Dataset created as part of the Master Thesis "Business Intelligence – Automation of Data Marts modeling and its data processing".

Lucerne University of Applied Sciences and Arts

Master of Science in Applied Information and Data Science (MScIDS)

Autumn Semester 2022

Change log Version 1.1:

The following SQL scripts were added:

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    pg.dictionary_table


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    pg.dictionary_relation


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    pg.get_dimension_candidate


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    pg.get_columns

Scripts are based on Microsoft SQL Server Version 2017 and compatible with a data warehouse built with Datavault Builder. Data warehouse objects scripts of the sample data warehouse are restricted and cannot be shared.

The following are documents that were used to build a mock database and data warehouse and sample analysis on the data warehouse. The mock company is a summer camp agency. The software that was used for this project was SQL, Excel, Visual Studio, and Power BI.

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Data Warehouse As A Service Market Size 2024-2028

The data warehouse as a service market size is forecast to increase by USD 12.32 billion at a CAGR of 24.49% between 2023 and 2028.

The market is experiencing significant growth due to several key trends. One major trend is the shift from traditional on-premises data warehouses to cloud-based DWaaS solutions. Advanced storage technologies, such as columnar databases, in-memory storage, and cloud storage, are also driving market growth. 
However, data privacy and security risks are challenges that need to be addressed, as organizations move their data to the cloud. DWaaS providers are responding by implementing data security and data encryption techniques to mitigate these risks. Overall, the DWaaS market is poised for continued growth as more businesses seek to leverage the benefits of cloud-based data warehousing solutions.

What will be the Size of the Data Warehouse As A Service Market During the Forecast Period?

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The market represents a significant shift in how businesses manage their data environments. DWaaS offers flexibility and scalability, enabling organizations to focus on their core competencies while leveraging cloud computing for their data warehousing needs. This market is driven by the increasing demand for Business Intelligence (BI) that can handle large data volumes and provide advanced analytics capabilities. 
Technological developments in cloud computing, software, computing, and storage have made DWaaS a viable alternative to traditional on-premises data warehouses. However, the adoption of DWaaS is not without challenges. Security issues and integration complexities are key concerns for businesses considering a move to the cloud.
Restricted customization is another challenge, as some organizations require specific configurations for their data warehouses. Despite these challenges, the benefits of DWaaS, such as reduced IT infrastructure complexity and improved data accessibility, continue to drive market growth. The DWaaS market is expected to expand as more businesses seek to harness the power of their data for enterprise management, visualization, and data analytics.

How is this Data Warehouse As A Service Industry segmented and which is the largest segment?

The DWaaS industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  BFSI
  Government
  Healthcare
  E-commerce and retail
  Others


Type

  Enterprise DWaaS
  Operational data storage


Geography

  North America

    US


  Europe

    Germany
    France


  APAC

    China
    Japan


  Middle East and Africa



  South America

By End-user Insights

The BFSI segment is estimated to witness significant growth during the forecast period.

The BFSI sector's reliance on managing and analyzing large financial data volumes has fueled the adoption of Data Warehouse as a Service (DWaaS) solutions. DWaaS offers flexibility and scalability, enabling BFSI companies to efficiently manage data from retail banking institutions, lending operations, credit underwriting procedures, and financial consulting firms. DWaaS solutions provide core competencies in cloud computing, business intelligence (BI), data analytics, enterprise management, visualization, and BI solutions. Technological developments, such as IoT technology and AI technology, further enhance DWaaS capabilities. However, challenges persist, including security issues, integration challenges, and restricted customization. Cloud solutions, including cloud data warehouses, offer a data environment that is software, computing, and storage-intensive.

DWaaS companies address concerns with service disruptions, latency, data integration, and data access. Security measures, such as data encryption and data masking, ensure data privacy. Despite these challenges, DWaaS adoption continues to grow, offering decision support services, data categorization, and data assessment to mid-size businesses and large enterprises.

Get a glance at the Data Warehouse As A Service Industry report of share of various segments Request Free Sample

The BFSI segment was valued at USD 665.10 million in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 35% to the growth of the global market during the forecast period.

Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

For more insights on the market share of various regions, Request Free Sample

The North American market for Data Warehouse as a Service (DWaaS) is experiencing significant growth due to the region's early adoption of advanced techn

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

Snapshot img

Cloud Data Warehouse Market Size 2025-2029

The cloud data warehouse market size is forecast to increase by USD 63.91 billion at a CAGR of 43.3% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing penetration of IoT-enabled devices generating vast amounts of data. This data requires efficient storage and analysis, making cloud data warehouses an attractive solution due to their scalability and flexibility. Additionally, the growing need for edge computing further fuels market expansion, as organizations seek to process data closer to its source in real-time. However, challenges persist in the form of company lock-in issues, where businesses may find it difficult to migrate their data from one cloud provider to another, potentially limiting their flexibility and strategic options.
To capitalize on market opportunities and navigate challenges effectively, companies must stay informed of emerging trends and adapt their strategies accordingly. By focusing on interoperability and data portability, they can mitigate lock-in risks and maintain agility in their data management strategies. The market is experiencing significant growth due to several key trends. The increasing penetration of Internet of Things (IoT) devices is driving the need for more efficient data management solutions, leading to the adoption of cloud data warehouses.

What will be the Size of the Cloud Data Warehouse Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic market, businesses seek efficient solutions for managing and analyzing their data. Data visualization tools and business intelligence platforms enable users to gain insights through interactive dashboards and reports. Data automation tools streamline data processing, while data enrichment tools enhance data quality by adding external data sources. Data virtualization tools provide a unified view of data from various sources, and data integration tools ensure seamless data flow between systems. NoSQL databases and big data platforms offer scalability and flexibility for handling large volumes of data. Data cleansing tools eliminate errors and inconsistencies, while data encryption tools secure sensitive data.
Data migration tools facilitate moving data between systems, and data validation tools ensure data accuracy. Real-time analytics platforms and predictive analytics platforms provide insights in near real-time, while prescriptive analytics platforms suggest actions based on data trends. Data deduplication tools eliminate redundant data, and data governance tools ensure compliance with regulations. Data orchestration tools manage workflows, and data science platforms facilitate machine learning and artificial intelligence applications. Data archiving tools store historical data, and data pipeline tools manage data movement between systems. Data fabric and data standardization tools ensure data consistency across the organization, while data replication tools maintain data availability and disaster recovery.

How is this Cloud Data Warehouse Industry segmented?

The cloud data warehouse industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Industry Application

  Large enterprises
  SMEs


Deployment

  Public
  Private


End-user

  Cloud server provider
  IT and ITES
  BFSI
  Retail
  Others


Application

  Customer analytics
  Business intelligence
  Data modernization
  Operational analytics
  Predictive analytics


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By Industry Application Insights

The large enterprises segment is estimated to witness significant growth during the forecast period. In today's business landscape, cloud data warehouse solutions have gained significant traction among large enterprises, enabling them to efficiently manage and process data across various industries and geographies. Traditional on-premises data warehouses come with high costs due to the need for expensive hardware and physical space. Cloud-based alternatives offer a more cost-effective and convenient solution, allowing organizations to access tools and information remotely and streamline document sharing between multiple workplaces. Predictive analytics, data cost optimization, and data discovery are key drivers for cloud data warehouse adoption. These technologies offer insights into data trends and patterns, helping businesses make data-driven decisions.

Data timeliness and data standardization ar

Data Warehousing Market Outlook

According to our latest research, the global Data Warehousing market size reached USD 32.7 billion in 2024, reflecting robust adoption across diverse industry verticals. The market is anticipated to expand at a CAGR of 8.6% from 2025 to 2033, driven by surging demand for advanced analytics, cloud integration, and real-time business intelligence. By 2033, the Data Warehousing market size is forecasted to reach USD 68.2 billion, underscoring the sector’s pivotal role in empowering organizations to harness data for strategic decision-making. This growth is underpinned by the ongoing digital transformation across sectors, the proliferation of big data, and the increasing adoption of cloud-based solutions.

