How to Confidently Unleash Data to Meet the Needs of Your Entire Organization - ABD222 - re:Invent 2017

•

1 like•350 views

Where are you on the spectrum of IT leaders? Are you confident that you’re providing the technology and solutions that consistently meet or exceed the needs of your internal customers? Do your peers at the executive table see you as an innovative technology leader? Innovative IT leaders understand the value of getting data and analytics directly into the hands of decision makers, and into their own. In this session, Daren Thayne, Domo’s Chief Technology Officer, shares how innovative IT leaders are helping drive a culture change at their organizations. See how transformative it can be to have real-time access to all of the data that' is relevant to YOUR job (including a complete view of your entire AWS environment), as well as understand how it can help you lead the way in applying that same pattern throughout your entire company.

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS re:Invent
How to Confidently Unleash Data to
Meet the Needs of Your Entire
Organization
D A R E N T H A Y N E , C H I E F T E C H N O L O G Y O F F I C E R
D O M O

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Technology Leadership…
You’ve got a
tough job

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
The number of apps in
use in the enterprise
(many as Shadow IT)
is EXPLODING!

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
More data, more
formats, higher
frequencies ⇢ all with
increased expectations
of self-service

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Oh yeah… and you
also need to keep
costs under control

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
It is just too much…
88% of CIOs say their role is increasingly challenging

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
You could just learn how to run faster…
…and inevitably reach the breaking point.

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Or…you can INNOVATE!
Innovative technology leaders
are taking on an
INCREASINGLY STRATEGIC
role in the enterprise

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Be seen as a Catalyst

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Who is ?

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Mission
Optimize your business in real time by
connecting you to the data and people you
need to improve business results.

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Built for everyone
MANAGERSCXOs ANALYSTS ITOPS HRSERVICESSALESFINANCE MARKETING
COLLABORATION
PORTIONS OF
ENTERPRISE
APPLICATION MARKET
DATA
INTEGRATION TOOLS
DATA
MANAGEMENT
TRADITIONAL BI
& ANALYTICS
+ Open Data Platform
+ Predictive & Prescriptive
+ Mobile-first
+ Any Data, Any User
+ Built-in Collaboration
+ Real-time, Scalable, Secure
Built for ALL users

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
All of your people…

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
…And your data on Domo

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
A Modern Data Platform
• Massively and economically scales
• Connects to data wherever it is
• Empowers individuals to explore and derive insights
• Facilitates collaboration
• Doesn’t pit governance against data access
• Greatly facilitates a culture change

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Introspection – What type of leader are
you?

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
The Word

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Unleash the wisdom

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Image Source: Wikipedia/Apple

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Don’t sacrifice what’s important to IT
• Data Governance can be maintained and expanded
• Shadow IT can be corralled
• Legacy data and analytics assets can be better leveraged
• Automate many manually intensive and repetitive tasks
• Common layer for managing data entitlements
• Reduce costs by leveraging more cost-effective IT infrastructure

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
The Domo Difference

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Can I manage AWS with Domo? (Yes.)
Manage by Purpose
Manage by Service
►
►

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
How I use Domo to manage AWS

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
JASON ROBERTS
GLOBAL HEAD OF TECHNOLOGY AND
ANALYTICS

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
about randstad
top 3
32,280
4,752
626,300
€20.7b
internal
employees
branch offices &
inhouse locations
average talent on
assignment weekly
in revenue
in market share in
10+ countries
over
90%
coverage of the global
HR services market
strategic building blocks
strong concepts best people
excellent execution superior brands
randstad
alliance partners

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Building Consultative Capabilities with Data
talent advisor toolkit

33 © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
DEMO

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
FINAL THOUGHTS

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Driving Culture Change
• Empower everyone with access to real-time data and insights
• Arm them with powerful – yet easy-to-use – analytics
• Align your organization around your single source of truth
• Maintain governance and control of your data
• Be the hero

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
The choice is in your hands…
Continue to let it happen to you
OR
Become the innovative leader to transform your role and the future
direction of your company

© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Thank You.
D A R E N . T H A Y N E @ D O M O . C O M
@ d a r e n t h a y n e

To meet the needs of the global marketing organization, the AWS marketing analytics team built a scalable platform that allows the data science team to deliver custom econometric and machine learning models for end user self-service. To meet data security standards, we use end-to-end data encryption and different AWS services such as Amazon Redshift, Amazon RDS, Amazon S3, Amazon EMR with Apache Spark and Auto Scaling. In this session, you see real examples of how we have scaled and automated critical analysis, such as calculating the impact of marketing programs like re:Invent and prioritizing leads for our sales teams.

