Ce diaporama a bien été signalé.
Le téléchargement de votre SlideShare est en cours. ×

Better Business from Exploring Ideas - Modern Data Architectures on AWS

Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Chargement dans…3
×

Consultez-les par la suite

1 sur 32 Publicité

Better Business from Exploring Ideas - Modern Data Architectures on AWS

Télécharger pour lire hors ligne

Learn how organisations are able to drive better business outcomes from big data products and in turn, deliver personalised, real-time experiences to customers. We will walk through a common customer journey and demonstrate how to quickly test ideas and gather insights from data lakes, data pipelines, and sandboxes. See how to serve the needs of your business users, business analysts, and data scientists using AWS services for analytics, Big Data, and Machine Learning.

Speaker: Vicky Falconer, Business Development Manager - Big Data, AWS

Learn how organisations are able to drive better business outcomes from big data products and in turn, deliver personalised, real-time experiences to customers. We will walk through a common customer journey and demonstrate how to quickly test ideas and gather insights from data lakes, data pipelines, and sandboxes. See how to serve the needs of your business users, business analysts, and data scientists using AWS services for analytics, Big Data, and Machine Learning.

Speaker: Vicky Falconer, Business Development Manager - Big Data, AWS

Publicité
Publicité

Plus De Contenu Connexe

Diaporamas pour vous (20)

Similaire à Better Business from Exploring Ideas - Modern Data Architectures on AWS (20)

Publicité

Plus par Amazon Web Services (20)