The rapid expansion of the Data Warehousing market is primarily fueled by the exponential increase in data volumes generated from various sources such as IoT devices, enterprise applications, and social media platforms. Organizations across industries are striving to convert raw data into actionable insights, leading to heightened investments in data warehousing infrastructure and solutions. The integration of artificial intelligence and machine learning algorithms within data warehouses is enabling advanced analytics, predictive modeling, and real-time reporting, which further accelerates market growth. Additionally, the push towards digital transformation initiatives is compelling enterprises to modernize their legacy data management systems and migrate to more agile and scalable data warehousing platforms.

Another significant growth factor for the Data Warehousing market is the increasing adoption of cloud-based data warehousing solutions. Cloud deployment offers unparalleled scalability, flexibility, and cost efficiency, making it an attractive choice for both large enterprises and small and medium-sized businesses (SMEs). Cloud data warehouses eliminate the need for substantial upfront capital expenditure and reduce the complexities associated with on-premises infrastructure management. Furthermore, the integration of data warehousing with other cloud services, such as advanced analytics and AI-driven tools, enhances the overall value proposition for organizations seeking to optimize their data-driven decision-making processes.

The proliferation of self-service business intelligence (BI) tools and the growing emphasis on data democratization are also catalyzing the growth of the Data Warehousing market. Enterprises are empowering business users with intuitive tools that enable them to access, analyze, and visualize data without heavy reliance on IT departments. This shift not only accelerates the pace of decision-making but also fosters a data-driven culture within organizations. As regulatory requirements around data privacy and security become more stringent, data warehousing solutions are evolving to incorporate advanced security features, compliance frameworks, and robust data governance capabilities, further boosting market adoption.

Regionally, North America continues to dominate the Data Warehousing market due to the early adoption of advanced technologies, the presence of major cloud service providers, and a mature digital ecosystem. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid digitalization, increasing IT investments, and the proliferation of SMEs embracing cloud-based analytics. Europe is also witnessing steady growth, supported by stringent data protection regulations and a strong focus on digital innovation. The Middle East & Africa and Latin America are gradually catching up, with organizations in these regions increasingly recognizing the strategic value of data warehousing in driving business transformation.

Component Analysis

The Component segment of the Data Warehousing market comprises ETL Solutions, Data Warehouse Database, Data Warehouse Software, and Services. ETL (Extract, Transform, Load) solutions are foundational to the data warehousing process, enabling organizat

This is the sample database from sqlservertutorial.net. This is a great dataset for learning SQL and practicing querying relational databases.

Database Diagram:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F4146319%2Fc5838eb006bab3938ad94de02f58c6c1%2FSQL-Server-Sample-Database.png?generation=1692609884383007&alt=media" alt="">

Terms of Use

The sample database is copyrighted and cannot be used for commercial purposes. For example, it cannot be used for the following but is not limited to the purposes: - Selling - Including in paid courses

The Data Warehouse As A Service Market Report is Segmented by Deployment Model (Public Cloud, Private Cloud, Hybrid/Multi-cloud), End-User Enterprise Size (Large Enterprises, Small and Medium Enterprises), End-User Industry (BFSI, Government and Public Sector, and More), Service Type (Enterprise DWaaS, Operational Data-Store As A Service, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Snapshot img

Enterprise Data Warehouse (EDW) Market Size 2025-2029

The enterprise data warehouse (edw) market size is valued to increase USD 43.12 billion, at a CAGR of 28% from 2024 to 2029. Data explosion across industries will drive the enterprise data warehouse (edw) market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 32% growth during the forecast period.
By Product Type - Information and analytical processing segment was valued at USD 4.38 billion in 2023
By Deployment - Cloud based segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 857.82 million
Market Future Opportunities: USD 43116.60 million
CAGR : 28%
APAC: Largest market in 2023