How Twilio Scaled Its Data Driven Culture - ABD309 - re:Invent 2017

Amazon Web Services

As a leading cloud communications platform, Twilio has always been strongly data-driven. But as headcount and data volumes grew—and grew quickly—they faced many new challenges. One-off, static reports work when you’re a small startup, but how do you support a growth stage company to a successful IPO and beyond? Today, Twilio's data team relies on AWS and Looker to provide data access to 700 colleagues. Departments have the data they need to make decisions, and cloud-based scale means they get answers fast. Data delivers real-business value at Twilio, providing a 360-degree view of their customer, product, and business. In this session, you hear firsthand stories directly from the Twilio data team and learn real-world tips for fostering a truly data-driven culture at scale. Session sponsored by Looker

ABD302_Real-Time Data Exploration and Analytics with Amazon Elasticsearch Ser...

Amazon Web Services

The document is about real-time data exploration and analytics using Amazon Elasticsearch Service. It discusses ingesting and storing data in Elasticsearch, sizing the Elasticsearch domain, securing the domain, adding durability, monitoring the domain, and analyzing the stored data. The presentation was given by Jon Handler, a Principal Solutions Architect at AWS, at AWS re:Invent in November 2017.

ABD316_American Heart Association Finding Cures to Heart Disease Through the ...

Amazon Web Services

Combining disparate datasets and making them accessible to data scientists and researchers is a prevalent challenge for many organizations, not just in healthcare research. American Heart Association (AHA) has built a data science platform using Amazon EMR, Amazon Elasticsearch Service, and other AWS services, that corrals multiple datasets and enables advanced research on phenotype and genotype datasets, aimed at curing heart diseases. In this session, we present how AHA built this platform and the key challenges they addressed with the solution. We also provide a demo of the platform, and leave you with suggestions and next steps so you can build similar solutions for your use cases.

ABD214_Real-time User Insights for Mobile and Web Applications with Amazon Pi...

Amazon Web Services

With customers demanding relevant and real-time experiences across a range of devices, digital businesses are looking to gather user data at scale, understand this data, and respond to customer needs instantly. This requires tools that can record large volumes of user data in a structured fashion, and then instantly make this data available to generate insights. In this session, we demonstrate how you can use Amazon Pinpoint to capture user data in a structured yet flexible manner. Further, we demonstrate how this data can be set up for instant consumption using services like Amazon Kinesis Firehose and Amazon Redshift. We walk through example data based on real world scenarios, to illustrate how Amazon Pinpoint lets you easily organize millions of events, record them in real-time, and store them for further analysis.

ABD303_Developing an Insights Platform—the Sysco Journey from Disparate Syste...

Amazon Web Services

Sysco has nearly 200 operating companies across its multiple lines of business throughout the United States, Canada, Central/South America, and Europe. As the global leader in food services, Sysco identified the need to streamline the collection, transformation, and presentation of data produced by the distributed units and systems, into a central data ecosystem. Sysco's Business Intelligence and Analytics team addressed these requirements by creating a data lake with scalable analytics and query engines leveraging AWS services. In this session, Sysco will outline their journey from a hindsight reporting focused company to an insights driven organization. They will cover solution architecture, challenges, and lessons learned from deploying a self-service insights platform. They will also walk through the design patterns they used and how they designed the solution to provide predictive analytics using Amazon Redshift Spectrum, Amazon S3, Amazon EMR, AWS Glue, Amazon Elasticsearch Service and other AWS services.

