Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the DP-203T00 Data Engineering on Microsoft Azure course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 1 Days 6 CPD hours This course is intended for The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies. Job role: Data Analyst, Data Engineer, Data Scientist Overview Describe end-to-end analytics in Microsoft Fabric Describe core features and capabilities of lakehouses in Microsoft Fabric Create a lakehouse Ingest data into files and tables in a lakehouse Query lakehouse tables with SQL Configure Spark in a Microsoft Fabric workspace Identify suitable scenarios for Spark notebooks and Spark jobs Use Spark dataframes to analyze and transform data Use Spark SQL to query data in tables and views Visualize data in a Spark notebook Understand Delta Lake and delta tables in Microsoft Fabric Create and manage delta tables using Spark Use Spark to query and transform data in delta tables Use delta tables with Spark structured streaming Describe Dataflow (Gen2) capabilities in Microsoft Fabric Create Dataflow (Gen2) solutions to ingest and transform data Include a Dataflow (Gen2) in a pipeline This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric. Introduction to end-to-end analytics using Microsoft Fabric Explore end-to-end analytics with Microsoft Fabric Data teams and Microsoft Fabric Enable and use Microsoft Fabric Knowledge Check Get started with lakehouses in Microsoft Fabric Explore the Microsoft Fabric Lakehouse Work with Microsoft Fabric Lakehouses Exercise - Create and ingest data with a Microsoft Fabric Lakehouse Use Apache Spark in Microsoft Fabric Prepare to use Apache Spark Run Spark code Work with data in a Spark dataframe Work with data using Spark SQL Visualize data in a Spark notebook Exercise - Analyze data with Apache Spark Work with Delta Lake Tables in Microsoft Fabric Understand Delta Lake Create delta tables Work with delta tables in Spark Use delta tables with streaming data Exercise - Use delta tables in Apache Spark Ingest Data with DataFlows Gen2 in Microsoft Fabric Understand Dataflows (Gen2) in Microsoft Fabric Explore Dataflows (Gen2) in Microsoft Fabric Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric Exercise - Create and use a Dataflow (Gen2) in Microsoft Fabric
his course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. These concepts are daily used by programmers and is your first step to working as a programmer. By the end, you'll be comfortable in programming Python code. You will have done small projects. This will serve for you as examples and samples that you can use to build larger projects.
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Master R for data science and machine learning applications in various industries. Develop advanced Excel skills, including data analytics and pivot table expertise. Acquire hands-on experience with Tableau for effective data visualisation. Learn Python programming essentials for data analysis and engineering solutions. Understand Google Data Studio to create dynamic reports and dashboards. Why Choose Our Data Engineering Course? FREE Data Engineering certificate accredited Get a free student ID card with Data Engineering Training Get instant access to this Data Engineering course. Learn Data Engineering from anywhere in the world The Data Engineering is affordable and simple to understand The Data Engineering is an entirely online, interactive lesson with voiceover audio Lifetime access to the Data Engineering course materials The Data Engineering comes with 24/7 tutor support Start your learning journey straightaway with our Data Engineering Bundle! This Data Engineering bundle will equip you with the skills and knowledge to become a data-savvy civil engineer. You will learn how to collect, analyze, and interpret data to improve infrastructure projects and processes. This Data Engineering bundle includes courses on data analysis, data science, machine learning, SQL programming, Excel pivot tables, Excel data analytics, Python for data analysis, Google Data Studio, business intelligence, data mining, GDPR data protection, JavaScript functions for data analysts, and Python programming. Assessment Process of Data Engineering Once you have completed all the courses in the Data Engineering bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Engineering bundle is suitable for everyone. Also, our Data Engineering Bundle is perfect for: Aspiring data engineers Business intelligence analysts Data-driven marketers IT professionals Statistics enthusiasts Career changers Requirements You will not need any prior background or expertise in the Data Engineering Bundle. Career path This Data Engineering bundle will allow you to kickstart or take your career to the next stage in the related sector such as: Data Analyst BI Developer ML Engineer Data Scientist Database Administrator Data Strategist Certificates CPD Accredited Digital Certificate Digital certificate - Included CPD Accredited Hard Copy Certificate Hard copy certificate - Included If you are an international student, then you have to pay an additional 10 GBP for each certificate as an international delivery charge.