Market Summary

The market is a dynamic and ever-evolving landscape, characterized by continuous innovation and adaptation to industry demands. Core technologies, such as cloud computing and big data analytics, are driving the market's growth, enabling organizations to manage and analyze vast amounts of data more effectively. In terms of applications, business intelligence and data mining are leading the way, providing valuable insights for strategic decision-making. Service types, including consulting, implementation, and support, are essential components of the EDW market. According to recent reports, the consulting segment is expected to dominate the market due to the increasing demand for expert advice in implementing and optimizing EDW solutions. However, data security concerns remain a significant challenge, with regulations like GDPR and HIPAA driving the need for robust security measures. Despite these challenges, the market continues to expand, with data explosion across industries fueling the demand for EDW solutions. For instance, the healthcare sector is projected to witness a compound annual growth rate (CAGR) of 15.3% between 2021 and 2028. Furthermore, the market is witnessing a significant focus on new solution launches, with major players like Microsoft, IBM, and Oracle introducing advanced EDW offerings to meet the evolving needs of businesses.

What will be the Size of the Enterprise Data Warehouse (EDW) Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Enterprise Data Warehouse (EDW) Market Segmented and what are the key trends of market segmentation?

The enterprise data warehouse (edw) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. Product TypeInformation and analytical processingData miningDeploymentCloud basedOn-premisesSectorLarge enterprisesSMEsEnd-userBFSIHealthcare and pharmaceuticalsRetail and E-commerceTelecom and ITOthersGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW)

By Product Type Insights

The information and analytical processing segment is estimated to witness significant growth during the forecast period.

The market is experiencing significant growth, with data replication strategies becoming increasingly sophisticated to ensure capacity planning models accommodate expanding data volumes. ETL tool selection and business intelligence platforms are crucial components, enabling query optimization strategies and disaster recovery planning. Data warehouse migration, data profiling methods, and real-time data ingestion are essential for maintaining a competitive edge. Data warehouse automation, data quality metrics, and data warehouse modernization are ongoing priorities, with data cleansing techniques and dimensional modeling techniques essential for ensuring data accuracy. Data warehousing architecture, performance monitoring tools, and high availability solutions are integral to ensuring scalability and availability. Audit trail management, data lineage tracking, and data warehouse maintenance are critical for maintaining data security and compliance. Data security protocols and data encryption methods are essential for protecting sensitive information, while data virtualization techniques and access control mechanisms facilitate self-service business intelligence tools. ETL process optimization and data governance policies are key to streamlining operations and ensuring data consistency. The IT, BFSI, education, healthcare, and retail sectors are driving market growth, with information processing and analytical processing becoming increasingly important. The construction of web-based accessing tools integrated with web browsers is a current trend, enabling users to access data warehouses easily. According to recent studies, the market for data warehousing solutions is projected to grow by 18.5%, while the adoption of cloud data warehou

Logical Data Warehouse Market Outlook

According to our latest research, the global logical data warehouse market size in 2024 stands at USD 6.4 billion, reflecting robust demand from enterprises seeking agile, scalable, and integrated data solutions. The market is expected to advance at a CAGR of 19.2% from 2025 to 2033, reaching a projected value of USD 29.9 billion by 2033. This remarkable growth is primarily driven by the rising need for real-time data integration and analytics, as organizations across industries optimize their data architectures to support digital transformation and informed decision-making.

One of the most significant growth factors for the logical data warehouse market is the exponential increase in data volumes generated by organizations. As businesses adopt digital-first strategies, the proliferation of structured and unstructured data from diverse sources, including IoT devices, cloud applications, and social media platforms, has created a pressing need for unified data management frameworks. Logical data warehouses offer a virtualized approach, enabling seamless access, integration, and analysis of distributed data without the need for physical consolidation. This agility not only accelerates time-to-insight but also reduces the costs and complexities associated with traditional data warehousing solutions, making logical data warehouses an attractive proposition for enterprises aiming to remain competitive in a data-driven world.

Another key driver is the increasing adoption of advanced analytics and artificial intelligence across sectors such as BFSI, healthcare, and retail. Logical data warehouses empower organizations to harness real-time data streams for predictive analytics, machine learning, and business intelligence applications, all while ensuring data governance and compliance. The ability to integrate disparate data sources and provide a single, unified view significantly enhances the accuracy and efficiency of analytics initiatives. This capability is particularly crucial for industries that rely on timely insights to optimize operations, personalize customer experiences, and mitigate risks. As a result, the logical data warehouse market continues to witness strong traction among organizations seeking to leverage data as a strategic asset.

