Data Warehousing trainings

Data Warehousing Training

• Training type: E-learning (online)
• Language: English
• Online access: 24/7, 365 days after activation
• Interactive multimedia lessons with video, audio and subtitles
• Videos of up to 3-10 minutes, watchable at your own pace
• Practical exercises with real-time analysis of actions and results
• Flexible management with progress reporting
• View lessons by specific topic
• Your answers are immediately evaluated
• The software tells you exactly where your possible mistakes lie
• Possibility to repeat an assignment (unlimited)
• View solution videos
• Data Warehousing Certifications
• Tips & Tricks
• Exam Quiz
• MeasureUp Exam Simulation (150+ questions)
• LiveLabs (if available)
• Award Winning E-learning
• Full training for the official Exam
• User-friendly environment
• Includes Online Tutor (via email and chat)
• Certificate of Participation included

What is Data Warehousing?

Data warehousing is the process of collecting, managing and storing large amounts of data from various sources in a centralized location specifically for reporting and data analysis. It is a technique used to support business intelligence (BI) activities, where data is processed to gain insights and make informed decisions.

In data warehousing, data is collected from various sources, such as databases, spreadsheets and other data storage systems, and integrated into a single, comprehensive data repository. The data is then transformed and organized according to specific rules and structures to make it easily accessible and analyzable.

Data warehousing is essential for organizations because it enables them to make informed business decisions based on reliable, consolidated data. It provides a comprehensive view of an organization's data that can be used for various purposes, such as trend analysis, forecasting and strategic planning.

Data warehousing systems can be complex and require specialized knowledge to design, implement and maintain. Therefore, many organizations turn to certified professionals to help them manage their data warehousing systems and maximize their benefits.

Why Data Warehousing?

Data warehousing is important because it enables organizations to store, manage and analyze large amounts of structured and unstructured data from various sources in a central repository. This helps companies make informed decisions by providing a comprehensive and holistic view of their operations. With data warehousing, organizations can also identify patterns and trends, monitor performance and detect anomalies in real-time, allowing them to respond quickly to changing market conditions and optimize their operations for maximum efficiency and profitability.

In addition, data warehousing helps organizations comply with regulatory requirements by maintaining complete and accurate records of their data transactions and activities. All in all, data warehousing is critical for modern companies that rely on data-driven insights to remain competitive and achieve long-term success.

How does Data Warehousing work?

Data warehousing involves collecting and consolidating data from various sources into a central repository. The process usually involves extracting data from different systems, transforming it into a consistent format and loading it into the data warehouse.

The data is organized into subject areas, such as sales, marketing or customer data, so that users can more easily access the information they need. Data warehousing also includes the use of specialized tools and technologies to ensure data quality, manage metadata and provide reporting and analysis capabilities.

Once data is loaded into the data warehouse, it can be used for various purposes, such as business intelligence, reporting and analysis. Users can query the data with tools such as SQL or business intelligence software to gain insights and make informed decisions.

Data warehousing also enables historical analysis of data, which is important for trend analysis and identifying patterns over time. All in all, data warehousing plays a crucial role in enabling organizations to leverage their data to gain competitive advantages and make data-driven decisions.

10 Benefits of Data Warehousing

1. Better decision-making: With data warehousing, companies can collect, consolidate and analyze data from multiple sources to make informed decisions.
2. Faster access to data: With data warehousing, companies have quick access to large amounts of data, allowing them to respond more quickly to changing market conditions.
3. Increased efficiency: Data warehousing can help streamline processes and automate data management, leading to greater efficiency and lower costs.
4. Improved data quality: Data warehousing can help ensure data accuracy and consistency by consolidating data from different sources and applying standardized rules.
5. Better customer insight: Data warehousing can help companies better understand their customers by consolidating data from various sources, including sales, marketing and customer service.
6. Better business performance: By providing better insights into business performance, data warehousing can help companies optimize their operations and improve their bottom line.
7. Better collaboration: Data warehousing can facilitate collaboration between teams by providing a central repository of data that can be accessed by multiple users.
8. Greater flexibility: With data warehousing, companies can respond quickly to changing market conditions and adapt to new trends and technologies.
9. Better regulatory compliance: Data warehousing can help companies comply with regulatory requirements by ensuring data accuracy, consistency and security.
10. Better competitive advantage: By providing better insights into customer behavior, market trends and business performance, data warehousing can help companies gain a competitive advantage and stay ahead of the competition.

