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Data has gravity – The AWS
Data Management approach
Adolfo Abreu
Business Development Latam Team
Database, Big Data, Analy...
What do you know about Amazon?
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.2
Unprecedented
SC...
Amazon Web Services
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.3
Applying amazon.com concept...
Personalized
Recommendations
Fulfillment automation
& Inventory Management
Drones Voice driven
Interactions
Inventing enti...
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Analytics
Redshift
Data warehousing
EMR
Hadoop + Spark
Athena
Interactive analytics
Kinesis Data Analytics
Real time
Elast...
Analytics
QuickSight SageMaker
S3/Glacier
Glue
ETL & Data Catalog
Lake Formation
Data Lakes
Database Migration Service | S...
Redshift
Data warehousing
EMR
Hadoop + Spark
Athena
Interactive analytics
Kinesis Data
Analytics Real time
Elasticsearch S...
Quickly build new
apps in the cloud
Gain new
insights
“Lift and shift” existing
apps to the cloud
Three type of projects
Traditionally, analytics looked like this
Relational data
GBs-TBs scale [not designed for PB/EBs]
Expensive: Large initial...
Snowball
Snowmobile Kinesis
Data Firehose
Kinesis
Data Streams
S3
Redshift
EMR
Athena Kinesis
Elasticsearch Service
Data l...
How it works
S3
IAM KMS
OLTP
ERP
CRM
LOB
Devices
Web
Sensors
Social Kinesis
Build data lakes quickly
• Identify, crawl, an...
Relational Key-value Document In-memory Graph Time-series Ledger
DynamoDB NeptuneAmazon RDS
Aurora CommercialCommunity
Tim...
Amazon RDS
Managed relational database service with a choice of six popular database engines
Available & durable
Automatic...
Amazon QuickSight
First BI service with pay-per-session pricing for everyone in your organization
Serverless, cloud-powere...
AWS Directory Service
Microsoft AD
Custom Date Format Dashboard Save As Aggregate Calculations Readers Groups
Private VPC
...
Amazon QuickSight—embedded dashboards
Supercharge your applications with embedded dashboards
Fully interactive with drill ...
Discover all the hidden trends and
anomalies on millions of metrics
Amazon QuickSight—ML Insights
Example: anomaly detecti...
“Sales for office supplies in APAC was
15% above expected.”
Amazon QuickSight—ML Insights
Example: anomaly detection
“SMB Segment was the top
contributor.”
Amazon QuickSight—ML Insights
Example: anomaly detection
“It’s significant because SMB typically
only accounts for 30% of sales.”
Amazon QuickSight—ML Insights
Example: anomaly de...
QuickSight ML-powered forecasting Traditional BI forecasting
Captures seasonality and upward trends
Automatically excludes...
Insights in plain language narrative
Embedded within your dashboard
No more staring at dashboards for hours!
Fully customi...
Most enterprise database & analytics cloud customers
Most startup database & analytics cloud customers
Artificial Intelligence, Machine
Learning, Deep Learning, Data
Science #buzZZzzzWords…
?!
Artificial Intelligence
• “the science and engineering of making intelligent machines”
(John McCarthy - ~1950s)
Weak AI St...
Machine Learning
“is a field of computer science that gives computers
the ability to learn without being explicitly
progra...
Deep Learning
• “is a subarea of machine learning that uses deep neural networks to model
complex problems”
Deep	Learning
...
Autonomous cars
Object detection
Centimeter-accurate positioningReal time per pixel
image segmentation
Autonomous cars
Text to Speech
Visual Search
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Find real value in raw data streams
Customer & Industry Maturity
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Advanced
knowledge
...
§ Cross Industry Standard
Process for Data Mining
§ Current de facto process for
doing Data Science
§ Highlights the cycli...
Artificial Intelligence @ AWS
Application
Services
Platform
Services
Frameworks
& Infrastructure
Apache MXNet PyTorchCogni...
Thank you!