Furthermore, the growing emphasis on data governance, privacy, and regulatory compliance is shaping market dynamics. With stringent regulations such as GDPR and CCPA, enterprises are under increasing pressure to maintain data integrity, lineage, and security across their data ecosystems. Logical data warehouses facilitate centralized governance by providing robust metadata management, access controls, and audit trails, ensuring that organizations can meet regulatory requirements while maximizing the value of their data assets. The convergence of data integration, governance, and analytics within a single logical framework is a compelling factor driving market adoption, particularly among large enterprises and highly regulated industries.

From a regional perspective, North America currently dominates the logical data warehouse market, accounting for the largest share in 2024 due to early technology adoption and the presence of leading vendors. However, Asia Pacific is poised for the highest growth rate over the forecast period, fueled by rapid digital transformation initiatives and increasing investments in cloud infrastructure. Europe is also witnessing substantial demand, driven by strict data privacy regulations and a mature enterprise landscape. Meanwhile, Latin America and the Middle East & Africa are gradually emerging as promising markets, supported by the expansion of digital economies and government-led smart initiatives. The global outlook indicates a robust and geographically diversified growth trajectory for the logical data warehouse market through 2033.

Component Analysis

The logical data warehouse market is segmented by component into software and services, each playing a pivotal role in enabling organization

According to Cognitive Market Research, the global data warehouse as a service market was USD 4,874.9 million in 2022 and will grow at a compound annual growth rate (CAGR) of 23.5% from 2023 to 2030. How are the Key Drivers Affecting the Data Warehouse as a Service Market?

Rising Demand for High Speed And Low Latency Analytics is Driving the Data Warehouse as a Service Market

The rising demand for high-speed and low-latency analytics propels the Data Warehouse as a Service (DWaaS) Market. Businesses require real-time insights from vast datasets to make agile decisions. DWaaS platforms can process and analyze data rapidly, enabling quicker response times.

In May 2021, WPP unveiled a collaboration with Microsoft aimed at innovative content production transformation by introducing Cloud Studio.

(Source:http://news.microsoft.com/2021/05/05/wpp-and-microsoft-to-creatively-transform-content-production-through-new-cloud-studio-partnership/)

With the need to extract actionable insights swiftly, DWaaS solutions cater to this demand, enhancing operational efficiency, improving decision-making, and bolstering organizations' competitiveness in the rapidly evolving digital landscape.

The Factors Restraining the Growth of the Data Warehouse as a Service Market

Data Security Concerns are Restraining the Data Warehouse as a Service Market

Data security concerns constrain the Data Warehouse as a Service (DWaaS) Market. Organizations hesitate to migrate sensitive data to cloud-based solutions due to potential breaches, unauthorized access, and compliance risks. Ensuring robust encryption, authentication, and compliance with data protection regulations is challenging. Building trust in cloud-based storage and analytics security is crucial for wider DWaaS adoption as businesses prioritize safeguarding their valuable data assets.

Impact of the COVID-19 Pandemic on the Data Warehouse as a Service Market:

COVID-19 significantly disrupted the Data Warehouse as a Service (DWaaS) market. The pandemic's remote work requirements accelerated the demand for cloud-based data solutions. Organizations sought scalable and accessible DWaaS to accommodate changing data needs. Simultaneously, economic uncertainties led some businesses to delay or reconsider investments. The DWaaS landscape responded with increased emphasis on flexibility, remote accessibility, cost optimization, and robust security measures to address the evolving challenges posed by the pandemic. Introduction of Data Warehouse as a Service:

The data warehouse as a service (DWaaS) Market is growing due to businesses' increasing need for scalable and cost-effective data management solutions. DWaaS offers the flexibility to handle large and diverse data sets, enabling data-driven decision-making. The cloud-based nature of DWaaS streamlines implementation reduces infrastructure costs, and ensures easy accessibility, contributing to its rapid adoption and market expansion.