Here's how Data Warehousing can help your business

Data warehousing can help companies in several ways. By consolidating data from different sources, companies can gain a more complete picture of their operations, customers and market trends. This allows them to make more informed decisions, identify growth opportunities and optimize their operations.

Data warehousing can also improve data quality and consistency. With a central repository for data, companies can ensure that all users have access to the same information, reducing the likelihood of errors or inconsistencies. This can lead to better decision-making and more accurate reporting.

Data warehousing can also improve the speed and efficiency of data analysis. With a data warehouse, companies can run complex queries on large data sets without affecting the performance of transactional systems. This allows them to quickly identify trends, detect anomalies and create predictive models.

Finally, data warehousing can give companies a competitive advantage. By better leveraging their data, companies can identify new growth opportunities, improve the customer experience and optimize their operations. This can lead to higher revenues, lower costs and increased profitability.

Data Warehousing training

Courses for Data Warehousing are suitable for any IT professional, whether private or business. According to your already acquired training and knowledge, you choose which Data Warehousing training course you start with, or continue with. Do you need advice? Then we are at your service via phone, chat and email.

For each online training course purchased, you have 1 year of access. 24 hours a day, 7 days a week for up to 365 days. So you decide when and how long you learn for the training. Is the daytime not convenient? The evening and night are available to you. Even if you go on vacation for a few weeks, this is no problem and you simply pick it up again after your well-deserved vacation.

Data Warehousing certifications

Data Warehousing certifications are specialized programs that provide knowledge and skills in designing, implementing and managing data warehouses. The certifications cover a wide range of topics, including data modeling, ETL (extract, transform, load) processes, data architecture, data quality, data security and data analytics.

• IBM Certified Solution Designer - InfoSphere DataStage v11.5
  The IBM Certified Solution Designer certification in InfoSphere DataStage v11.5 validates candidates' knowledge and skills in building and implementing DataStage projects. This certification covers topics such as project design, DataStage architecture, data modeling, data transformation and performance tuning.
• Microsoft Certified: Azure Data Engineer Associate
  The Microsoft Certified: Azure Data Engineer Associate certification is designed for data engineers who design and implement Azure data solutions. This certification validates skills in designing data storage solutions, data processing solutions and data security solutions in Azure.
• Oracle Certified Professional, Oracle Database 12c: Data Warehousing
  The Oracle Certified Professional certification in Data Warehousing validates candidates' skills in designing, implementing and managing Oracle data warehousing solutions. This certification covers topics such as data modeling, data integration, performance tuning and security in Oracle data warehousing.
• SAP Certified Application Associate - SAP BW/4HANA 2.0
  The SAP Certified Application Associate certification in SAP BW/4HANA 2.0 validates candidates' knowledge in designing and implementing SAP data warehousing solutions. This certification covers topics such as data modeling, data provisioning, data transformation and performance optimization in SAP BW/4HANA.
• SAS Certified Data Integration Developer for SAS 9
  The SAS Certified Data Integration Developer for SAS 9 certification validates candidates' skills in designing and implementing SAS data integration solutions. This certification covers topics such as data integration development, data transformation, data cleansing and metadata management in SAS.
• Teradata Certified Professional Program - Data Warehousing
  The Teradata Certified Professional Program in Data Warehousing validates candidates' skills in designing, developing and implementing Teradata data warehousing solutions. This certification covers topics such as data modeling, data integration, performance tuning and security in Teradata.
• Informatica Certified Professional - Data Integration
  The Informatica Certified Professional certification in Data Integration validates candidates' skills in designing and implementing Informatica data integration solutions. This certification covers topics such as data integration development, data transformation, data quality and metadata management in Informatica.
• AWS Certified Big Data - Speciality
  The AWS Certified Big Data - Specialty certification validates candidates' skills in designing and implementing big data solutions on the AWS platform. This certification covers topics such as data collection, data storage, data processing and data analytics in AWS.
• Google Cloud Certified - Professional Data Engineer
  The Google Cloud Certified - Professional Data Engineer certification validates candidates' skills in designing and implementing data solutions on the Google Cloud Platform. This certification covers topics such as data modeling, data ingestion, data processing and data analysis in Google Cloud.
• Cloudera Certified Data Analyst (CCA Data Analyst)
  The Cloudera Certified Data Analyst (CCA Data Analyst) certification validates candidates' skills in analyzing data in Cloudera environments using Hive and Impala. This certification covers topics such as data ingestion, data transformation, data analysis and performance tuning in Cloudera.