ABD218_How Euroleague Basketball Uses IoT Analytics to Engage Fans- ABD218

Amazon Web Services

IoT and big data have made their way out of industrial applications, general automation, and consumer goods, and are now a valuable tool for improving consumer engagement across a number of industries, including media, entertainment, and sports. The low cost and ease of implementation of AWS analytics services and AWS IoT have allowed AGT, a leader in IoT, to develop their IoTA analytics platform. Using IoTA, AGT brought a tailored solution to EuroLeague Basketball for real-time content production and fan engagement during the 2017-18 season. In this session, we take a deep dive into how this solution is architected for secure, scalable, and highly performant data collection from athletes, coaches, and fans. We also talk about how the data is transformed into insights and integrated into a content generation pipeline. Lastly, we demonstrate how this solution can be easily adapted for other industries and applications.

Migrating your traditional Data Warehouse to a Modern Data Lake

Amazon Web Services

In this session, we discuss the latest features of Amazon Redshift and Redshift Spectrum, and take a deep dive into its architecture and inner workings. We share many of the recent availability, performance, and management enhancements and how they improve your end user experience. You also hear from 21st Century Fox, who presents a case study of their fast migration from an on-premises data warehouse to Amazon Redshift. Learn how they are expanding their data warehouse to a data lake that encompasses multiple data sources and data formats. This architecture helps them tie together siloed business units and get actionable 360-degree insights across their consumer base.

In this session, we detail Sysco's journey from a company focused on hindsight-based reporting to one focused on insights and foresight. For this shift, Sysco moved from multiple data warehouses to an AWS ecosystem, including Amazon Redshift, Amazon EMR, AWS Data Pipeline, and more. As the team at Sysco worked with Tableau, they gained agile insight across their business. Learn how Sysco decided to use AWS, how they scaled, and how they became more strategic with the AWS ecosystem and Tableau. Session sponsored by Tableau

FINRA's Managed Data Lake: Next-Gen Analytics in the Cloud - ENT328 - re:Inve...

Amazon Web Services

FINRA faced challenges with their on-premises data infrastructure, including difficulty tracking data, limited scalability, and high costs. They migrated to a managed data lake on AWS to address these issues. This provided centralized data management with a catalog, separation of storage and compute, encryption, and cost optimization. It enabled faster analytics through Presto querying, machine learning model development, and reduced TCO by 30% compared to their on-premises environment. Lessons learned included embracing disruption, automating infrastructure, and treating infrastructure as code. FINRA is exploring additional AWS services like Athena, Lambda, and Step Functions to continue improving their analytics capabilities.

DAT307_Modern Cloud Data Warehousing

Amazon Web Services

"We're still in the midst of a data explosion. With data, we want to do things smarter, quicker, and more accurately, and working with a company like Snowflake enables us to do so. In this session, Kelly Mungary, Lionsgate director of enterprise data and analytics, details how Lionsgate achieved the “Holy Grail” of data analytics – easily storing, blending, and analyzing structured and semi-structured data for agile reporting and data science. With modern data warehousing built for the cloud, Lionsgate achieves faster time to market and continues to migrate investment away from traditional, fading platforms. Lionsgate is a leading global entertainment company that generates vast stores of varied data types from sales, research, social media, exit polls, box office activity, and many other channels to better serve its business customers and its fans. Session sponsored by Snowflake"

Best Practices for Distributed Machine Learning and Predictive Analytics Usin...

Amazon Web Services

This session, we focus on common use cases and design patterns for predictive analytics using Amazon EMR. We address accessing data from a data lake, extraction and preprocessing with Apache Spark, analytics and machine learning code development with notebooks (Jupyter, Zeppelin), and data visualization using Amazon QuickSight. We cover other operational topics, such as deployment patterns for ad hoc exploration and batch workloads using Spot and multi-user notebooks. The intended audience for this session includes technical users who are building statistical and data analytics models for the business using tools, such as Python, R, Spark, Presto, Amazon EMR, Notebooks.

FSV302_An Architecture for Trade Capture and Regulatory Reporting

Amazon Web Services

For many securities organizations, post-trade processing is expensive, cumbersome, and time-consuming. This is in part due to the massive volumes of data required for processing a trade and the limited agility of the technology on which many organizations rely today. In order to create efficiencies and move faster, many financial services organizations are working with AWS to implement post-trade solutions built with AWS storage services (Amazon S3 and Amazon Glacier) and big data capabilities (Amazon Athena, Amazon EMR, Amazon Redshift, and Amazon QuickSight ). In this session, we walk through a trade capture and regulatory reporting solution that uses the aforementioned AWS services. We also provide guidance around obtaining data-driven insights (from pixels to pictures); bolstering encryption with AWS KMS; and maintaining transparency and control with Amazon CloudWatch and Amazon CloudTrail (which also helps meet SEC Rule 613 that requires the creation of comprehensive consolidated audit trails).