In February 2021, AWS launched the Amazon Redshift Query Editor, compatible with ENHANCED cluster VPC routing. This feature extends support to all node types, and the query time-out limit was extended from 10 minutes to 24 hours for handling queries with longer execution times.

(Source:http://aws.amazon.com/about-aws/whats-new/2021/02/amazon-redshift-query-editor-supports-clusters-with-enhanced-vpc-routing-query-run-times-node-types/)

The CMAR Data Warehouse is an spatially enabled Oracle data repository which contains survey underway, CTD data, hydrological (bottle sample) data, biological catch data from Divisional research vessels, and data from other sources as presently held in the Division's archive. There are GIS layers covering a range of themes obtained from WA agencies and Industry for use in the NWSJEMS project available only to NWSJEMS researchers. Moored instrument data from CMAR research deployments contain currents for various ocean regions. On-line access to this data is usually with the CMAR Data Trawler (see Marlin record 6389), a Java application developed under the auspices of the North West Shelf Joint Environmental Management Study (NWSJEMS) and the CMAR Data Centre. Public users have only limited access to Warehouse content.

Real-Time Data Warehouse Market Outlook

According to our latest research, the global Real-Time Data Warehouse market size reached USD 6.4 billion in 2024. The market is experiencing robust growth, driven by the increasing adoption of advanced analytics and the necessity for instantaneous insights across industries. The market is forecasted to grow at a CAGR of 12.7% from 2025 to 2033, reaching a projected value of USD 18.8 billion by 2033. Key growth drivers include the proliferation of IoT devices, surging demand for real-time business intelligence, and the rapid digital transformation initiatives undertaken by organizations worldwide.

The primary growth factor for the Real-Time Data Warehouse market is the exponential increase in data generation from diverse sources such as IoT sensors, social media, enterprise applications, and connected devices. Organizations today are under immense pressure to process, analyze, and act on data as it is generated, enabling them to make informed decisions in real time. This has led to a significant shift from traditional batch-processing data warehouses to modern real-time architectures that can ingest, process, and deliver actionable insights instantaneously. As businesses strive to gain a competitive edge by leveraging data-driven strategies, the demand for real-time data warehousing solutions continues to surge across various industry verticals.

Another critical driver is the evolving landscape of customer expectations and regulatory requirements. In sectors such as BFSI, healthcare, and retail, consumers and regulators alike are demanding greater transparency, faster response times, and improved service delivery. Real-time data warehouses empower organizations to monitor transactions, detect anomalies, and respond to customer needs with unprecedented speed and accuracy. Additionally, the integration of advanced technologies such as artificial intelligence, machine learning, and predictive analytics with real-time data warehouses is unlocking new possibilities for personalized experiences, fraud detection, and operational efficiency. These advancements are fueling further investment in real-time data warehousing infrastructure and solutions.

The shift towards cloud-based solutions is another significant growth factor for the Real-Time Data Warehouse market. Cloud deployment offers unparalleled scalability, flexibility, and cost efficiency, making it an attractive option for organizations of all sizes. The cloud also facilitates seamless integration with other enterprise systems and enables real-time data sharing across geographically dispersed teams. As digital transformation accelerates, enterprises are increasingly migrating their data warehousing workloads to the cloud to leverage its benefits. This trend is further amplified by the rise of hybrid and multi-cloud strategies, which allow organizations to optimize their data management and analytics capabilities while maintaining compliance and security.

From a regional perspective, North America continues to dominate the Real-Time Data Warehouse market, owing to its advanced IT infrastructure, strong presence of leading technology vendors, and early adoption of cutting-edge analytics solutions. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid industrialization, increasing digitalization, and the proliferation of connected devices. Europe also holds a significant share, supported by stringent data regulations and a strong focus on innovation. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth as organizations in these regions recognize the value of real-time data-driven decision-making and invest in modern data warehousing solutions.

Component Analysis

The Component segment of the Real-Time Data Warehouse market is broadly categorized into software, hardware, and services. Each of these components plays a crucial role in enabling organizations to build, manage, and optimize their real-time data warehousing

Photo by Maxim Hopman on Unsplash.