Each of these ICT certifications cover a range of topics related to data warehousing, such as data modeling, data integration, data management and data analytics. These certifications can help professionals demonstrate their expertise in data warehousing and enhance their value to potential employers. In addition, many of these certifications are vendor-specific, meaning they are focused on a particular software or platform, giving professionals a competitive advantage in the job market.

Jobs and careers related Data Warehousing certifications

Data Warehousing is a crucial aspect of modern businesses, and people with certifications in this field have a wealth of job opportunities. Here are some jobs and career paths available to people with Data Warehousing certifications:

• Data Warehouse Developer: A Data Warehouse Developer is responsible for designing, developing and implementing data warehousing solutions. They work closely with stakeholders to identify data requirements and develop data models to support business processes.
• ETL Developer: ETL (Extract, Transform, Load) Developers are responsible for building and maintaining the ETL processes that move data from source systems to data warehouses. They are responsible for ensuring data quality and accuracy throughout the process.
• Business Intelligence Analyst: A Business Intelligence Analyst is responsible for analyzing data and producing reports, dashboards and visualizations to help business leaders make informed decisions. They work closely with stakeholders to identify data requirements and develop data models to support business processes.
• Data Scientist: A Data Scientist is responsible for designing and implementing machine learning models to analyze large data sets. They use statistical analysis and data visualization techniques to identify patterns and trends in data that can be used to inform business decisions.
• Database Administrator: A Database Administrator is responsible for managing the storage, security and integrity of data in a data warehouse. They work closely with developers and stakeholders to ensure that the data warehouse is optimized for performance and scalability.
• Data Architect: A Data Architect is responsible for designing and developing the data architecture for an organization. They work closely with stakeholders to identify data requirements and develop data models to support business processes.
• Big Data Engineer: A Big Data Engineer is responsible for designing and developing solutions for storing and analyzing large data sets. They work with stakeholders to identify data requirements and develop data models to support business processes.
• Data Analyst: A Data Analyst is responsible for analyzing data and producing reports, dashboards and visualizations to help business leaders make informed decisions. They work closely with stakeholders to identify data requirements and develop data models to support business processes.
• Solution Architect: A Solution Architect is responsible for designing and developing end-to-end solutions for an organization. They work closely with stakeholders to identify business requirements and develop solutions that meet those requirements.
• Project Manager: A Project Manager is responsible for managing the development of data warehousing solutions. They work closely with stakeholders to identify project requirements, develop project plans and manage the project to completion.

ICT professionals with a degree in Data Warehousing can expect a wide range of jobs in various industries, including healthcare, finance, retail and more. The skills and knowledge gained from these certifications are extremely valuable in today's data-driven world and can lead to a rewarding and lucrative career.

History of Data Warehousing

The concept of data warehousing dates back to the 1980s, when companies began collecting and storing large amounts of data in centralized databases for analysis. However, the term "data warehousing" was first coined by Bill Inmon in the early 1990s, who is widely considered the father of data warehousing. Inmon defined a data warehouse as a "subject-oriented, integrated, time-variant and non-volatile collection of data to support the management decision-making process."

Data warehousing used to be a complex and expensive process, requiring significant investments in hardware, software and personnel. However, technological advances and the widespread adoption of the Internet have made data warehousing more accessible and affordable to organizations of all sizes.

Today, data warehousing is an essential part of modern business intelligence and analytics, enabling organizations to extract insights from their vast amounts of data. Data warehousing has evolved to include various technologies and techniques, such as ETL (Extract, Transform, Load) tools, data modeling, data mining and data visualization.

As the volume and complexity of data continues to increase, the importance of data warehousing is expected to grow. Companies need to efficiently store, manage and analyze their data to make informed decisions, optimize operations and gain a competitive advantage. Thus, data warehousing is an essential component of modern data-driven businesses.

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