The reference for the dataset and the dashboard was Youtube Channel codebasics. I have used a fictitious company called Atlix where the Sales Director want the sales data to be in a proper format which can help in decision making.

We have a total of 5 tables namely customers, products, markets, date & transactions. The data is exported from Mysql to Tableau.

In tableau , inner joins were used.

In the transactions table, we notice that sum sales amount figures are either negative or zero while the sales qty is either 1 or more. This cannot be right. Therefore, we filter the sales amount table in Tableau by having the least sales amount as minimum 1.

When currency column from transactions table was grouped in MySql, we could see ‘USD’ and ‘INR’ showing up. We cannot have a sales data showing two currencies. This was rectified by converting the USD sales amount into INR by taking the latest exchange rate at Rs.81.

We make the above change in tableau by creating a new calculated field called ‘Normalised Sales Amount’. If [Sales Amount] == ‘USD’ then [Sales Amount] * 81 else [Sales Amount] End.

Conclusion: The dashboard prepared is an interactive dashboard with filters. For eg. By Clicking on Mumbai under “Sales by Markets” we will see the results change in the other charts as well as they Will now show the results pertaining only to Mumbai. This can be done by year , month, customers , products etc. Parameter with filter has also been created for top customers and top products. This produces a slider which can be used to view the top 10 customers and products and slide it accordingly.

Following information can be passed on to the sales team or director.

Total Sales: from Jun’17 to Feb’20 has been INR 12.83 million. There is a drop of 57% in the sales revenue from 2018 to 2019. The year 2020 has not been considered as it only account for 2 months data. Markets: Mumbai which is the top most performing market and accounts for 51% of the total sales market has seen a drop in sales of almost 64% from 2018 to 2019. Top Customers: Path was on 2nd position in terms of sales in the year 2018. It accounted for 19% of the total sales after Electricalslytical which accounted for 21% of the total sales. But in year 2019, both Electricalslytical and Path were the 2nd and 4th highest customers by sales. By targeting the specific markets and customers through new ideas such as promotions, discounts etc we can look to reverse the trend of decreasing sales.

The global data visualization market, valued at $9.84 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 10.95% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across various industries necessitates effective visualization tools for insightful analysis and decision-making. Furthermore, the rising adoption of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, driving market growth. Advances in artificial intelligence (AI) and machine learning (ML) are integrating seamlessly with data visualization platforms, enhancing automation and predictive capabilities, further stimulating market demand. The BFSI (Banking, Financial Services, and Insurance) sector, along with IT and Telecommunications, are major adopters, leveraging data visualization for risk management, fraud detection, customer relationship management, and network optimization. However, challenges remain, including the need for skilled professionals to effectively utilize these tools and concerns regarding data security and privacy. The market segmentation reveals a strong presence of executive management and marketing departments across organizations, highlighting the strategic importance of data visualization in business operations. The market's competitive landscape is characterized by established players like SAS Institute, IBM, Microsoft, and Salesforce (Tableau), along with emerging innovative companies. This competition fosters innovation and drives down costs, making data visualization solutions more accessible to a broader range of businesses and organizations. Regional variations in market penetration are expected, with North America and Europe currently holding significant shares, but Asia Pacific is poised for substantial growth, driven by rapid digitalization and technological advancements in the region. The on-premise deployment mode still holds a considerable market share, though the cloud/on-demand segment is experiencing faster growth due to its inherent advantages. The ongoing trend towards self-service business intelligence (BI) tools is empowering end-users to access and analyze data independently, increasing the overall market demand for user-friendly and intuitive data visualization platforms. Future growth will depend on continued technological advancements, expanding applications across diverse industries, and addressing the existing challenges related to data skills gaps and security concerns. This report provides a comprehensive analysis of the Data Visualization Market, projecting robust growth from $XX Billion in 2025 to $YY Billion by 2033. It covers the period from 2019 to 2033, with a focus on the forecast period 2025-2033 and a base year of 2025. This in-depth study examines key market segments, competitive landscapes, and emerging trends influencing this rapidly evolving industry. The report is designed for executives, investors, and market analysts seeking actionable insights into the future of data visualization. Recent developments include: September 2022: KPI 360, an AI-driven solution that uses real-time data monitoring and prediction to assist manufacturing organizations in seeing various operational data sources through a single, comprehensive industrial intelligence dashboard that sets up in hours, was recently unveiled by SymphonyAI Industrial., January 2022: The most recent version of the IVAAP platform for ubiquitous subsurface visualization and analytics applications was released by INT, a top supplier of data visualization software. IVAAP allows exploring, visualizing, and computing energy data by providing full OSDU Data Platform compatibility. With the new edition, IVAAP's map-based search, data discovery, and data selection are expanded to include 3D seismic volume intersection, 2D seismic overlays, reservoir, and base map widgets for cloud-based visualization of all forms of energy data.. Key drivers for this market are: Cloud Deployment of Data Visualization Solutions, Increasing Need for Quick Decision Making. Potential restraints include: Lack of Tech Savvy and Skilled Workforce/Inability. Notable trends are: Retail Segment to Witness Significant Growth.

