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The DP-900T00: Microsoft Azure Data Fundamentals course is designed to introduce learners to the Core data concepts and the Azure data services that can handle a broad range of data processing and analytics needs. It targets those interested in beginning to work with data in the cloud.
Module 1 lays the foundation by exploring basic data concepts, the various data roles and responsibilities, and differentiates between relational and non-Relational data, alongside an overview of Data analytics.
Module 2 delves into Azure's Relational data services, provisioning, deployment, and querying of Relational databases, which is pivotal for managing structured data.
Module 3 shifts focus to non-Relational data offerings in Azure, demonstrating how to provision, deploy, and manage non-Relational data stores, catering to scalable and flexible Data storage needs.
Finally, Module 4 offers insights into modern data warehouse analytics, covering Data ingestion, storage, processing in Azure, and visualization with Power BI.
This course is beneficial for individuals seeking to understand data concepts and analytics, and those aiming to implement data solutions using Microsoft Azure services. It prepares learners for the DP-900 certification exam, which can enhance their professional credentials in the field of data and analytics.
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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
To ensure you have the best learning experience in the DP-900T00: Microsoft Azure Data Fundamentals course, we recommend that you possess the following minimum prerequisites:
Please note that while prior experience in these areas can be helpful, the course is designed to introduce these concepts to beginners. Therefore, a strong willingness to learn and engage with the course material is the most important prerequisite.
The DP-900T00: Microsoft Azure Data Fundamentals course is designed for individuals seeking foundational knowledge in data services within Azure.
Target audience for the DP-900T00 course includes:
Gain foundational knowledge of core data concepts, Azure data services, and the roles within the data landscape, setting the stage for deeper exploration into Azure's database solutions.
Data storage involves saving digital information within a data storage system through various ways like hard drives, SSDs, or cloud storage solutions. Crucial for preserving records and making data accessible and manageable, systems like Microsoft Azure offer structured courses and certifications to enhance understanding and skills in this arena. Professionals can opt for training like the DP-900 Microsoft course, part of the Azure data certification list, to gain in-depth knowledge about data concepts and Azure data services, ensuring they are equipped with the pertinent skills for effective data handling and storage in a variety of environments.
Data analytics involves examining raw data to uncover patterns, draw conclusions, and make informed decisions. This process can be significantly enhanced with training and certifications like the DP 900 Microsoft course, a part of the Azure data certification list. The DP 900 training and certification helps professionals understand and manage data solutions on Microsoft Azure effectively, equipping them with the necessary skills to handle large datasets, perform analytics, and generate insights. The DP 900 course is tailored to introduce and hone data analytics skills, ensuring proficiency in applying data technology in real-world scenarios.
Data ingestion is the process of moving data from various sources into a system where it can be stored, analyzed, and processed. This involves collecting data from databases, systems, or real-time streams, and importing it into a central location like a data warehouse. Subsequently, this consolidated data can be used for advanced analytics or monitoring. This process is fundamental in data management and directly supports capabilities explored in courses like the DP 900 Microsoft course as part of the Azure data certification list, helping professionals understand how to efficiently handle and utilize large sets of data.
Core data concepts are foundational ideas about organizing, storing, and managing data. They involve understanding different types of data structures, databases, and the principles of data manipulation. Essential for anyone pursuing DP 900 certification or other Azure data certifications, these concepts help in effectively handling data within various systems. Mastering them through DP 900 training or courses allows professionals to ensure data integrity, security, and accessibility in cloud environments like Microsoft Azure.
Azure data services encompass a collection of integrated cloud services that enable the handling, analysis, and storage of large amounts of data across the Microsoft Azure platform. These services support various database management systems, offer sophisticated analytics solutions, and provide comprehensive data governance tools. Whether you are looking to validate your skills through a DP 900 Microsoft course, seeking an Azure data certification list, or aiming to achieve DP 900 certification, training in Azure data services like those detailed in the DP 900 course will equip you with the necessary expertise to excel in data management and analysis on Azure.
Relational data refers to a method of structuring information in which data is organized into tables (relations), each consisting of rows (records) and columns (fields). This structure allows for easy access and management of data relationships, enabling efficient querying, updating, and administration of data using Structured Query Language (SQL). Relational databases are fundamental in many business applications, supporting data integrity and allowing for complex queries and analysis. They are widely used in managing customer information, financial records, and product inventories, forming the backbone of enterprise data systems.
Non-relational data refers to types of data that do not fit into the traditional table-based structure of relational databases. Instead, non-relational databases, also known as NoSQL databases, store data in formats like key-value pairs, document-based stores, or graphs. This flexibility allows for efficient storage and retrieval of complex or unstructured data that doesn't easily conform to the rigid schema of relational databases. Non-relational data management is increasingly popular in handling large volumes of varied data types and is a focus in fields like data science and big data analytics.
Relational data services involve managing structured data using predefined schema, commonly implemented in relational database management systems (RDBMS). They excel in handling operations with complex queries and transaction reliability, storing data in tables linked by relationships. This makes data retrieval efficient and highly organized. These services support industries needing robust data integrity and are critical for enterprise applications, ensuring data is easily accessible and manageable. For professionals looking to specialize in this field, courses like the DP 900 Microsoft course and various Azure data certifications provide comprehensive training on Microsoft's relational data technologies.
Provisioning and deployment of relational databases involve setting up and preparing database systems to manage and store structured data effectively. The process includes configuring resources like servers and storage, as well as installing database software. Deployment refers to the distribution and integration of this database setup within an existing IT environment, ensuring that it can handle required operations and scale as needed. This systematic approach helps organizations streamline data management, enhance efficiency, and support various application needs.
Querying of relational databases involves using structured commands, typically written in SQL (Structured Query Language), to retrieve or manipulate data stored in a table-based format. Users can select specific data pieces, update records, insert new data, or delete unwanted data. Effective querying helps in analyzing data, generating reports, and making data-driven decisions, ensuring efficient management and utilization of information within an organization’s database systems. This skill is crucial for managing and analyzing large sets of data efficiently.
Non-relational data stores, also known as NoSQL databases, are designed to handle large volumes of data that do not fit into traditional database schemas. Unlike relational databases that store data in rows and columns, non-relational databases use various formats like key-value pairs, documents, graphs, or wide-columns. This flexibility makes them ideal for handling big data and real-time web apps. They scale out efficiently and can manage unstructured data like social media content, videos, or large sets of real-time sensor data, supporting diverse application needs with performance at scale.
The DP-900T00: Microsoft Azure Data Fundamentals course is designed for individuals seeking foundational knowledge in data services within Azure.
Target audience for the DP-900T00 course includes:
Gain foundational knowledge of core data concepts, Azure data services, and the roles within the data landscape, setting the stage for deeper exploration into Azure's database solutions.
