https://aws-dojo.com/videos/ Recent content in Videos on AWS Dojo Hugo -- gohugo.io en-us Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video1/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video1/ Amazon Honeycode is a new service launched by AWS. It is a fully-managed service to build mobile & web applications without writing any code. It comes with App Builder to build the applications. It also comes with automation features for the calculations, alerts and notifications. Learn how to quickly build a web / mobile application with a csv data sheet. Watch Video at Youtube https://aws-dojo.com/videos/video2/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video2/ Struggling with CSV vs. Parquet. I did little experiment in AWS. Found Parquet gives better cost performance over CSV due to low storage and less data scanned for the query. However – the query performance is almost the same. Please watch this video to see my experiment in AWS. Watch Video at Youtube https://aws-dojo.com/videos/video3/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video3/ AWS Athena ODBC driver is used to explore and visualize the data in the AWS based data lake with business intelligence tools. Watch the video to learn how to configure Athena ODBC driver and Microsoft PowerBI Desktop to access data in AWS Data Lake to create the reports. Watch Video at Youtube https://aws-dojo.com/videos/video4/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video4/ A device shadow is a JSON document that is used to store and retrieve device state information. The device shadow is associated with AWS IoT thing object. Any application or service which wants to know the device state; can access the device shadow irrespective whether the device is connected to AWS IoT or not. Shadow communications can primarily happen in two ways – MQTT Messages and API. n this video, you learn to build an application in Microsoft c# which is used to talk to AWS IoT Device Shadow Service using IoT Data APIs. https://aws-dojo.com/videos/video5/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video5/ The EventBridge Schema Registry allows to discover, create, and manage OpenAPI or JSONSchema Draft4 specification schemas for events on EventBridge. Once the schema has been created for an event, one can download code bindings for popular programming languages and use with applications. n this video, you learn to create schema in AWS EventBridge. You then generate code-binding for the schema and learn how to use it in the applications. Watch Video at Youtube https://aws-dojo.com/videos/video6/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video6/ AWS Glue DataBrew is a new visual data preparation tool that makes it easy for data analysts and data scientists to clean and normalize data to prepare it for analytics and machine learning. There are more than 250 pre-built transformations to automate data preparation tasks, all without the need to write any code. In this video, you learn to use DataBrew to process the data and also convert the processing into a job. https://aws-dojo.com/videos/video7/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video7/ AWS CloudShell is a browser-based shell to run AWS CLI. CloudShell is pre-authenticated with the logged-in console credentials. The common development and operations tools are pre-installed. CloudShell is run from the AWS console and there is no additional cost. In this video, you learn to use CloudShell in the AWS Console. Watch Video at Youtube https://aws-dojo.com/videos/video8/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video8/ AWS Data Wrangler is an open source initiative from AWS Professional Services. It extends the power of Pandas by allowing to work AWS data related services using Panda DataFrames. Once can use Python Panda and AWS Data Wrangler to build ETL with major services - Athena, Glue, Redshift, Timestream, QuickSight, CloudWatchLogs, DynamoDB, EMR, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL). In this video, you learn to use AWS Data Wrangler with AWS SageMaker Notebook and AWS Glue Job. https://aws-dojo.com/videos/video9/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video9/ Amazon Redshift data sharing enabled secure and easy to configure sharing of live data across Amazon Redshift clusters for read purposes. Data sharing improves the agility of the organizations to allow instant, granular, and high-performance access to data across Amazon Redshift clusters without the need to manually copy or move it. In this video, you learn to use data sharing between Redshift Clusters. Watch Video at Youtube https://aws-dojo.com/videos/video10/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video10/ Amazon Redshift allows seamlessly data query from any database in the cluster, regardless of which database the connection is with. Cross-database queries eliminate data copies and simplify the data organization to support multiple business groups on the same cluster. Support for cross-database queries is available on Amazon Redshift RA3 node types. In this video, you learn using cross database queries in Redshift Cluster. Watch Video at Youtube https://aws-dojo.com/videos/video11/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video11/ Amazon Athena is a Serverless and interactive query service to query and analyze data in Amazon S3 using standard SQL. Amazon Athena cost depends on amount of data scanned to bring the query result. The amount of data scanned can be optimized using data partitioning and parquet format based storage. The video explain these two methods and then does a live demo to show the result of the optimization. Watch Video at Youtube https://aws-dojo.com/videos/video12/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video12/ Amazon Athena is a serverless and interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Amazon Athena Federated Query can be used to run SQL queries across data stored in relational, non-relational, object, and custom data sources. Athena uses data source connectors that run on AWS Lambda to execute federated queries. The data source connectors help connect with data sources like CloudWatch, DocumentDB, DynamoDB, HBase, JDBC data sources (like Redshift, MySql, SQL Server) etc. https://aws-dojo.com/videos/video13/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video13/ Amazon Honeycode is a new service launched by AWS. It is a fully-managed service to build mobile & web applications without writing any code. It comes with App Builder to build the applications. It also comes with automation features for the calculations, alerts and notifications. Honeycode also supports integration with other AWS Services. The video create a app from the scratch to learn fundamentals of building applications using Amazon Honeycode. https://aws-dojo.com/videos/video14/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video14/ Amazon Redshift ML facilitates to create, train, and apply machine learning models using SQL commands in Amazon Redshift. Redshift ML takes advantage of Amazon SageMaker for the machine learning. Redshift ML provides simple, optimized, and secure integration between Redshift and Amazon SageMaker. Redshift ML makes the model available as a SQL function within the Redshift data warehouse to enable prediction query in the SQL statements and reports. The video shows Amazon Redshift ML capabilities. https://aws-dojo.com/videos/video15/ Wed, 06 May 2020 09:52:48 +0200 https://aws-dojo.com/videos/video15/ Amazon RDS provides both managed and serverless relational database services for database engines like MySQL, PostgreSQL and SQL Server. AWS Lambda enables serverless compute. For many uses cases like APIs, data processing, the lambda function needs to talk to RDS databases. In this video, you learn methods to make Lambda function talk to RDS. It will use Python for the programming and MySQL, PostgreSQL as the database engine. Watch Video at Youtube