6. AnalyzeStore
Amazon
Glacier
Amazon
S3
Amazon Dyna
moDB
Amazon RDS,
Aurora
AWS 빅데이터 포트폴리오 – 신규 서비스
AWS Data Pipeli
ne
Amazon CloudS
earch
Amazon E
MR
Amazon EC2
Amazon
Redshift
Amazon M
achine
Learning
AWS Database Mi
gration Service
New
Amazon Ki
nesis Fireh
ose
New
AWS Import/Expo
rt
AWS Direct Conne
ct
Collect
Amazon Kinesis Amazon
QuickSight
New
Amazon Elastics
earch
Launched
Amazon
Kinesis Analyti
cs
New
8. 너무나 많은 데이터
누가 우리의 가장 중요한 고객이고, 무엇을 사고 있지?
지금 어떤 장비들을 교체해야 하지?
지역별 우리 제품의 수익률은?
왜 가장 수익이 많이 나는 지역이 성장하지 않지?
얼마나 많은 재고들을 가지고 있지?
가짜 계정에 대한 비용이 증가하고 있나?
마케팅 켐페인은 어떻게 진행되고 있지?
직원들의 만족도는 어떻게 변하고 있지?
너무나 많고 많은 질문들
약간의 통찰력
9. 예전의 BI 솔루션
너무 많은 비용
Pay $ million before seeing first analysis
3 year TCO $150 to $250 per user per mont
h
너무 오래 걸림
Spend 6 to 12 months of consulting a
nd SW implementation time
10. Can’t handle NoSQL, Streaming Data
시간
비용
라이센스 및 하드웨어에 수십억원을
6~12개월의 컨설팅 필요
규모에 비해 느린 성능
빠른 쿼리 성능을 보장하지 않음
Extra $$ For Mobile and Sharing
Extra $$ For IoT Dashboards
예전의 BI 솔루션
12. AnalyzeStore
Amazon
Glacier
Amazon
S3
Amazon Dyna
moDB
Amazon RDS,
Aurora
AWS 빅데이터 포트폴리오 – 신규 서비스
AWS Data Pipeli
ne
Amazon CloudS
earch
Amazon E
MR
Amazon EC2
Amazon
Redshift
Amazon M
achine
Learning
AWS Database Mi
gration Service
New
Amazon Ki
nesis Fireh
ose
New
AWS Import/Expo
rt
AWS Direct Conne
ct
Collect
Amazon Kinesis Amazon
QuickSight
New
Amazon Elastics
earch
Launched
Amazon
Kinesis Analyti
cs
New
17. Business User
QuickSight API
Data Prep Metadata SuggestionsConnectors SPICE
Business User
QuickSight UI
Mobile Devices Web Browsers
Partner BI products
Amazon
S3
Amazon Kine
sis
Amazon Dynam
oDB
Amazon
EMR
Amazon
Redshift
Amazon RDSFiles Third-party
18. • AWS 내 데이터의 손쉬운 탐색
• SPICE를 통한 빠른 통찰력
• 직관적인 시각화 및 전환 (AutoGraph)
• 네이티브 모바일 경험
• 안전한 공유 및 협업 (StoryBoard)
혁신
21. • 안전하게 검색하고 AWS 데이터에 연결
• 신속하게 AWS 데이터 소스를 탐색
• Relational databases (Amazon RDS, Amazon RDS for Aurora,
Amazon Redshift)
• NoSQL databases (Amazon DynamoDB)
• Amazon EMR, Amazon S3, files (CSV, Excel, TSV, XLF, CLF)
• Streaming data sources (Amazon DynamoDB, Amazon Kinesis)
• 테이블이나 파일에서 데이터를 쉽게 임포트
• 데이터 유형 자동 감지
AWS 내 데이터의 손쉬운 탐색
22. • Super-fast, Parallel, In-memory optimized, Calculation Engine
• 2배 ~ 4배 압축된 columnar data
• 머신 코드로 생성된 컴파일된 쿼리
• 질 높은 계산
• SQL 과 유사한 구문
• 쿼리에 대한 매우 빠른 응답시간
• 관리형 서비스 – 하드웨어와 소프트웨어 라이센스 고민 불필요
SPICE를 통한 빠른 통찰력
23. • 데이터 유형 자동 감지
• 최적의 쿼리 생성
• 적절한 그래프 유형 선택
• 그래프 유형 커스터마이징 가능
• 매우 빠른 응답
AutoGraph를 통한 직관적인 시각화
This is the AWS Big Data portfolio. We have tools like Direct Connect and Import Export that can bring in a lot of data. We can persist that data into a number of storage services from S3 to DynamoDB to EMR and RedShift for further analysis.
Amazon Redshift provides a fast, fully managed, petabyte-scale data warehouse for less than $1000 per terabyte per year. Amazon Elastic MapReduce provides a managed, easy to use analytics platform built around the powerful Hadoop framework. Recently we announced Amazon Kinesis, a managed service for real-time processing of streaming big data. Amazon Glacier allows you to backup and archive an unlimited amount of data at just 1 cent per GB per month. Automate and schedule big data processing workloads with Data Pipeline.
The tools to support big data collection, computation along with collaboration and sharing are all available in a couple of clicks, with AWS.
This is the AWS Big Data portfolio. We have tools like Direct Connect and Import Export that can bring in a lot of data. We can persist that data into a number of storage services from S3 to DynamoDB to EMR and RedShift for further analysis.
Amazon Redshift provides a fast, fully managed, petabyte-scale data warehouse for less than $1000 per terabyte per year. Amazon Elastic MapReduce provides a managed, easy to use analytics platform built around the powerful Hadoop framework. Recently we announced Amazon Kinesis, a managed service for real-time processing of streaming big data. Amazon Glacier allows you to backup and archive an unlimited amount of data at just 1 cent per GB per month. Automate and schedule big data processing workloads with Data Pipeline.
The tools to support big data collection, computation along with collaboration and sharing are all available in a couple of clicks, with AWS.
Just leave 4 questions
Takes too long
Costs too much
GB Scale deployments
This is the AWS Big Data portfolio. We have tools like Direct Connect and Import Export that can bring in a lot of data. We can persist that data into a number of storage services from S3 to DynamoDB to EMR and RedShift for further analysis.
Amazon Redshift provides a fast, fully managed, petabyte-scale data warehouse for less than $1000 per terabyte per year. Amazon Elastic MapReduce provides a managed, easy to use analytics platform built around the powerful Hadoop framework. Recently we announced Amazon Kinesis, a managed service for real-time processing of streaming big data. Amazon Glacier allows you to backup and archive an unlimited amount of data at just 1 cent per GB per month. Automate and schedule big data processing workloads with Data Pipeline.
The tools to support big data collection, computation along with collaboration and sharing are all available in a couple of clicks, with AWS.
Time to first insight from months to minutes
Goes from GBs to Terabytes
Very fast response to queries
Cost down to 1/10th
Fast to get started – sign up and go