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.41
Big Data Analytics, Machine Learning e Inteligência Artificial
Big Data Analytics, Machine Learning e Inteligência Artificial
Big Data Analytics, Machine Learning e Inteligência Artificial
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Big Data Analytics, Machine Learning e Inteligência Artificial

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Big Data Analytics, Machine Learning e Inteligência Artificial

  1. 1. Data has gravity – The AWS Data Management approach Adolfo Abreu Business Development Latam Team Database, Big Data, Analytics, AI, ML, IoT
  2. 2. What do you know about Amazon? © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.2 Unprecedented SCALE Hyper SPEED Relentless INNOVATION Customer OBSESSION
  3. 3. Amazon Web Services © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.3 Applying amazon.com concepts to infrastructure Unprecedented SCALE Hyper SPEED Relentless INNOVATION Customer OBSESSION Infinite IT resources available in minutes 18 regions, 55 availability zones New capabilities launched daily Working Backwards from the customer PR FAQ
  4. 4. Personalized Recommendations Fulfillment automation & Inventory Management Drones Voice driven Interactions Inventing entirely new Customer experiences At Amazon, we’ve been making investments in Machine Learning for the last 20 years
  5. 5. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
  6. 6. Analytics Redshift Data warehousing EMR Hadoop + Spark Athena Interactive analytics Kinesis Data Analytics Real time Elasticsearch Service Operational Analytics QuickSight SageMaker S3/Glacier Glue ETL & Data Catalog Lake Formation Data Lakes Database Migration Service | Snowball | Snowmobile | Kinesis Data Firehose | Kinesis Data Streams Data Movement Business Intelligence & Machine Learning Data Lake Our portfolio - purpose-built for builders
  7. 7. Analytics QuickSight SageMaker S3/Glacier Glue ETL & Data Catalog Lake Formation Data Lakes Database Migration Service | Snowball | Snowmobile | Kinesis Data Firehose | Kinesis Data Streams Data Movement Business Intelligence & Machine Learning Data Lake Redshift Data warehousing EMR Hadoop + Spark Kinesis Data Analytics Real time Elasticsearch Service Operational Analytics Athena Interactive analytics RDS MySQL, PostgreSQL, MariaDB, Oracle, SQL Server Aurora MySQL, PostgreSQL DynamoDB Key value, Document ElastiCache Redis, Memcached Neptune Graph Timestream Time Series QLDB Ledger Database RDS on VMware Databases Our portfolio - purpose-built for builders
  8. 8. Redshift Data warehousing EMR Hadoop + Spark Athena Interactive analytics Kinesis Data Analytics Real time Elasticsearch Service Operational Analytics RDS MySQL, PostgreSQL, MariaDB, Oracle, SQL Server Aurora MySQL, PostgreSQL QuickSight SageMaker DynamoDB Key value, Document ElastiCache Redis, Memcached Neptune Graph Timestream Time Series QLDB Ledger Database S3/Glacier Glue ETL & Data Catalog Lake Formation Data Lakes Database Migration Service | Snowball | Snowmobile | Kinesis Data Firehose | Kinesis Data Streams Data Movement Analytics Databases Business Intelligence & Machine Learning Data Lake Managed Blockchain Blockchain Templates Blockchain RDS on VMware Our portfolio - purpose-built for builders
  9. 9. Quickly build new apps in the cloud Gain new insights “Lift and shift” existing apps to the cloud Three type of projects
  10. 10. Traditionally, analytics looked like this Relational data GBs-TBs scale [not designed for PB/EBs] Expensive: Large initial capex + $10K-$50K/TB/year 90% of data was thrown away because of cost OLTP ERP CRM LOB Data Warehouse Business Intelligence
  11. 11. Snowball Snowmobile Kinesis Data Firehose Kinesis Data Streams S3 Redshift EMR Athena Kinesis Elasticsearch Service Data lakes on AWS Kinesis Video Streams AI Services QuickSight Exabyte scale Store and analyze relational and non-relational data Purpose-built analytics tools Cost effective • Store at 2.3 cents per GB-month in Amazon S3 • Query with Amazon Athena at ½ cent per GB scanned • DW with Amazon Redshift for $1,000/TB/year Give access to everyone • Amazon QuickSight: $0.30 for 30 minutes of use
  12. 12. How it works S3 IAM KMS OLTP ERP CRM LOB Devices Web Sensors Social Kinesis Build data lakes quickly • Identify, crawl, and catalog sources • Ingest and clean data • Transform into optimal formats Simplify security management • Enforce encryption • Define access policies • Implement audit login Enable self-service and combined analytics • Analysts discover all data available for analysis from a single data catalog • Use multiple analytics tools over the same data Athena Redshift AI Services EMR QuickSight Data catalog
  13. 13. Relational Key-value Document In-memory Graph Time-series Ledger DynamoDB NeptuneAmazon RDS Aurora CommercialCommunity Timestream QLDBElastiCacheDocumentDB AWS databases services