Unlock the potential of data visualization with our in-depth analysis of the booming Tableau Services market. Discover key trends, growth drivers, and regional market share projections for 2025-2033, including insights into consulting, maintenance, and development services across enterprise segments. Learn more about leading companies and future opportunities.

📊 Sales & Customer Analytics – Tableau Dashboard (PDF & Interactive) 🔍 Overview This dataset includes a Tableau project analysing sales trends & customer insights with an interactive dashboard switch.

The dashboards provide actionable insights into: ✅ Sales performance & revenue trends 📈 ✅ Top-performing products & regions 🌍 ✅ Customer segmentation & behavior analysis 🛍️ ✅ Retention strategies & marketing impact 🎯

📂 Files Included 📄 Sales & Customer Analytics Dashboard (PDF Report) – A full summary of insights. 🎨 Tableau Workbook (.twbx) – The interactive dashboards (requires Tableau). 🖼️ Screenshots – Previews of the dashboards.

🔗 Explore the Interactive Dashboards on Tableau Public :

Sales Dashboard:[https://public.tableau.com/app/profile/egbe.grace/viz/SalesCustomerDashboardsDynamic_17385906491570/CustomerDashboard] Customer Dashboard: [https://public.tableau.com/app/profile/egbe.grace/viz/SalesCustomerDashboardsDynamic_17385906491570/CustomerDashboard]

📌 Key Insights from the Dashboards ✅ Revenue trends show peak sales periods & seasonal demand shifts. ✅ Top-selling products & regions help businesses optimize their strategies. ✅ Customer segmentation identifies high-value buyers for targeted marketing. ✅ Retention analysis provides insights into repeat customer behaviour.

💡 How This Can Help: This dataset and Tableau project can help businesses & analysts uncover key patterns in sales and customer behavior, allowing them to make data-driven decisions to improve growth and customer retention.

💬 Would love to hear your feedback! Let’s discuss the impact of sales analytics in business strategy.

📢 #DataAnalytics #Tableau #SalesAnalysis #CustomerInsights #BusinessIntelligence #DataVisualization

The data discovery market, projected at $XX million in 2025, is experiencing robust growth, fueled by a compound annual growth rate (CAGR) of 21%. This expansion is driven by several key factors. The increasing volume and complexity of data generated by businesses across diverse sectors necessitate efficient tools for data analysis and insights extraction. The rise of big data analytics and the growing adoption of cloud-based solutions are further propelling market growth. Businesses across industries, particularly Banking, Financial Services, and Insurance (BFSI), Telecommunications and IT, and Retail and E-commerce, are increasingly recognizing the value of data-driven decision-making, leading to higher adoption rates of data discovery platforms. The market is segmented by component (software and services), enterprise size (SMEs and large enterprises), and industry vertical, with each segment contributing uniquely to overall market dynamics. While the market faces challenges such as the need for skilled professionals and the complexity of integrating data from disparate sources, the overall trend suggests sustained growth, driven by the continuous rise in data generation and the expanding need for actionable insights. The competitive landscape is characterized by a mix of established players like Tableau, SAP, and Oracle, and emerging innovative companies. This competition fosters innovation and drives down costs, making data discovery solutions more accessible to a broader range of businesses. While North America currently holds a significant market share, regions like Asia Pacific are expected to witness rapid growth driven by increasing digitalization and adoption of advanced analytics. The forecast period (2025-2033) anticipates sustained growth, though the rate of expansion may gradually moderate as the market matures. The market's future trajectory will depend on factors such as technological advancements, regulatory changes, and the overall economic climate. Continued investment in research and development, coupled with strategic partnerships and acquisitions, will be key to success in this dynamic and rapidly evolving market. Recent developments include: August 2022: CoreLogic, a major global provider of analytics-driven and property data solutions, expanded its partnership with Google Cloud to assist in the introduction of its novel CoreLogic Discovery Platform. Discovery Platform, which is fully built on Google Cloud's safe and sustainable technology, offers a complete asset analytics platform and cloud-based data interchange for enterprises in a variety of industries., June 2022: Select Star established an official collaboration with dbt Labs. Dbt has been one of Select Star's most significant integrations, with over 15,000 models and 225,000 columns linked up to date. Select Star is intended to facilitate the data discovery required by companies in order to harness the potential of their data and generate effective outcomes. As a result, Select Star and Dbt Labs have a shared goal, to empower analytics engineers to convert information better and keep appropriate documentation so that business users and data analysts can trust their data., June 2022: TD SYNNEX's SNX Tech Data established a collaboration with Instructure INST, a Learning Management Systems ("LMS") company, to utilize advanced learning capabilities in India. TD SYNNEX earned a substantial advantage with this deal, in addition to developing its data, Internet of Things, and analytics products. By enabling end-to-end business analytics powered by self-service data discovery, corporate reporting, mobile apps, and embedded analytics, TD SYNNEX's partners were able to offer complete business analytics propelled by data-driven business culture.. Key drivers for this market are: Increasing Number of Multi-Structured Data Sources, Growing Importance for Data-Driven Decision-Making. Potential restraints include: Increasing Number of Multi-Structured Data Sources, Growing Importance for Data-Driven Decision-Making. Notable trends are: The Banking, Financial Services, and Insurance Sector Holds a Dominant Position.