ABD311_Deploying Amazon QuickSight For Enterprise

Amazon Web Services

One of the biggest tradeoffs customers usually make when deploying BI solutions at scale is agility versus governance. Large-scale BI implementations with the right governance structure can take months to design and deploy. In this session, learn how you can avoid making this tradeoff using Amazon QuickSight. Learn how to easily deploy Amazon QuickSight to thousands of users using Active Directory and Federated SSO, while securely accessing your data sources in Amazon VPCs or on-premises. We also cover how to control access to your datasets, implement row-level security, create scheduled email reports, and audit access to your data.

RET301-Build Single Customer View across Multiple Retail Channels using AWS S...

Amazon Web Services

A challenge faced by many retailers is how to form an integrated single view of the customer across multiple retail channels to help you better understand purchasing behavior & patterns. In this session, we will present a solution that merges web analytics data with customer purchase history based on AWS API Gateway, Lambda and S3. Learn how to track customer purchase behaviors across different selling channels to better predict future needs and make relevant, intelligent recommendations.

FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...

Amazon Web Services

FINRA’s analytics platform unlocks the value in capital markets data by accelerating trade analytics and providing a foundation for machine learning at scale. The platform enables FINRA’s analysts to perform discovery on petabytes of trade data to identify instances of potential fraud, market manipulation, and insider trading. By centralizing all data in S3, FINRA’s architecture offers improved agility, scalability, and cost effectiveness. Analytics services such as Amazon EMR and Amazon Redshift have freed FINRA’s data scientists from the constraints of desktop tools, allowing them to apply machine learning techniques to develop and test new surveillance patterns. All of this is done while meeting FINRA’s security and compliance responsibilities as a financial regulator. At the end of this session, you’ll have an understanding of how to apply FINRA’s architecture to trade analytics and other financial services use cases, including meeting regulatory requirements such as the Consolidated Audit Trail (CAT) reporting.

GPSTEC201_Building an Artificial Intelligence Practice for Consulting Partners

Amazon Web Services

Companies around the world are looking at using artificial intelligence and machine learning to launch new innovative products and services and to drive efficiencies via automation in their businesses. Come to this session to understand why you should consider building an AI/ML practice in your consulting company. Learn the importance of having strong data engineering skills, including data annotation, and get some tips on building a data science team that can deliver customer projects.

ABD208_Cox Automotive Empowered to Scale with Splunk Cloud & AWS and Explores...

Amazon Web Services

"In this session, learn how Cox Automotive is using Splunk Cloud for real time visibility into its AWS and hybrid environments to achieve near instantaneous MTTI, reduce auction incidents by 90%, and proactively predict outages. We also introduce a highly anticipated capability that allows you to ingest, transform, and analyze data in real time using Splunk and Amazon Kinesis Firehose to gain valuable insights from your cloud resources. It’s now quicker and easier than ever to gain access to analytics-driven infrastructure monitoring using Splunk Enterprise & Splunk Cloud. Session sponsored by Splunk"

ATC302_How to Leverage AWS Machine Learning Services to Analyze and Optimize ...

Amazon Web Services

In this session, you’ll learn how AdTech companies use AWS services like Glue, Athena, Quicksight, and EMR to analyze your Google DoubleClick Campaign Manager data at scale without the burden of infrastructure or worries about server maintenance. We’ll live-process a click stream so you can see how Machine Learning can help maximize your revenue by finding the most optimal path of a campaign and we’ll look at a real world demo from A9’s Advertising Science Team of how they use the data to build Look-alike Model in their projects.

