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We're here to help you find itThe Microsoft Cloud Workshop - Modernizing Data Analytics with SQL Server 2019 (40565) certification provides a better understanding of how to transform business operations by using SQL Server 2019. It provides insights into how to leverage data analytics, machine learning, and the latest SQL server tools for modernizing data infrastructure. The certification helps individuals and industries manage, process, and analyze large volumes of data in real-time to aid in business intelligence, strategy development, and decision-making. It enhances skills in designing, implementing, and maintaining complex data architecture systems, offering a significant advantage in the data-driven aspects of various industries, such as IT, healthcare, finance, and more.
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Classroom Training price is on request
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♱ Excluding VAT/GST
Classroom Training price is on request
You can request classroom training in any city on any date by Requesting More Information
There is no specific course prerequisite listed for the Modernizing Data Analytics with SQL Server 2019 - Microsoft Cloud Workshop (40565) training. However, to get the most out of the training, participants should have:
1. A basic understanding of SQL Server features and technologies like SQL Server, Hadoop, and the PolyBase feature in SQL Server.
2. Experience in designing and managing SQL Server databases.
3. Familiarity with the Microsoft Azure platform, especially Azure storage options, and Azure Virtual Machines.
4. Knowledge of SQL Server Analysis Services (SSAS) and SQL Server Integration Services (SSIS).
It is recommended for IT professionals, database architects, data engineers, and technical decision-makers who want to modernize data analytics with SQL Server 2019.
The Microsoft Cloud Workshop (40565) certification training focuses on modernizing data analytics with SQL Server 2019. The course covers essential topics such as deploying and configuring SQL Server 2019 Big Data Clusters, utilizing data virtualization, implementing data lakes and scalable data processing, and integrating machine learning services. Through hands-on labs and practice sessions, participants acquire valuable skills needed for tackling challenges in data management and advanced analytics while effectively utilizing the capabilities of SQL Server 2019.
Learning Modernizing Data Analytics with SQL Server 2019 - Microsoft Cloud Workshop(40565) empowers you to leverage the latest SQL Server technologies for fast, effective data analytics. This course enhances your data management skills, boosts your ability to handle complex datasets, and improve business decision-making, ultimately opening doors for future career growth in the data analytics domain.
SQL Server 2019 is a relational database management system developed by Microsoft. It builds on previous versions by enhancing performance, providing more security features, and allowing better integration with other systems. A key aspect of SQL Server 2019 is its support for big data clusters, which lets users manage big data environments for large-scale analytics and computational tasks. It also supports a variety of programming languages and data types, facilitating a flexible development environment. SQL Server 2019 Management Studio is the main tool used for configuring, managing, and administering all components within Microsoft SQL Server.
Data analytics involves examining raw data to find trends and answer questions. The ultimate aim is to harness this information to make informed decisions. By using various tools and methods, analysts can gather insights from both historical and real-time data. This process requires techniques and software capable of managing and analyzing large datasets. SQL (Structured Query Language) is commonly used for this purpose, enabling the manipulation and retrieval of data stored in relational databases. Improving business strategies, customer satisfaction, and operational efficiency are just a few benefits driven by data analytics.
Machine learning is a branch of artificial intelligence that allows computers to learn and make decisions without being explicitly programmed. It involves feeding data into algorithms, which then analyze and learn from the data, improving their performance over time. This leads to machines that can recognize patterns, make predictions, and enhance decision-making processes across various industries, improving both efficiency and effectiveness.
Business intelligence (BI) is a technology-driven process used to analyze data and present actionable information to help executives, managers, and other corporate end users make informed business decisions. BI encompasses a variety of tools, applications, and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against the data, and create reports, dashboards, and data visualizations to make the analytical results available to corporate decision-makers as well as operational workers.
Data architecture systems are the frameworks and methodologies used to manage data across an organization. At their core, they explain how data is collected, stored, processed, and utilized. This involves defining data storage, data flow, and data usage patterns to ensure data is secure, easily accessible, and effective in supporting business processes. Effective data architecture simplifies decision-making by providing a clear structure for data environments and facilitating efficient SQL database management, such as with tools like SQL 2019 Management Studio, which help in administering, deploying, and recovering data in an organized way.