****Dataset Overview – LinkedIn Survey of Data Professionals****

The dataset is derived from a LinkedIn-based survey targeting professionals in the data field, including Data Analysts, Data Scientists, Data Engineers, and others. It provides valuable insights into career trends, salary expectations, educational backgrounds, and tool preferences among respondents.

This dataset originates from Alex Freberg's Power BI tutorial project (credits and links provided in the video description). It serves as an excellent resource for beginners looking to build standalone visualization projects using Power BI or Tableau. The dataset allows users to showcase data storytelling, interactive dashboard design, and visualization skills effectively;

Skills which can be displayed;

•Data transformation using Power Query •Data cleaning using Power BI(unstandardized information,missing data,unnecessary and empty columns) •Usage of DAX formulas for Data Exploration

Key Columns in the Dataset:

Dataset contains a wide range of valuable information, some columns (such as "Email," "City," and "Referrer") are intentionally left blank or contain incomplete data, as they are either not essential for analysis or were anonymized to protect respondent privacy. These fields can typically be excluded during data cleaning and preprocessing stages without impacting the integrity of the insights drawn from the core survey questions.

Timestamp – When the response was recorded. Unique ID Email Date Taken (America/New_York) Time Taken (America/New_York) Browser OS City Country Referrer Time Spent Q1 - Which Title Best Fits your Current Role? Q2 - Did you switch careers into Data? Q2 - Did you switch careers into Data? Q3 - Current Yearly Salary (in USD) Q4 - What Industry do you work in? Q5 - Favorite Programming Language Q6 - How Happy are you in your Current Position with the following? (Salary) Q6 - How Happy are you in your Current Position with the following? (Coworkers) Q6 - How Happy are you in your Current Position with the following? (Management) Q6 - How Happy are you in your Current Position with the following? (Upward Mobility) Q6 - How Happy are you in your Current Position with the following? (Learning New Things) Q7 - How difficult was it for you to break into Data? Q8 - If you were to look for a new job today, what would be the most important thing to you? Q9 - Male/Female? Q10 - Current Age Q11 - Which Country do you live in? Q12 - Highest Level of Education Q13 - Ethnicity

Purpose of the Dataset:

To explore career dynamics and compensation trends in the data industry. To understand how skills, tools, education, and location correlate with salaries and satisfaction.

Credits: Power BI Portfolio Project by Alex The Analyst: https://www.youtube.com/watch?v=I0vQ_VLZTWg&t=6506s Alex's Github for Power BI tutorial: https://github.com/AlexTheAnalyst/PowerBI/blob/main/Power%20BI%20-%20Final%20Project.xlsx

Prelude

This dataset is a cleaned version of the Chicago Crime Dataset, which can be found here. All rights for the dataset go to the original owners. The purpose of this dataset is to display my skills in visualizations and creating dashboards. To be specific, I will attempt to create a dashboard that will allow users to see metrics for a specific crime within a given year using filters and metrics. Due to this, there will not be much of a focus on the analysis of the data, but there will be portions discussing the validity of the dataset, the steps I took to clean the data, and how I organized it. The cleaned datasets can be found below, the Query (which utilized BigQuery) can be found here and the Tableau dashboard can be found here.

About the Dataset

Important Facts

The dataset comes directly from the City of Chicago's website under the page "City Data Catalog." The data is gathered directly from the Chicago Police's CLEAR (Citizen Law Enforcement Analysis and Reporting) and is updated daily to present the information accurately. This means that a crime on a specific date may be changed to better display the case. The dataset represents crimes starting all the way from 2001 to seven days prior to today's date.

Reliability

Using the ROCCC method, we can see that: * The data has high reliability: The data covers the entirety of Chicago from a little over 2 decades. It covers all the wards within Chicago and even gives the street names. While we may not have an idea for how big the sample size is, I do believe that the dataset has high reliability since it geographically covers the entirety of Chicago. * The data has high originality: The dataset was gained directly from the Chicago Police Dept. using their database, so we can say this dataset is original. * The data is somewhat comprehensive: While we do have important information such as the types of crimes committed and their geographic location, I do not think this gives us proper insights as to why these crimes take place. We can pinpoint the location of the crime, but we are limited by the information we have. How hot was the day of the crime? Did the crime take place in a neighborhood with low-income? I believe that these key factors prevent us from getting proper insights as to why these crimes take place, so I would say that this dataset is subpar with how comprehensive it is. * The data is current: The dataset is updated frequently to display crimes that took place seven days prior to today's date and may even update past crimes as more information comes to light. Due to the frequent updates, I do believe the data is current. * The data is cited: As mentioned prior, the data is collected directly from the polices CLEAR system, so we can say that the data is cited.