Introduction

According to Economatica, a company specializing in the Latin American stock market, the Brazilian stock exchange market, governed by Brasil, Bolsa, Balcão (B3), exchanged BRL ~25.9 billion per day in the first half of 2020, during the coronavirus epidemic. Furthermore, it is estimated that in this same period there was an 18% growth in the number of Brazilian investors, totaling ~2.6 million active investors. Therefore, the financial market moves a large amount of values and, consequently, produces a vast amount of information and data daily; These data represent the movements of shares, their respective prices, dollar exchange values, and so on. This dataset contains daily stock values and information about their companies.

Inspiration

• Data Analysis - Spark
• Price Prediction - Regression task
• Best Group of Stocks - Association Rules task

This dataset provides an environment (Data Warehouse-like) for analysis and visualization of financial business for users of decision support systems. Specifically, the data allow compare different assets (i.e. stocks) listed on B3, according to the sectors of the economy in which these assets operate. For example, with this Data Warehouse, the user will be able to answer questions similar to this one: What are the most profitable sectors for investment in a given period of time? In this way, the user can identify which are the sectors that are standing out, as well as which are the most profitable companies in the sector.

Dataset

https://i.imgur.com/28Mf0sN.png" alt="Data Warehouse">

This dataset is split into five files: - dimCoin.csv - Dimension table with information about the coins. - dimCompany.csv - Dimension table with information about the companies. - dimTime.csv - Dimension table with information about the datetime. - factCoins.csv - Fact table with coin value over time. - factStocks.csv - Fact table with stock prices over time.

Source

The data were available by B3. You can access in https://www.b3.com.br/en_us/market-data-and-indices/ .I just structure and model the data as Data Warehouse tables. You can access my code in https://github.com/leomaurodesenv/b3-stock-indexes

GMP2 Africa Region dataset contains information on POPs concentrations in ambient air, human tissue - breast milk and surface water; for water-soluble fluorinated POPs only (perfluorooctane sulfonic acid, its salts and perfluorooctane sulfonyl fluoride). The second global data collection that can be seen in this dataset was held during 2013–2014 and it contained information on 23 POPs listed in the Stockholm Convention when the second global data collection took place. The data were sampled between 2008 and 2014, however also older data were reported. The Africa Region is characterized by six different climatic zones that have influence on the movement and distribution of POPs. In addition, except for large deserts in Northern and Southern Africa, the regions face challenges associated with hot and humid climatic conditions that promote growth of a myriad of pests and disease vectors. POPs have therefore been used in many sectors including agriculture, industry and public health to control pests and diseases. The region collaborated with the following programmes and strategic partners to obtain data on core media: • the MONET-Africa project coordinated by the Centre of Excellence in Environmental Chemistry and Ecotoxicology, Brno, Czech Republic (RECETOX), • the Global Atmospheric Passive Sampling (GAPS) programme coordinated by Environment Canada, • the World Health Organization (WHO) – Milk survey

Explore detailed Hand Knotted import data of Rh Richmond Sample Warehouse in the USA—product details, price, quantity, origin countries, and US ports.

Rh Richmond Sample Warehouse Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Explore detailed Handknotted Carpet import data of Rh Richmond Sample Warehouse in the USA—product details, price, quantity, origin countries, and US ports.

Adventure Works 2022 dataset

How this Dataset is created?

On the official website the dataset is available over SQL server (localhost) and CSVs to be used via Power BI Desktop running on Virtual Lab (Virtaul Machine). As per first two steps of Importing data are executed in the virtual lab and then resultant Power BI tables are copied in CSVs. Added records till year 2022 as required.

How this Dataset may help you?

this dataset will be helpful in case you want to work offline with Adventure Works data in Power BI desktop in order to carry lab instructions as per training material on official website. The dataset is useful in case you want to work on Power BI desktop Sales Analysis example from Microsoft website PL 300 learning.

How to use this Dataset?

Download the CSV file(s) and import in Power BI desktop as tables. The CSVs are named as tables created after first two steps of importing data as mentioned in the PL-300 Microsoft Power BI Data Analyst exam lab.