ABD206-Building Visualizations and Dashboards with Amazon QuickSight

Amazon Web Services

Just as a picture is worth a thousand words, a visual is worth a thousand data points. A key aspect of our ability to gain insights from our data is to look for patterns, and these patterns are often not evident when we simply look at data in tables. The right visualization will help you gain a deeper understanding in a much quicker timeframe. In this session, we will show you how to quickly and easily visualize your data using Amazon QuickSight. We will show you how you can connect to data sources, generate custom metrics and calculations, create comprehensive business dashboards with various chart types, and setup filters and drill downs to slice and dice the data.

ABD205_Building a Superpower

Amazon Web Services

ARC207_Monitoring Performance of Enterprise Applications on AWS

Amazon Web Services

"Applications running in a typical data center are static entities. But applications aren't static in the cloud. Dynamic scaling and resource allocation is the norm on AWS. Technologies such as Amazon EC2, AWS Lambda, and Auto Scaling provide flexibility in building dynamic applications and with this flexibility comes an opportunity to learn how an enterprise application functions optimally. New Relic helps manage these applications without sacrificing simplicity. In this session, we discuss changes in monitoring dynamic cloud resources. We'll share best practices we’ve learned working with New Relic customers on managing applications running in this environment to understand and optimize how they are performing. Session sponsored by New Relic"

GPSWKS401_Designing a Cloud Enterprise Data Warehouse

Amazon Web Services

This document provides an overview and summary of a workshop on designing a cloud enterprise data warehouse using AWS services. The workshop covers Amazon Redshift for the data warehouse, Amazon Kinesis and AWS Glue for ingesting and processing data, and Amazon QuickSight for visualization. It discusses designing the data warehouse, loading data through batch and streaming methods, and using AWS services together to build the complete analytics pipeline for collecting, storing, processing and analyzing data in the cloud.

GPSBUS201-GPS Demystifying Artificial Intelligence

Amazon Web Services

STG302_Best Practices for Amazon S3

Amazon Web Services

GAM306_Building a Lake of Wisdom

Amazon Web Services

Learn how Rovio replaced functionalities in their analytics platform provided by a 3rd party vendor in seven weeks with Amazon Athena, Amazon EMR, and Amazon Redshift. In the ever changing world of games, you must stay ahead of trends and understand your customer base’s actions. We describe how we built a data lake using AWS services such as Amazon S3, Amazon Athena, and Amazon EMR. We give a general overview on our analytics stack, business problems unique to the gaming industry we’re trying to solve, data philosophy (one truth, open data), and challenges we had at the beginning of this year. We also dive deep into areas most gaming companies struggle with, like how we manage the schemas, convert data to efficient columnar format, partition the data, ultimately use the data, and handle some of the challenges we faced using services like Athena. Learn about our quest to perfect games and customer gaming experience!

AMF302-Alexa Wheres My Car A Test Drive of the AWS Connected Car Reference.pdf

Amazon Web Services

Today's trends in auto technology are all about connecting cars and their occupants to the outside world in a seamless and safe manner. In this session, we discuss how automotive companies are leveraging AWS for a variety of connected vehicle use cases. You'll leave this session with source code, architecture diagrams, and an understanding of how to apply the AWS Connected Vehicle Reference Architecture to build your own prototypes. You'll also learn how car companies can leverage Amazon services such as Alexa and AWS services such as AWS IOT, AWS Greengrass, AWS Lambda and Amazon API Gateway to rapidly develop and deploy innovative connected vehicle services.

Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017

Amazon Web Services

AWS Lambda is a great fit for many data processing tasks, for data analytics and for machine learning inference. The Lambda team use Lambda for our own Analytics in conjunction with other AWS services. In this session, we will cover how we tie these services together to crunch the data Lambda creates to generate insights to better run our service. We will cover common design patterns for big data processing, how they map to Lambda and serverless, and look at some new patterns that serverless makes possible. Finally we will look to how to leverage Machine Learning inference on Lambda to derive better insights from the data.

The Enterprise Fast Lane - What Your Competition Doesn't Want You to Know abo...

Amazon Web Services

The document discusses how AutoScout24 transformed its enterprise IT organization to become cloud native. It covers how the company transitioned from a monolithic architecture running in its own data centers to a microservices architecture built on AWS. This involved cultural changes like moving to autonomous teams organized around business capabilities rather than technical stacks. The transformation principles discussed include becoming data-driven, embracing failure, and empowering cross-functional teams of engineers. The goal was to enable faster innovation, reduce costs, and attract top talent through an evolutionary approach to digital transformation.