Processing the Data

Cleaning the Dataset

The purpose of this step is to clean the dataset such that there are no outliers in the dashboard. To do this, we are going to do the following: * Check for any null values and determine whether we should remove them. * Update any values where there may be typos. * Check for outliers and determine if we should remove them.

The following steps will be explained in the code segments below. (I used BigQuery for this so the coding will follow BigQuery's syntax) ```

Examining the dataset

There are over 7.5 million rows of data

Putting a limit so it does not take a long time to run

SELECT * FROM portfolioproject-350601.ChicagoCrime.Crime LIMIT 1000;

Seeing which points are null

There are 85,000 null points so we can exclude them as it's not a significant amount since it is only ~1.3% of the dataset

Most of the null points are in the lat and long, which we will need later

Because we don't have the full address, we can't estimate the lat and long in SQL so we will have to delete the rows with Null Data

SELECT * FROM portfolioproject-350601.ChicagoCrime.Crime WHERE unique_key IS NULL OR case_number IS NULL OR date IS NULL OR primary_type IS NULL OR location_description IS NULL OR arrest IS NULL OR longitude IS NULL OR latitude IS NULL;

Deleting all null rows

DELETE FROM portfolioproject-350601.ChicagoCrime.Crime WHERE
unique_key IS NULL OR case_number IS NULL OR date IS NULL OR primary_type IS NULL OR location_description IS NULL OR arrest IS NULL OR longitude IS NULL OR latitude IS NULL;

Checking for any duplicates in the unique keys

None to be found

SELECT unique_key, COUNT(unique_key) FROM `portfolioproject-350601.ChicagoCrime....

The global visual data analysis tool market is experiencing robust growth, driven by the increasing need for businesses to extract actionable insights from ever-expanding datasets. The market, currently valued at approximately $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 18% from 2025 to 2033. This significant expansion is fueled by several key factors. The proliferation of big data, coupled with the rising adoption of cloud-based solutions and advanced analytics techniques, empowers organizations across various sectors – including banking, manufacturing, and government – to make data-driven decisions. Furthermore, the continuous innovation in visualization technologies, offering more intuitive and user-friendly interfaces, is broadening accessibility and accelerating market penetration. The growing demand for real-time data analysis and predictive modeling further contributes to the market's upward trajectory. Despite the significant growth potential, the market faces certain challenges. High implementation costs, particularly for on-premises solutions, and the need for specialized skills to effectively utilize these tools can act as restraints for smaller businesses. However, the emergence of affordable cloud-based alternatives and increased availability of training programs are gradually mitigating these barriers. The market segmentation reveals a clear preference towards cloud-based solutions due to their scalability, flexibility, and cost-effectiveness. The banking and finance sectors, followed by manufacturing and consultancy, represent the largest market segments. Key players like Tableau, Microsoft, and Salesforce are driving innovation and shaping market competition through continuous product enhancements and strategic acquisitions. The geographical landscape displays strong growth potential across North America and Europe, while Asia-Pacific is expected to emerge as a significant market in the coming years.

