{"course":{"productid":26441,"modality":1,"active":true,"language":"de","title":"Building Data Analytics Solutions Using Amazon Redshift","productcode":"BDASAR","vendorcode":"AW","vendorname":"Amazon Web Services","fullproductcode":"AW-BDASAR","courseware":{"has_ekit":true,"has_printkit":false,"language":""},"url":"https:\/\/portal.flane.ch\/course\/amazon-bdasar","essentials":"<p>Sie sollten mindestens ein Jahr Erfahrung in der Verwaltung von Data Warehouses mitbringen und folgende Kurse vorher besucht haben:<\/p>\n<ul>\n<li>Entweder <span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/course\/amazon-awse\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>AWS Technical Essentials <span class=\"fl-prod-pcode\">(AWSE)<\/span><\/a><\/span> oder <span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/course\/amazon-awsa\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Architecting on AWS <span class=\"fl-prod-pcode\">(AWSA)<\/span><\/a><\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/course\/amazon-bdla\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Building Data Lakes on AWS <span class=\"fl-prod-pcode\">(BDLA)<\/span><\/a><\/span><\/li><\/ul>","audience":"<p>Dieser Kurs richtet sich an Data Warehouse Engineers, Data Platform Engineers, sowie Architects und Operators, die Datenanalyse-Pipelines erstellen und verwalten.<\/p>","contents":"<ul>\n<li>Module A: Overview of Data Analytics and the Data Pipeline<\/li><li>Module 1: Using Amazon Redshift in the Data Analytics Pipeline<\/li><li>Module 2: Introduction to Amazon Redshift<\/li><li>Module 3: Ingestion and Storage<\/li><li>Module 4: Processing and Optimizing Data<\/li><li>Module 5: Security and Monitoring of Amazon Redshift Clusters<\/li><li>Module 6: Designing Data Warehouse Analytics Solutions<\/li><li>Module B: Developing Modern Data Architectures on AWS<\/li><\/ul>","outline":"<h5>Module A: Overview of Data Analytics and the Data Pipeline<\/h5>\n<ul>\n<li>Data analytics use cases<\/li><li>Using the data pipeline for analytics<\/li><\/ul><h5>Module 1: Using Amazon Redshift in the Data Analytics Pipeline<\/h5>\n<ul>\n<li>Why Amazon Redshift for data warehousing?<\/li><li>Overview of Amazon Redshift<\/li><\/ul><h5>Module 2: Introduction to Amazon Redshift<\/h5>\n<ul>\n<li>Amazon Redshift architecture<\/li><li>Interactive Demo 1: Touring the Amazon Redshift console<\/li><li>Amazon Redshift features<\/li><li>Practice Lab 1: Load and query data in an Amazon Redshift cluster<\/li><\/ul><h5>Module 3: Ingestion and Storage<\/h5>\n<ul>\n<li>Ingestion<\/li><li>Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API<\/li><li>Data distribution and storage<\/li><li>Interactive Demo 3: Analyzing semi-structured data using the SUPER data type<\/li><li>Querying data in Amazon Redshift<\/li><li>Practice Lab 2: Data analytics using Amazon Redshift Spectrum<\/li><\/ul><h5>Module 4: Processing and Optimizing Data<\/h5>\n<ul>\n<li>Data transformation<\/li><li>Advanced querying<\/li><li>Practice Lab 3: Data transformation and querying in Amazon Redshift<\/li><li>Resource management<\/li><\/ul><p>\n \nInteractive Demo 4: Applying mixed workload management on Amazon Redshift\n \n<\/p>\n<ul>\n<li>Automation and optimization<\/li><li>Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster<\/li><\/ul><h5>Module 5: Security and Monitoring of Amazon Redshift Clusters<\/h5>\n<ul>\n<li>Securing the Amazon Redshift cluster<\/li><li>Monitoring and troubleshooting Amazon Redshift clusters<\/li><\/ul><h5>Module 6: Designing Data Warehouse Analytics Solutions<\/h5>\n<ul>\n<li>Data warehouse use case review<\/li><li>Activity: Designing a data warehouse analytics workflow<\/li><\/ul><h5>Module B: Developing Modern Data Architectures on AWS<\/h5>\n<ul>\n<li>Modern data architectures<\/li><\/ul>","summary":"<p>In diesem Kurs erstellen Sie eine Datenanalysel&ouml;sung mit Amazon Redshift, einem Cloud-Data-Warehouse-Dienst. Der Kurs konzentriert sich auf die Datenerfassungs-, Aufnahme-, Katalogisierungs-, Speicherungs- und Verarbeitungskomponenten der Analysepipeline. Sie lernen, Amazon Redshift in einen Data Lake zu integrieren, um sowohl Analyse- als auch Machine-Learning-Workloads zu unterst&uuml;tzen. Sie erfahren auch, wie Sie Best Practices f&uuml;r Sicherheit, Leistung und Kostenmanagement auf den Betrieb von Amazon Redshift anwenden.<\/p>\n<p>Dieser Kurs umfasst Pr&auml;sentationen, interaktive Demos, Labs, Diskussionen und &Uuml;bungen.