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Here's what you get: Step by step Data Engineering Advanced Diploma lessons One to one assistance from Data Engineering Advanced Diplomaprofessionals if you need it Innovative exams to test your knowledge after the Data Engineering Advanced Diplomacourse 24/7 customer support should you encounter any hiccups Top-class learning portal Unlimited lifetime access to all twenty-five Data Engineering Advanced Diploma courses Digital Certificate, Transcript and student ID are all included in the price PDF certificate immediately after passing Original copies of your Data Engineering Advanced Diploma certificate and transcript on the next working day Easily learn the Data Engineering Advanced Diploma skills and knowledge you want from the comfort of your home CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Engineering Advanced Diploma training is suitable for - Students Recent graduates Job Seekers Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Data Engineering Advanced Diploma Requirements To participate in this Data Engineering Advanced Diploma course, all you need is - A smart device A secure internet connection And a keen interest in Data Engineering Advanced Diploma Career path You will be able to kickstart your Data Engineering Advanced Diploma career because this course includes various courses as a bonus. This Data Engineering Advanced Diploma is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Data Engineering Advanced Diploma career opportunities. Certificates CPD Accredited Certificate Digital certificate - Included CPD Accredited e-Certificate - Free CPD Accredited Hardcopy Certificate - Free Enrolment Letter - Free Student ID Card - Free
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Duration 5 Days 30 CPD hours Overview Mining data Manipulating data Visualizing and reporting data Applying basic statistical methods Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. 1 - Identifying Basic Concepts of Data Schemas Identify Relational and Non-Relational Databases Understand the Way We Use Tables, Primary Keys, and Normalization 2 - Understanding Different Data Systems Describe Types of Data Processing and Storage Systems Explain How Data Changes 3 - Understanding Types and Characteristics of Data Understand Types of Data Break Down the Field Data Types 4 - Comparing and Contrasting Different Data Structures, Formats, and Markup Languages Differentiate between Structured Data and Unstructured Data Recognize Different File Formats Understand the Different Code Languages Used for Data 5 - Explaining Data Integration and Collection Methods Understand the Processes of Extracting, Transforming, and Loading Data Explain API/Web Scraping and Other Collection Methods Collect and Use Public and Publicly-Available Data Use and Collect Survey Data 6 - Identifying Common Reasons for Cleansing and Profiling Data Learn to Profile Data Address Redundant, Duplicated, and Unnecessary Data Work with Missing Value Address Invalid Data Convert Data to Meet Specifications 7 - Executing Different Data Manipulation Techniques Manipulate Field Data and Create Variables Transpose and Append Data Query Data 8 - Explaining Common Techniques for Data Manipulation and Optimization Use Functions to Manipulate Data Use Common Techniques for Query Optimization 9 - Applying Descriptive Statistical Methods Use Measures of Central Tendency Use Measures of Dispersion Use Frequency and Percentages 10 - Describing Key Analysis Techniques Get Started with Analysis Recognize Types of Analysis 11 - Understanding the Use of Different Statistical Methods Understand the Importance of Statistical Tests Break Down the Hypothesis Test Understand Tests and Methods to Determine Relationships Between Variables 12 - Using the Appropriate Type of Visualization Use Basic Visuals Build Advanced Visuals Build Maps with Geographical Data Use Visuals to Tell a Story 13 - Expressing Business Requirements in a Report Format Consider Audience Needs When Developing a Report Describe Data Source Considerations For Reporting Describe Considerations for Delivering Reports and Dashboards Develop Reports or Dashboards Understand Ways to Sort and Filter Data 14 - Designing Components for Reports and Dashboards Design Elements for Reports and Dashboards Utilize Standard Elements Creating a Narrative and Other Written Elements Understand Deployment Considerations 15 - Understand Deployment Considerations Understand How Updates and Timing Affect Reporting Differentiate Between Types of Reports 16 - Summarizing the Importance of Data Governance Define Data Governance Understand Access Requirements and Policies Understand Security Requirements Understand Entity Relationship Requirements 17 - Applying Quality Control to Data Describe Characteristics, Rules, and Metrics of Data Quality Identify Reasons to Quality Check Data and Methods of Data Validation 18 - Explaining Master Data Management Concepts Explain the Basics of Master Data Management Describe Master Data Management Processes Additional course details: Nexus Humans CompTIA Data Plus (DA0-001) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the CompTIA Data Plus (DA0-001) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support | All-Inclusive Cost
The comprehensive Diploma in Data Engineering with Google BigQuery & Google Cloud has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Diploma in Data Engineering with Google BigQuery & Google Cloud today, and learn from the very best the industry has to offer! This best selling Diploma in Data Engineering with Google BigQuery & Google Cloud has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Diploma in Data Engineering with Google BigQuery & Google Cloud is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Diploma in Data Engineering with Google BigQuery & Google Cloud is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Diploma in Data Engineering with Google BigQuery & Google Cloud is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Diploma in Data Engineering with Google BigQuery & Google Cloud, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Diploma in Data Engineering with Google BigQuery & Google Cloud will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Diploma in Data Engineering with Google BigQuery & Google Cloud to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.