AbstractThe H1B is an employment-based visa category for temporary foreign workers in the United States. Every year, the US immigration department receives over 200,000 petitions and selects 85,000 applications through a random process and the U.S. employer must submit a petition for an H1B visa to the US immigration department. This is the most common visa status applied to international students once they complete college or higher education and begin working in a full-time position. The project provides essential information on job titles, preferred regions of settlement, foreign applicants and employers' trends for H1B visa application. According to locations, employers, job titles and salary range make up most of the H1B petitions, so different visualization utilizing tools will be used in order to analyze and interpreted in relation to the trends of the H1B visa to provide a recommendation to the applicant. This report is the base of the project for Visualization of Complex Data class at the George Washington University, some examples in this project has an analysis for the different relevant variables (Case Status, Employer Name, SOC name, Job Title, Prevailing Wage, Worksite, and Latitude and Longitude information) from Kaggle and Office of Foreign Labor Certification(OFLC) in order to see the H1B visa changes in the past several decades. Keywords: H1B visa, Data Analysis, Visualization of Complex Data, HTML, JavaScript, CSS, Tableau, D3.jsDatasetThe dataset contains 10 columns and covers a total of 3 million records spanning from 2011-2016. The relevant columns in the dataset include case status, employer name, SOC name, jobe title, full time position, prevailing wage, year, worksite, and latitude and longitude information.Link to dataset: https://www.kaggle.com/nsharan/h-1b-visaLink to dataset(FY2017): https://www.foreignlaborcert.doleta.gov/performancedata.cfmRunning the codeOpen Index.htmlData ProcessingDoing some data preprocessing to transform the raw data into an understandable format.Find and combine any other external datasets to enrich the analysis such as dataset of FY2017.To make appropriated Visualizations, variables should be Developed and compiled into visualization programs.Draw a geo map and scatter plot to compare the fastest growth in fixed value and in percentages.Extract some aspects and analyze the changes in employers’ preference as well as forecasts for the future trends.VisualizationsCombo chart: this chart shows the overall volume of receipts and approvals rate.Scatter plot: scatter plot shows the beneficiary country of birth.Geo map: this map shows All States of H1B petitions filed.Line chart: this chart shows top10 states of H1B petitions filed. Pie chart: this chart shows comparison of Education level and occupations for petitions FY2011 vs FY2017.Tree map: tree map shows overall top employers who submit the greatest number of applications.Side-by-side bar chart: this chart shows overall comparison of Data Scientist and Data Analyst.Highlight table: this table shows mean wage of a Data Scientist and Data Analyst with case status certified.Bubble chart: this chart shows top10 companies for Data Scientist and Data Analyst.Related ResearchThe H-1B Visa Debate, Explained - Harvard Business Reviewhttps://hbr.org/2017/05/the-h-1b-visa-debate-explainedForeign Labor Certification Data Centerhttps://www.foreignlaborcert.doleta.govKey facts about the U.S. H-1B visa programhttp://www.pewresearch.org/fact-tank/2017/04/27/key-facts-about-the-u-s-h-1b-visa-program/H1B visa News and Updates from The Economic Timeshttps://economictimes.indiatimes.com/topic/H1B-visa/newsH-1B visa - Wikipediahttps://en.wikipedia.org/wiki/H-1B_visaKey FindingsFrom the analysis, the government is cutting down the number of approvals for H1B on 2017.In the past decade, due to the nature of demand for high-skilled workers, visa holders have clustered in STEM fields and come mostly from countries in Asia such as China and India.Technical Jobs fill up the majority of Top 10 Jobs among foreign workers such as Computer Systems Analyst and Software Developers.The employers located in the metro areas thrive to find foreign workforce who can fill the technical position that they have in their organization.States like California, New York, Washington, New Jersey, Massachusetts, Illinois, and Texas are the prime location for foreign workers and provide many job opportunities. Top Companies such Infosys, Tata, IBM India that submit most H1B Visa Applications are companies based in India associated with software and IT services.Data Scientist position has experienced an exponential growth in terms of H1B visa applications and jobs are clustered in West region with the highest number.Visualization utilizing programsHTML, JavaScript, CSS, D3.js, Google API, Python, R, and Tableau

The data here include SFI research programmes from 2011 that were managed end-to-end in SFI’s Grants and Awards Management System. Programmes were gradually managed through the Grants and Awards Management System from 2011, and therefore awards made under programmes prior to 2011 were excluded as these data were not available. Furthermore, non-research funded programmes (e.g. education and public engagement grants) and programmes where SFI simply provided the funding to another organisation who solicit and process the applications, for example Wellcome, Royal Society etc., were also excluded.

The data include awards offered by SFI, irrespective of whether the award was accepted or declined by the applicant, as this best represents completion of the SFI peer review process. Where awards were transferred or underwent different ownership after their inception, data were based on the lead applicant’s self-declared gender at the time the award decision was made and currently reflects a binary categorisation of gender, e.g. male or female (with exclusions as described previously) between 2011 and 2021.

Learning Data Visualization Tools Market Outlook

According to our latest research, the global Learning Data Visualization Tools Market size reached USD 2.8 billion in 2024, demonstrating robust growth driven by the increasing demand for data literacy and analytics skills across various sectors. The market is expected to grow at a CAGR of 13.7% from 2025 to 2033, projecting a value of USD 8.8 billion by 2033. This surge is primarily attributed to the rapid digitization of education and corporate learning environments, the proliferation of big data, and the critical need for interactive, accessible analytical tools to foster effective data comprehension and decision-making.

One of the most significant growth factors for the Learning Data Visualization Tools Market is the widespread integration of data-driven decision-making processes within organizations and educational institutions. As businesses and academic settings increasingly rely on data to guide strategies, there is a parallel surge in the demand for professionals who possess strong data visualization skills. This has led to a marked increase in the adoption of user-friendly data visualization tools such as Tableau, Power BI, and Google Data Studio in both formal education and corporate training programs. The ability of these tools to simplify complex datasets into intuitive visual representations is a key driver, enabling learners to grasp intricate concepts more efficiently and apply them in real-world scenarios.

Technological advancements and the evolution of cloud-based learning platforms have further propelled the market. The shift toward digital and remote learning, especially post-pandemic, has accelerated the adoption of cloud-based data visualization tools, which offer scalability, accessibility, and seamless integration with other e-learning resources. Cloud deployment eliminates geographical barriers, allowing learners and organizations from diverse regions to access advanced visualization tools and resources at any time. Additionally, the increasing availability of free and open-source visualization libraries such as D3.js has democratized access to these technologies, further expanding the market’s reach across different socioeconomic segments.

