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  • [Thai Sub] Modernise your Data Platform - Keynote and Fireside Chat48:53

    [Thai Sub] Modernise your Data Platform - Keynote and Fireside Chat

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    AWS Dev Day Australia On-demand 2018

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  • [VN Sub] Modernise your Data Platform - Keynote and Fireside Chat48:52

    [VN Sub] Modernise your Data Platform - Keynote and Fireside Chat

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  •  AWS Data, Databases, and Analytics Online Series_Data Flywheel Video ID1:23

    AWS Data, Databases, and Analytics Online Series_Data Flywheel Video ID

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  • Modernise your Data Platform - English for Uberflip48:52

    Modernise your Data Platform - English for Uberflip

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  • Turn Data into Insights - Thai Subs for Uberflip51:55

    Turn Data into Insights - Thai Subs for Uberflip

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  • 자동화된 기계 학습 예측 모델 구성과 손쉬운 데이터 시각화 기법33:30

    자동화된 기계 학습 예측 모델 구성과 손쉬운 데이터 시각화 기법

    문곤수, AWS AI / ML Specialist Solutions Architect 현대적 데이터 분석기법 중 기계 학습을 통해 데이터 통찰력을 얻는 것은 매우 중요합니다. 본 세션에서는 고객 이탈 데이터를 Amazon SageMaker Autopilot을 통해 손쉽게 기계학습 모델을 생성 한 후, 여기서 나온 예측 데이터를 Quicksight를 통해

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  • 데이터 웨어하우스(DW) 고도화를 위한 클라우드 기술과 이전 전략24:00

    데이터 웨어하우스(DW) 고도화를 위한 클라우드 기술과 이전 전략

    김윤건, AWS Data and Analytics Business Development Manager 전통적인 DW 환경을 넘어서 데이터 저장 위치와 포맷에 관계 없이 최소시간으로 비용 효율적으로 분석할 수 있는 클라우드 기반 'Lake House'가 주목받고 있습니다. 본 세션에서는 레이크 하우스 아키텍처를 강화하여 데이터 레이크와 데이터베이스, DW를

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  • Turn Data into Insights - English for Uberflip51:58

    Turn Data into Insights - English for Uberflip

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  • 빠르고 손쉽게 클라우드 기반 데이터 분석 시작하기37:36

    빠르고 손쉽게 클라우드 기반 데이터 분석 시작하기

    정세웅, AWS Analytics Specialist Solutions Architect 클라우드를 통해 누구나 손쉽게 데이터 분석에 참여할 수 있습니다. 개발자가 아니더라도 Amazon S3 데이터레이크에 저장된 데이터를 Athena를 통해 익숙한 SQL문으로 빠르고 질의할 수 있습니다. 이에 대한 결과를 Quicksight를 통해 다양한 보고서, 대시

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  •  데알못을 위한 데이터레이크(Data Lake) 구성 및 관리하기29:02

    데알못을 위한 데이터레이크(Data Lake) 구성 및 관리하기

    윤석찬, AWS 수석 테크에반젤리스트 현대적 데이터 분석과 기계 학습을 위한 통찰을 얻기 위해서는 대용량 데이터의 일관적 수집 및 저장이 필수적입니다. 데이터 레이크는 클라우드가 가져온 큰 혜택 중 하나로서, 원본 데이터를 빠르고 체계적으로 분류하고 수집 및 보호할 수 있습니다. 본 세션에서는 "데이터 늪"이 발생하지 않도록, Amazon Kinesis

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  • Purpose-built databases: Choose the right tool for each job (Level 200)33:02

    Purpose-built databases: Choose the right tool for each job (Level 200)

    Seldom can one database fit the needs of multiple distinct use cases. The days of the one-size-fits-all monolithic database are behind us and highly distributed applications are using many purpose-bui

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  • Embedding analytics into applications with Amazon QuickSight (Level 200)26:57

    Embedding analytics into applications with Amazon QuickSight (Level 200)

    Users need reports, visualizations, and insights quickly, so they can act immediately when unusual business events occur. In this session, learn how to easily enhance your applications with rich, inte

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  • Unite streaming and batch analytics with AWS Glue (Level 300)22:24

    Unite streaming and batch analytics with AWS Glue (Level 300)

    When processing data with velocity, there is usually a delay between the point when data is collected and its availability in reports and dashboards. Often the delay results in the need to validate or

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  • Building scalable, secure log analytics with Amazon Elasticsearch Service (Level 200)31:11

    Building scalable, secure log analytics with Amazon Elasticsearch Service (Level 200)

    You have servers, you have applications, and you have microservices. This inevitably means that you also have logs. They are not the most exciting data that your systems generate, but many times, they

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  • Building data integration services for real-time on AWS (Level 200)28:21

    Building data integration services for real-time on AWS (Level 200)

    For many use cases timing is critical and the value of data diminishes rapidly. This means that every micro-second counts. In this session, learn how we provide customers with fully managed streaming

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  • Data warehousing on AWS: Amazon Redshift use cases and deployment patterns (Level 200)30:59

    Data warehousing on AWS: Amazon Redshift use cases and deployment patterns (Level 200)

    The amount of data generated by IoT, smart devices, cloud applications, and social is growing exponentially. You need ways to easily and cost-effectively analyze all of this data with minimal time-to-

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  • Building modern application with modern databases (Level 300)17:18

    Building modern application with modern databases (Level 300)

    Applications today require databases with unlimited scale that respond quicker than ever before. Applications such as those use for ecommerce and social media applications and connected devices need m

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  • Migrate your on-premises data warehouse to Amazon Redshift (Level 200)26:34

    Migrate your on-premises data warehouse to Amazon Redshift (Level 200)

    Most companies are over-run with data, yet they lack critical insights to make timely and accurate business decisions due to cost, complexity, and rigid architectures of traditional data warehouses. T

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  •  Accelerating data analytics with cloud-native file storage (Level 300)25:07

    Accelerating data analytics with cloud-native file storage (Level 300)

    Building analytics practices into a core competency is critical for modern businesses and a core tenet of a digital innovation strategy. Many data scientists require a shared workspace to foster colla

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