  14. 14. Amazon RDS Managed relational database service with a choice of six popular database engines Available & durable Automatic Multi-AZ data replication; automated backup, snapshots, failover Easy to administer No need for infrastructure provisioning, installing and maintaining DB software Highly scalable Scale database compute and storage with a few clicks with no application downtime Fast & secure SSD storage and guaranteed provisioned I/O; data encryption at rest and in transit
  15. 15. Amazon QuickSight First BI service with pay-per-session pricing for everyone in your organization Serverless, cloud-powered BI service (no servers to manage) Scale from 10s of users to 100s of thousands of users Pay only for what you use • Readers: $0.30/30 min session with a $5/user/month max • Authors: $18/month/Author Integrates with S3, Athena, Redshift, RDS, Aurora, & EMR
  16. 16. AWS Directory Service Microsoft AD Custom Date Format Dashboard Save As Aggregate Calculations Readers Groups Private VPC 25 GB SPICE tables Spark and Presto Connector Scheduled refresh Just In Time Provisioning One-click upgrade Search Totals Excel Custom Range 100+ new features released since launch Federated SSO Athena connector Export to CSV S3 Analytics Week Aggregation Aurora PostgreSQL Calculations in SPICE Cross Account S3 Access Aggregate Filters Hourly refresh Row level security Hourly refresh 10K Filter Values On-screen controls Redshift Spectrum Support KPI Chart Spark Connector AWS Directory Service AD Connector Tabular Reports Data labels URL Actions Combo Charts Audit logging with CloudTrail Geospatial maps Count Distinct Parameters Relative Date Filters Filter Groups Table calculations Snowflake Connector SaaS Connectors Teradata Connector HIPAA PCI compliance Amazon QuickSight has been innovating quickly
  17. 17. Amazon QuickSight—embedded dashboards Supercharge your applications with embedded dashboards Fully interactive with drill down, filtering, & external links No servers to manage, no long-term commitments Pay for usage with pay-per-session reader pricing Easy embedding with JavaScript SDK
  18. 18. Discover all the hidden trends and anomalies on millions of metrics Amazon QuickSight—ML Insights Example: anomaly detection
  19. 19. “Sales for office supplies in APAC was 15% above expected.” Amazon QuickSight—ML Insights Example: anomaly detection
  20. 20. “SMB Segment was the top contributor.” Amazon QuickSight—ML Insights Example: anomaly detection
  21. 21. “It’s significant because SMB typically only accounts for 30% of sales.” Amazon QuickSight—ML Insights Example: anomaly detection
  22. 22. QuickSight ML-powered forecasting Traditional BI forecasting Captures seasonality and upward trends Automatically excludes bad data High confidence band Captures only seasonality Missing upward trend Confidence band influenced by bad data QuickSight ML Insights vs. traditional BI forecasting VS.
  23. 23. Insights in plain language narrative Embedded within your dashboard No more staring at dashboards for hours! Fully customizable to meet every need No coding needed. Easy-to-use UI templates. Amazon QuickSight—ML Insights Auto-narratives
  24. 24. Most enterprise database & analytics cloud customers
  25. 25. Most startup database & analytics cloud customers
  26. 26. Artificial Intelligence, Machine Learning, Deep Learning, Data Science #buzZZzzzWords… ?!
  27. 27. Artificial Intelligence • “the science and engineering of making intelligent machines” (John McCarthy - ~1950s) Weak AI Strong AI (AGI) I like artificial intelligence Lubię sztuczną inteligencję
  28. 28. Machine Learning “is a field of computer science that gives computers the ability to learn without being explicitly programmed” (Arthur Samuel - ~1959)
  29. 29. Deep Learning • “is a subarea of machine learning that uses deep neural networks to model complex problems” Deep Learning Machine Learning Artificial Intelligence
  30. 30. Autonomous cars Object detection
  31. 31. Centimeter-accurate positioningReal time per pixel image segmentation Autonomous cars
  32. 32. Text to Speech
  33. 33. Visual Search
  34. 34. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Find real value in raw data streams
  35. 35. Customer & Industry Maturity © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Advanced knowledge Basic understanding of AI/ML Low or no knowledge of AI/ML
  36. 36. § Cross Industry Standard Process for Data Mining § Current de facto process for doing Data Science § Highlights the cyclical and iterative natures of Data Science https://en.wikipedia.org/wiki/Cross_Industry_Standard_Process_for_Data_Mining Machine Learning modeling process
  37. 37. Artificial Intelligence @ AWS Application Services Platform Services Frameworks & Infrastructure Apache MXNet PyTorchCognitive Toolkit Keras Caffe2 & Caffe TensorFlow AWS Deep Learning AMI (Ubuntu & Amazon Linux – Cuda 8 & 9) GPU (P2 & P3) MobileCPU IoT (Greengrass) Amazon Machine Learning Mechanical Turk Spark & EMR Vision: Rekognition Rekognition Video Speech: Polly Transcribe Language: Lex Translate Comprehend Textract Gluon SageMaker Ground Truth RL, Neo, Pipeline DeepLens DeepRacer Marketplace Time Series: Forecast Recommendation: Personalize Elastic Inference Inferentia RoboMaker
  38. 38. Thank you! © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.41

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