Another crucial growth driver is the rising emphasis on upskilling and reskilling initiatives across industries. As automation and artificial intelligence reshape job requirements, data literacy has become a fundamental skill for both students and working professionals. Enterprises are investing heavily in learning platforms that incorporate data visualization tools to train their workforce, ensuring they remain competitive in the digital economy. The trend is mirrored in higher education, where curricula are being revamped to include data visualization modules, reflecting the growing recognition of its importance in fostering analytical and critical thinking skills among learners.

From a regional perspective, North America dominates the Learning Data Visualization Tools Market, accounting for the largest revenue share in 2024. This can be attributed to the presence of leading technology providers, a mature e-learning ecosystem, and high levels of digital adoption in both educational and corporate sectors. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid digital transformation, government initiatives to enhance digital literacy, and the increasing penetration of internet and mobile devices. Europe also contributes significantly, with a strong focus on educational innovation and enterprise training. These regional dynamics are shaping the competitive landscape and driving the global expansion of learning data visualization tools.

Tool Type Analysis

The Tool Type segment of the Learning Data Visualization Tools Market is highly diverse, encompassing established platforms like Tableau, Power BI, and Qlik, as well as newer entrants such as Google Data Studio and open-source solutions like D3.js. Tableau remains a market leader due to its intuitive drag-and-drop interface, robust analytics capabilities, and widespread adoption in both academic and corporate settings. Its ability to handle large datasets and integrate seamlessly with various data sources makes it a preferred choice for institutions aiming to provide hands-on, practical training in data visualization. Power BI, backed by Microsoft’s ecosystem, is gaining significant traction, particularly among enterpr

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 bar chart, text, stacked bar chart, dashboard, horizontal bars, donut chart, area chart, treemap, slicers, table, image.

The Business Data Visualization Software market is experiencing robust growth, driven by the increasing need for businesses of all sizes to derive actionable insights from their data. The market, valued at approximately $25 billion in 2025 (estimated based on typical market growth rates and reported market sizes in similar reports), is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This expansion is fueled by several key factors. The proliferation of big data necessitates efficient visualization tools for effective analysis and decision-making. Furthermore, the growing adoption of cloud-based solutions provides scalability and accessibility, lowering the barrier to entry for SMEs. The demand for advanced analytics capabilities, such as predictive modeling and real-time dashboards, is also significantly boosting market growth. Competition is fierce amongst established players like Microsoft, Tableau (Salesforce), and IBM, and newer entrants alike who are constantly innovating to provide more user-friendly and powerful visualization tools. The market is segmented by application (large enterprises and SMEs) and software type (Linux, Windows, Mac), reflecting the diverse needs of different users and operating systems. North America currently holds the largest market share, followed by Europe and Asia Pacific, with growth expected across all regions as organizations in emerging markets embrace data-driven decision-making. However, factors such as the high initial investment cost of implementing sophisticated software and the need for skilled professionals to effectively utilize these tools can act as restraints on market growth. The market's future trajectory will be shaped by several trends. The increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) into data visualization platforms will enable more insightful and automated analysis. Furthermore, the focus on improving user experience and simplifying complex data visualizations will broaden adoption. The growth of mobile-friendly data visualization applications will also contribute to market expansion, enabling access to data insights anytime, anywhere. The development of open-source alternatives and the continued consolidation within the industry through mergers and acquisitions will further influence the competitive landscape. This dynamic market offers significant opportunities for businesses that can effectively address the evolving needs of data-driven organizations.

The Tableau View extension for CKAN enables the display of Tableau Public visualizations directly within CKAN datasets. By providing a view plugin, this extension allows users to embed interactive Tableau vizzes, enhancing data presentation and exploration capabilities within the CKAN platform. This offers a seamless integration path for organizations already utilizing Tableau Public to share insights drawn from their data. Key Features: Tableau Public Viz Integration: Embed Tableau Public visualizations within CKAN resources through a dedicated view plugin. This plugin allows for the display of interactive Tableau dashboards alongside the underlying data. Simple Configuration: The extension primarily requires enabling the tableau_view plugin within the CKAN configuration file. Further configuration details and display examples may be available on the extension's wiki page (if any wiki pages exist). Streamlined Data Visualization: Provides a direct method to visually represent data managed in CKAN, improving user engagement and comprehension. Use Cases: Open Data Portals: Governments and organizations can use this extension to embed publicly available Tableau visualizations in their open data portals, enhancing the accessibility and understandability of data. Internal Data Dashboards: Organizations using CKAN for internal data management can use the extension to embed Tableau dashboards providing data summaries, trends, and performance metrics. Technical Integration: The extension integrates into CKAN as a view plugin. Once the tableau_view plugin is enabled in the CKAN configuration file (ckan.plugins), it becomes available as a view option for resources that support it. The readme suggests referring to a wiki page for additional configuration details, which, if available, is crucial for proper setup and usage. Benefits & Impact: The Tableau View extension streamlines data visualization for CKAN users. By embedding interactive Tableau Public visualizations, it becomes easier for users to explore, analyze, and understand the data managed by CKAN. This can lead to improved data literacy, more informed decision-making, and broader engagement with open data initiatives.