Better Business from Exploring Ideas - Modern Data Architectures on AWS

  1. 1. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Vicky Falconer Business Development Manager, Big Data - Amazon Web Services Better Business From Exploring Ideas Modern Data Architectures On AWS
  2. 2. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Let’s go on a Common Customer Journey
  3. 3. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Meet AudibleEars, as they move from B2B to B2C * This case is representative of a common customer journey, but AudibleEars isn’t an actual business AudibleEars manufacturers hearing aids. They ran a traditional business since 2005, selling through distribution channels. 2005 In 2016, they launched their first “AudibleEars App”. The hearing aid comes with the AudibleEars mobile app which enables customized control of the hearing device, voice to text translation, music streaming. The device syncs with the users mobile phone via Bluetooth. The mobile app has optional GPS tracking. 2016
  4. 4. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. AudibleEars Needs To Answer New Questions And Move Faster Raymond, Head of ProductLim, Head of Finance Are customers using the new features? What is the demand forecast by product category? What is the social sentiment about our products? How do quality issues impact cost of production? Can I look at supplier performance over time? How can we reduce our inventory holding costs?
  5. 5. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. To Answer New Questions Quickly, We Look To A Modern Data Architecture Design Massive upfront costs Overprovisioned capacity Long implementation times Pay as you go, for what you use Decoupled pipelines and engines Experimentation platform Ingest/ Collect Consume/ visualise Store Process/ analyze 1 4 0 9 5
  6. 6. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Outcome 1: Modernise And Consolidate
  7. 7. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Start With A Set Of Specific Questions To Answer, Then Work Backwards To The Data Required Lim, Head of Finance How do quality issues impact cost of production? Can I look at supplier performance over time? How can we reduce our inventory holding costs? Order History / Returns (CRM) Inventory / Production (ERP)
  8. 8. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Ingest ServingData sources Modern Data Architecture Insights to enhance business applications, new digital services Transactions ERP Data analysts DATA PIPELINES Ingest/ Collect Consume / Visualise Store Process / Analyze 1 4 0 9 5
  9. 9. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Start Small and Iterate
  10. 10. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Ingest ServingData sources Modern Data Architecture Insights to enhance business applications, new digital services Transactions ERP DATA PIPELINES Data Lake expdp Data Data analysts Data Warehouse Amazon Redshift Direct Query Amazon Athena She asks for the SMALLEST amount of data to answer her questions. If it isn’t good enough, she asks for another small slice to be loaded to the DATA LAKE
  11. 11. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Redshift – Modern Data Warehousing Fast, scalable, fully managed data warehouse at 1/10th the cost Massively parallel, scales from gigabytes to exabytes Queries data across your Redshift data warehouse and Amazon S3 data lake Fast at scale Columnar storage technology to improve I/O efficiency and scale query performance Open file formats Analyze optimised data formats on direct- attached disks, and all open file formats in S3 Cost-effective Start at $0.25 per hour; as low as $250-$333 per uncompressed terabyte per year $ Secure Audit everything; encrypt data end-to-end; extensive certification and compliance
  12. 12. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Characteristics Of A Data Lake Future Proof Flexible Access Dive in Anywhere Collect Anything
  13. 13. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Start With A Set Of Specific Questions To Answer, Then Work Backwards To The Data Required Raymond, Head of Product Are customers using the new features? What is the demand forecast by product category? What is the social sentiment about our products? Trending / Mentions (Social) Order History / Returns (CRM) NOW IN THE DATA LAKE
  14. 14. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Experiment, Validate, then Scale
  15. 15. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Ingest ServingData sources Modern Data Architecture Insights to enhance business applications, new digital services DATA PIPELINES Data Lake He first looks to the DATA LAKE, and imports only the category data he needs He imports JUST ENOUGH data to see if the market is responding to products. Business users Transactions ERP Social media Data Stream Capture Amazon Kinesis Events Amazon QuickSight Data Warehouse Amazon Redshift Stream Data Amazon ElasticSearch
  16. 16. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Common Data Pipeline Configuration Raw Data Amazon S3 Highly decoupled configurations scale better, are more fault tolerant, and cost optimised ETL (Hadoop) Amazon EMR Triggered Code Amazon Lambda Staged Data (Data Lake) Amazon S3 ETL & Catalog Management AWS Glue Data Warehouse Amazon Redshift Triggered Code Amazon Lambda
  17. 17. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Data security and management Encryption Access Controls Monitoring and Metrics Audit Trails Automation Serverless Computing Data Discovery and Protection Data Visualisation Data movement Physical Appliances Hybrid Storage Private Networks File Data WAN Acceleration Third-party Applications Streaming Data Complete Set Of Building Blocks FileBlock Object Archival Storage types
  18. 18. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Ingest ServingData sources Modern Data Architecture Insights to enhance business applications, new digital services Transactions ERP Data analysts Business users DATA PIPELINES EVENT PIPELINES Data Event Insights Data Lake Social media
  19. 19. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Outcome 2: Innovate For New Insight
  20. 20. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. AudibleEars Has Its First Direct Relationship With Consumers Krzysztof, Data ScientistBala, Head of Research & Development What are our customer segments, based on usage? Can we predict changes to hearing loss from usage of the app? Can we give a better customer experience, for example optimised settings, based on signals? How are consumers using the hearing aids? When do they turn them off? How are they altering the settings throughout the day? What kinds of people are in/decreasing usage?
  21. 21. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Start With A Set Of Specific Questions To Answer, Then Work Backwards To The Data Required Media consumption (Partner API) Registration, usage [time/place] (Mobile app) Bala, Head of Research & Development How are consumers using the hearing aids? When do they turn them off? How are they altering the settings throughout the day? What kinds of people are in/decreasing usage?
  22. 22. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Start With A Set Of Specific Questions To Answer, Then Work Backwards To The Data Required Krzysztof, Data Scientist Voice to text, GPS DATA LAKE, OR NOT? Registration, usage [time/place] (Mobile app) LOAD TO DATA LAKE What are our customer segments, based on usage? Can we predict changes to hearing loss from usage of the app? Can we give a better customer experience, for example optimised settings, based on signals?
  23. 23. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Sandboxes - Fast, Cheap, Low Risk
  24. 24. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Ingest ServingData sources Transactions Data scientists Business users Connected devices DATA PIPELINES EVENT PIPELINES Data Event Insights Data Lake Sandbox ML / Analytics / DLWeb logs / clickstream Modern Data Architecture Insights to enhance business applications, new digital services
  25. 25. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Ingest ServingData sources Modern Data Architecture Innovate for new revenues - personalisation and forecasting Transactions ERP Data analysts Data scientists Business users Connected devices DATA PIPELINES EVENT PIPELINES Data Event Insights Data Lake ML / Analytics Social media Web logs / clickstream
  26. 26. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Outcome 3: Real-Time Engagement
  27. 27. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. AudibleEars Offers A Personalised Life Soundtrack Personalised, based on past preferences, people with similar behaviors, and environments detected
  28. 28. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Use AudibleEars Voice Enablement To Recommend Settings What are the best settings for watching a play? Amazon Transcribe / Comprehend Action: <RECOMMEND> Category: THEATRE Request settings HISTORY RECOMMENDATION! PEOPLE LIKE YOU Amazon Kinesis Streams Connected device data Location: <FIND GPS> Ambient Noise: <FIND Noise>
  29. 29. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Ingest ServingData sources Modern Data Architecture Real-time engagement and interactive customer experiences Transactions ERP Data analysts Data scientists Business users Engagement platformsConnected devices Automation / events DATA PIPELINES EVENT PIPELINES Data Event Action Insights Data Lake ML / Analytics Predict / Recommend AI Services Social media Web logs / clickstream
  30. 30. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Business Outcomes on a Modern Data Architecture Outcome 1 : Modernise and consolidate • Insights to enhance business applications and create new digital services Outcome 2 : Innovate for new insights • Personalisation, demand forecasting, risk analysis Outcome 3 : Real-time engagement • Interactive customer experience, event-driven automation, fraud detection
  31. 31. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Ready to build better business from your ideas? Short list projects that directly impact customer engagement and adoption Build simple data pipelines that allow you to test new ideas, and fill your data lake Ask our solution architects and professional services teams to help you build
  32. 32. Thank You

×