<\/p>","essentials_plain":"Sie sollten mindestens ein Jahr Erfahrung in der Verwaltung von Data Warehouses mitbringen und folgende Kurse vorher besucht haben:\n\n\n- Entweder AWS Technical Essentials (AWSE) oder Architecting on AWS (AWSA)\n- Building Data Lakes on AWS (BDLA)","audience_plain":"Dieser Kurs richtet sich an Data Warehouse Engineers, Data Platform Engineers, sowie Architects und Operators, die Datenanalyse-Pipelines erstellen und verwalten.","contents_plain":"- Module A: Overview of Data Analytics and the Data Pipeline\n- Module 1: Using Amazon Redshift in the Data Analytics Pipeline\n- Module 2: Introduction to Amazon Redshift\n- Module 3: Ingestion and Storage\n- Module 4: Processing and Optimizing Data\n- Module 5: Security and Monitoring of Amazon Redshift Clusters\n- Module 6: Designing Data Warehouse Analytics Solutions\n- Module B: Developing Modern Data Architectures on AWS","outline_plain":"Module A: Overview of Data Analytics and the Data Pipeline\n\n\n\n- Data analytics use cases\n- Using the data pipeline for analytics\nModule 1: Using Amazon Redshift in the Data Analytics Pipeline\n\n\n\n- Why Amazon Redshift for data warehousing?\n- Overview of Amazon Redshift\nModule 2: Introduction to Amazon Redshift\n\n\n\n- Amazon Redshift architecture\n- Interactive Demo 1: Touring the Amazon Redshift console\n- Amazon Redshift features\n- Practice Lab 1: Load and query data in an Amazon Redshift cluster\nModule 3: Ingestion and Storage\n\n\n\n- Ingestion\n- Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API\n- Data distribution and storage\n- Interactive Demo 3: Analyzing semi-structured data using the SUPER data type\n- Querying data in Amazon Redshift\n- Practice Lab 2: Data analytics using Amazon Redshift Spectrum\nModule 4: Processing and Optimizing Data\n\n\n\n- Data transformation\n- Advanced querying\n- Practice Lab 3: Data transformation and querying in Amazon Redshift\n- Resource management\n\n \nInteractive Demo 4: Applying mixed workload management on Amazon Redshift\n \n\n\n\n- Automation and optimization\n- Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster\nModule 5: Security and Monitoring of Amazon Redshift Clusters\n\n\n\n- Securing the Amazon Redshift cluster\n- Monitoring and troubleshooting Amazon Redshift clusters\nModule 6: Designing Data Warehouse Analytics Solutions\n\n\n\n- Data warehouse use case review\n- Activity: Designing a data warehouse analytics workflow\nModule B: Developing Modern Data Architectures on AWS\n\n\n\n- Modern data architectures","summary_plain":"In diesem Kurs erstellen Sie eine Datenanalysel\u00f6sung mit Amazon Redshift, einem Cloud-Data-Warehouse-Dienst. Der Kurs konzentriert sich auf die Datenerfassungs-, Aufnahme-, Katalogisierungs-, Speicherungs- und Verarbeitungskomponenten der Analysepipeline. Sie lernen, Amazon Redshift in einen Data Lake zu integrieren, um sowohl Analyse- als auch Machine-Learning-Workloads zu unterst\u00fctzen. Sie erfahren auch, wie Sie Best Practices f\u00fcr Sicherheit, Leistung und Kostenmanagement auf den Betrieb von Amazon Redshift anwenden.\n\nDieser Kurs umfasst Pr\u00e4sentationen, interaktive Demos, Labs, Diskussionen und \u00dcbungen.","skill_level":"Intermediate","version":"1.0","duration":{"unit":"d","value":1,"formatted":"1 Tag"},"pricelist":{"List Price":{"DE":{"country":"DE","currency":"EUR","taxrate":19,"price":795},"AT":{"country":"AT","currency":"EUR","taxrate":20,"price":795},"SE":{"country":"SE","currency":"EUR","taxrate":25,"price":750},"SI":{"country":"SI","currency":"EUR","taxrate":20,"price":795},"IT":{"country":"IT","currency":"EUR","taxrate":20,"price":725},"PL":{"country":"PL","currency":"PLN","taxrate":23,"price":2000},"US":{"country":"US","currency":"USD","taxrate":null,"price":675},"AE":{"country":"AE","currency":"USD","taxrate":5,"price":650},"GR":{"country":"GR","currency":"EUR","taxrate":null,"price":795},"MK":{"country":"MK","currency":"EUR","taxrate":null,"price":795},"HU":{"country":"HU","currency":"EUR","taxrate":20,"price":795},"NL":{"country":"NL","currency":"EUR","taxrate":21,"price":795},"BE":{"country":"BE","currency":"EUR","taxrate":21,"price":795},"GB":{"country":"GB","currency":"GBP","taxrate":20,"price":900},"CH":{"country":"CH","currency":"CHF","taxrate":8.1,"price":870},"CA":{"country":"CA","currency":"CAD","taxrate":null,"price":930}}},"lastchanged":"2025-08-27T17:03:23+02:00","parenturl":"https:\/\/portal.flane.ch\/swisscom\/json-courses","nexturl_course_schedule":"https:\/\/portal.flane.ch\/swisscom\/json-course-schedule\/26441","source_lang":"de","source":"https:\/\/portal.flane.ch\/swisscom\/json-course\/amazon-bdasar"}}