data like social media. Through this, users can discover valuable insights as to how the business is doing. Business intelligence is a general name that embraces data mining, process analysis, performance benchmarking, and descriptive analytics. BI not only processes all the business data but also offers reports, performance indicators, and trends that are easily understood by management hence helping to make decisions. Recent developments include: In June 2023, ThoughtSpot, an AI-powered analytics firm, acquired Mode Analytics, a business intelligence company, to expand ThoughtSpot’s presence in India and double the customer base., In May 2023, Qlik acquired Talend for expanding the company’s capabilities for modern enterprises to transform, trust, access, analyze, and take action with data., In January 2023, Microsoft announced Power BI in Microsoft Teams for improved experiences. The announcements come with three new features, rich broadcast cards for Chat in Microsoft Teams, an update for legacy Power BI tabs for Channels 2.0, and listening and learning from experiences and requirements. , In December 2022, Tableau launched its upgraded Tableau 2022.4 for business users and analysts to explore insights. It automates developing, analyzing, and communicating insights with data stories such as Data Change Radar, Data guide, and Explain the Viz., In November 2022, Qlik launched a new cloud-based data integration platform. The advanced platform as a service combines catalog capabilities and data preparation in a single place. The new integration enables real-time data analysis for organizations. The advanced platform includes a range of services that form a data fabric unification of services to connect data sources that allow an organization to have an integrated view of its data., In October 2022, Mode Analytics announced its partnership with Dbt Labs to reveal the launch of the new Semantic Layer of Dbt. Mode Analytics deep integration and Dbt Semantic Layer enables governed, consistent metrics instantaneously accessible for exploration without any code. Thus, it allows organizations to define and manage their key business metrics consistently., In October 2022, Oracle enhanced inclusive and incorporated data and analytics facilities to empower corporate users. With the new abilities in Oracle Fusion Analytics over ERP, CX, HCM, and SCM analytics, corporate users can now use dashboards, KPIs, and reports to evaluate performance over strategic goals.. Key drivers for this market are: Increasing Usage of Integrated BI Systems to Augment the Market Growth . Potential restraints include: Difficulties in Abstracting Data from Third-party Systems due to Poor Data Quality Hinder the Market Growth. Notable trends are: Growing Popularity of Continuous Intelligence to Propel Market Growth.

This dataset is about book subjects. It has 3 rows and is filtered where the books is Beginning big data with Power BI and Excel 2013 : big data processing and analysis using Power BI in Excel 2013. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This project focuses on analyzing the S&P 500 companies using data analysis tools like Python (Pandas), SQL, and Power BI. The goal is to extract insights related to sectors, industries, locations, and more, and visualize them using dashboards.

Included Files:

sp500_cleaned.csv – Cleaned dataset used for analysis

sp500_analysis.ipynb – Jupyter Notebook (Python + SQL code)

dashboard_screenshot.png – Screenshot of Power BI dashboard

README.md – Summary of the project and key takeaways

This project demonstrates practical data cleaning, querying, and visualization skills.

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 the need for organizations, both large enterprises and SMEs, to effectively analyze their vast datasets and gain valuable insights for improved operational efficiency, strategic planning, and competitive advantage. This demand is further amplified by the user-friendly nature of Power BI, its robust analytical capabilities, and its seamless integration with other Microsoft products. While precise figures for market size and CAGR are not provided, a reasonable estimate, considering the growth trajectory of the BI market and the popularity of Power BI, would place the 2025 market size at approximately $2.5 billion, growing at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This implies a market size exceeding $8 billion by 2033. This growth is not uniform across all segments; the online service segment is predicted to outpace the offline segment due to the convenience and scalability it offers. Similarly, large enterprises currently represent a larger market share than SMEs, but the SME segment is expected to experience faster growth as more smaller businesses adopt data-driven strategies. Geographic distribution shows significant market presence across North America and Europe, with strong growth potential in the Asia-Pacific region. Factors that could restrain market growth include a shortage of skilled Power BI consultants, the complexity of data integration in some organizations, and the initial investment costs associated with implementation. However, these constraints are likely to be offset by the significant return on investment that Power BI offers through improved decision-making and enhanced operational efficiency. The increasing availability of training resources and the emergence of specialized consulting firms are also expected to mitigate the skilled consultant shortage over time.

About Datasets: - Domain : Finance - Project: Bank loan of customers - Datasets: Finance_1.xlsx & Finance_2.xlsx - Dataset Type: Excel Data - Dataset Size: Each Excel file has 39k+ records

KPI's: 1. Year wise loan amount Stats 2. Grade and sub grade wise revol_bal 3. Total Payment for Verified Status Vs Total Payment for Non Verified Status 4. State wise loan status 5. Month wise loan status 6. Get more insights based on your understanding of the data

Process: 1. Understanding the problem 2. Data Collection 3. Data Cleaning 4. Exploring and analyzing the data 5. Interpreting the results

This data contains stacked column chart, Donut chart, Stacked area chart, pie chart, matrix, slicer, treemap, clustered column chart, Map, Dashboard, Page Navigator, card, text box.

This hosted feature layer has been developed in-house by the VDOT CO TED Highway Safety section for crash analysis purpose based on updates from the Power BI Crash Tool. The Crash Data Dictionary can be found here. The main source of the data is owned and maintained by DMV. In providing this web map, we assume no responsibility for the accuracy and completeness of the data. In the process of recording and compiling the data, some deletions and/or omissions of data may occur and VDOT is not responsible for any such occurrences.

The main source of the data is owned and maintained by DMV. In providing this tool, VDOT assumes no responsibility for the accuracy and completeness of the data. In the process of recording and compiling the data, some deletions and/or omissions of data may occur and VDOT is not responsible for any such occurrences. The most recent data contained in this report is preliminary and subject to change. Please be advised that, under Title 23 United State Code – Section 409, this crash information cannot be used in discovery or as evidence in a Federal or State court proceeding or considered for other purposes in any action for damages against VDOT or the State of Virginia arising from any occurrence at the location identified.

All users shall comply with and be subject to all applicable laws and regulations, whether federal or state, in connection with any of the receipt and use of DMV data including, but not limited to, (1) the Federal Drivers Privacy Protection Act (18 U.S.C. § 2721 et seq.), (2) the Government Data Collection and Dissemination Practices Act (Va. Code § 2.2-3800 et seq.), (3) the Virginia Computer Crimes Act (Va. Code § 18.2-152.1 et seq.), (4) the provisions of Va. Code §§ 46.2-208 and 58.1-3, and (5) any successor rules, regulations, or guidelines adopted by DMV with regard to disclosure or dissemination of any information obtained from DMV records or files.