Explore the booming Visual Development Platform market, driven by big data and cloud adoption. Get insights on market size, CAGR, key drivers, restraints, and regional growth.

The global Data Preparation Software market is poised for substantial growth, projected to reach an estimated $613 million in 2025 with a compelling Compound Annual Growth Rate (CAGR) of 8.5% through 2033. This robust expansion is fueled by the escalating volume and complexity of data generated across all industries, necessitating efficient tools for cleaning, transforming, and enriching raw data into usable formats for analytics and decision-making. Large enterprises, in particular, are significant adopters, leveraging these solutions to manage vast datasets and derive actionable insights. However, the Small and Medium-sized Enterprises (SMEs) segment is emerging as a key growth driver, as more businesses recognize the competitive advantage that well-prepared data offers, even with limited IT resources. The prevalent trend towards cloud-based solutions further democratizes access to advanced data preparation capabilities, offering scalability and flexibility that are crucial in today's dynamic business environment. Key market drivers include the increasing demand for data-driven decision-making, the growing adoption of business intelligence and advanced analytics, and the need for regulatory compliance. Trends such as the integration of AI and machine learning within data preparation tools to automate repetitive tasks, the rise of self-service data preparation for business users, and the focus on data governance and quality are shaping the market landscape. While the market exhibits strong growth, potential restraints could include the high initial cost of some sophisticated solutions and the need for skilled personnel to fully leverage their capabilities. Geographically, North America and Europe are expected to continue their dominance, driven by established technological infrastructure and a strong analytics culture. However, the Asia Pacific region is anticipated to witness the fastest growth due to rapid digital transformation and increasing data generation. Here's a comprehensive report description on Data Preparation Software, incorporating your specified elements:

This report provides an in-depth analysis of the global Data Preparation Software market, projecting a robust growth trajectory from a Base Year of 2025 through a Forecast Period of 2025-2033. The Study Period covers 2019-2033, with a particular focus on the Estimated Year of 2025 and the Historical Period of 2019-2024. We project the market to reach substantial valuations, with the global market size estimated to be over $500 million in 2025, and poised for significant expansion in the coming decade.

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The visual analytics market has the potential to grow by USD 4.39 billion during 2021-2025, and the market’s growth momentum will accelerate at a CAGR of 11.32%.

This visual analytics market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers market segmentation by end-user (BFSI, CPG and retail, healthcare, manufacturing, and others) and geography (North America, APAC, Europe, MEA, and South America). The visual analytics market report also offers information on several market vendors, including Altair Engineering Inc., Alteryx Inc., Arcadia Data Inc., Datameer Inc., International Business Machines Corp., Microsoft Corp., QlikTech international AB, SAP SE, SAS Institute Inc., and Tableau Software LLC among others.

What will the Visual Analytics Market Size be in 2021?

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Visual Analytics Market: Key Drivers and Trends

The growing availability and complexity of data are notably driving the visual analytics market growth, although factors such as data privacy and security concerns may impede market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the visual analytics industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

      The growing availability and complexity of data will fuel the growth of the visual analytics market size.
      The availability of a large volume of data and rapidly growing data complexity in organizations are the major drivers for the development of various intelligence-based data analysis techniques.
      Intelligent techniques involving technologies such as ML and AI can help companies retrieve the huge amount of complex data in a useful manner and use that data to enhance their services and business processes. This, in turn, is expected to drive the growth of the market for visual analytics.




      The increased dependency on Internet for critical operations will drive the visual analytics market growth during the forecast period.
      E-commerce vendors are posting advertisements on search engines and other websites to attract several customers. This will increase the demand for visual analytics to help e-commerce vendors track customers, analyze customer behavior, and ensure proper decision-making.
      With the rising popularity and use of e-commerce, the number of digital media advertisements by e-commerce vendors is expected to increase, which will drive the growth of the market during the forecast period.

This visual analytics market analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth strategies for 2021-2025.

Who are the Major Visual Analytics Market Vendors?

The report analyzes the market’s competitive landscape and offers information on several market vendors, including:

Altair Engineering Inc.
Alteryx Inc.
Arcadia Data Inc.
Datameer Inc.
International Business Machines Corp.
Microsoft Corp.
QlikTech international AB
SAP SE
SAS Institute Inc.
Tableau Software LLC

This statistical study of the visual analytics market encompasses successful business strategies deployed by the key vendors. The visual analytics market is fragmented and the vendors are deploying growth strategies such as providing customized solutions to compete in the market.

To make the most of the opportunities and recover from post COVID-19 impact, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

The visual analytics market forecast report offers in-depth insights into key vendor profiles. The profiles include information on the production, sustainability, and prospects of the leading companies.

Which are the Key Regions for Visual Analytics Market?

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35% of the market’s growth will originate from North America during the forecast period. The US is a key market for visual analytics in North America. Market growth in this region will be faster than the growth of the market in Europe, MEA, and South America.

This market research report entails detailed information on the competitive intelligence, marketing gaps, and regional opportunities in store for vendors, which will assist in creating efficient business plans.

What are the Revenue-generating End-user Segments in the Visual Analy

The different leaders at Airbnb want to understand some important insights based on various attributes in the dataset so as to increase the revenue such as -

Which type of hosts to acquire more and where? The categorization of customers based on their preferences. What are the neighborhoods they need to target? What are the pricing ranges preferred by customers? The various kinds of properties that exist w.r.t. customer preferences. Adjustments in the existing properties to make it m more customer-oriented. What are the most famous localities and properties in New York currently? How to get unpopular properties more traction? and so on...

To prepare for the next best steps Airbnb needs to take as a business, you have been asked to analyze a dataset of various Airbnb listings in New York. Based on this analysis, Two presentations to the following groups need to be given. 1. Data Analysis Managers and Lead Data Analyst 2. Head of Acquisitions and Operations, NYC, and Head of User Experience, NYC.

The global Self-Service Business Intelligence (BI) Software market is poised for significant expansion, projected to reach a market size of $1389 million. This robust growth is driven by an anticipated Compound Annual Growth Rate (CAGR) of 7.8% from 2025 to 2033, indicating a dynamic and evolving landscape. The core of this expansion is fueled by the increasing democratization of data analytics, empowering businesses of all sizes to make data-driven decisions without relying heavily on dedicated IT departments. Large enterprises, with their vast datasets and complex analytical needs, are a primary segment, but Small and Medium-sized Enterprises (SMEs) are rapidly adopting these solutions to gain a competitive edge. The shift towards cloud-based deployments is a dominant trend, offering scalability, flexibility, and cost-effectiveness, which is crucial for widespread adoption across diverse business models. Key growth drivers include the escalating volume of data generated across industries, the persistent need for faster and more intuitive data insights, and the growing awareness of BI's role in strategic planning and operational efficiency. Companies like Zoho, Microsoft, Tableau, Google, and Salesforce are at the forefront, offering sophisticated yet user-friendly platforms. While the market is experiencing strong tailwinds, potential restraints such as data security concerns and the initial investment in training and integration for some organizations, may present challenges. Nevertheless, the overarching demand for actionable intelligence, coupled with continuous innovation in AI and machine learning integration within BI tools, will propel sustained market advancement throughout the forecast period. This comprehensive report delves into the dynamic Self-Service Business Intelligence (SSBI) Software market, offering a granular analysis of its trajectory from 2019 to 2033. Based on a Base Year of 2025, with an Estimated Year also of 2025, and a Forecast Period spanning 2025-2033, this study meticulously examines the Historical Period of 2019-2024. We will explore market concentration, key trends, regional dominance, product insights, and crucial growth drivers, while also identifying challenges and emerging opportunities. The report aims to provide stakeholders with actionable intelligence to navigate this rapidly evolving landscape.

The market for data visualization software for large screens is experiencing robust growth, driven by the increasing need for effective communication of complex data in command centers, exhibition halls, and corporate settings. The global market, estimated at $2.5 billion in 2025, is projected to expand significantly over the next decade, fueled by several key factors. The adoption of cloud-based solutions is accelerating, offering scalability and accessibility advantages over on-premise deployments. Furthermore, the rising demand for real-time monitoring and data-driven decision-making across diverse sectors such as government, defense, and corporate businesses is propelling market expansion. The trend towards interactive and immersive visualization experiences, utilizing advanced technologies like augmented and virtual reality, further contributes to the growth trajectory. While the initial investment in hardware and software can be a restraint for some organizations, the long-term benefits in operational efficiency and improved decision-making are outweighing this concern. The market segmentation, comprising application-based categories (real-time monitoring, strategic command, etc.) and deployment types (cloud and on-premise), provides opportunities for tailored solutions and caters to the diverse needs of end-users. Competition is fierce, with established players like Tableau and Google competing alongside specialized providers such as FineReport and Sisense. Geographic expansion, particularly in rapidly developing economies of Asia-Pacific, is expected to contribute to the overall market growth in the coming years. The competitive landscape features both established players with extensive product portfolios and niche providers focusing on specific industry applications. Strategic partnerships, product innovation, and mergers and acquisitions are anticipated to shape the market dynamics. The future growth will be significantly influenced by factors such as technological advancements in data visualization techniques, increasing data volumes from IoT devices, and the growing adoption of AI-powered analytics to provide more insightful and actionable visualizations. The market’s evolution is likely to involve greater integration with other business intelligence tools and a shift towards more intuitive and user-friendly interfaces to improve accessibility and data literacy across organizations. A sustained focus on cybersecurity and data privacy will also play a crucial role in shaping the market's trajectory in the long term.