Women in Big Data

Amazon Web Services

What's hot

A Journey from Too Much Data to Curated Insights - ABD211 - re:Invent 2017

Amazon Web Services

FINRA's Managed Data Lake: Next-Gen Analytics in the Cloud - ENT328 - re:Inve...

Amazon Web Services

DAT307_Modern Cloud Data Warehousing

Amazon Web Services

Best Practices for Distributed Machine Learning and Predictive Analytics Usin...

Amazon Web Services

FSV302_An Architecture for Trade Capture and Regulatory Reporting

Amazon Web Services

ABD311_Deploying Amazon QuickSight For Enterprise

Amazon Web Services

RET301-Build Single Customer View across Multiple Retail Channels using AWS S...

Amazon Web Services

FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...

Amazon Web Services

GPSTEC201_Building an Artificial Intelligence Practice for Consulting Partners

Amazon Web Services

ABD208_Cox Automotive Empowered to Scale with Splunk Cloud & AWS and Explores...

Amazon Web Services

ATC302_How to Leverage AWS Machine Learning Services to Analyze and Optimize ...

Amazon Web Services

ABD206-Building Visualizations and Dashboards with Amazon QuickSight

Amazon Web Services

ABD205_Building a Superpower

Amazon Web Services

ARC207_Monitoring Performance of Enterprise Applications on AWS

Amazon Web Services

GPSWKS401_Designing a Cloud Enterprise Data Warehouse

Amazon Web Services

GPSBUS201-GPS Demystifying Artificial Intelligence

Amazon Web Services

STG302_Best Practices for Amazon S3

Amazon Web Services

GAM306_Building a Lake of Wisdom

Amazon Web Services

AMF302-Alexa Wheres My Car A Test Drive of the AWS Connected Car Reference.pdf

Amazon Web Services

Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017

Amazon Web Services

What's hot (20)

A Journey from Too Much Data to Curated Insights - ABD211 - re:Invent 2017

FINRA's Managed Data Lake: Next-Gen Analytics in the Cloud - ENT328 - re:Inve...

DAT307_Modern Cloud Data Warehousing

Best Practices for Distributed Machine Learning and Predictive Analytics Usin...

FSV302_An Architecture for Trade Capture and Regulatory Reporting

ABD311_Deploying Amazon QuickSight For Enterprise

RET301-Build Single Customer View across Multiple Retail Channels using AWS S...

FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...

GPSTEC201_Building an Artificial Intelligence Practice for Consulting Partners

ABD208_Cox Automotive Empowered to Scale with Splunk Cloud & AWS and Explores...

ATC302_How to Leverage AWS Machine Learning Services to Analyze and Optimize ...

ABD206-Building Visualizations and Dashboards with Amazon QuickSight

ABD205_Building a Superpower

ARC207_Monitoring Performance of Enterprise Applications on AWS

GPSWKS401_Designing a Cloud Enterprise Data Warehouse

GPSBUS201-GPS Demystifying Artificial Intelligence

STG302_Best Practices for Amazon S3

GAM306_Building a Lake of Wisdom

AMF302-Alexa Wheres My Car A Test Drive of the AWS Connected Car Reference.pdf

Big Data, Analytics and Machine Learning on AWS Lambda - SRV402 - re:Invent 2017

Similar to How to Confidently Unleash Data to Meet the Needs of Your Entire Organization - ABD222 - re:Invent 2017

The Enterprise Fast Lane - What Your Competition Doesn't Want You to Know abo...

Amazon Web Services

Women in Big Data

Amazon Web Services

ENT212-An Overview of Best Practices for Large-Scale Migrations

Amazon Web Services

Introduction: AWS-Enabled Enterprise Storage Solutions

Amazon Web Services

This document discusses how AWS supports enterprises in their cloud adoption journey. It covers how more than two-thirds of IT budgets are spent keeping existing systems running rather than innovation, and how the cloud can help address this. It then describes the various support services AWS Enterprise Support provides, including technical account managers and health dashboards. Next, it introduces the AWS Cloud Adoption Framework, a methodology for understanding how the cloud can transform operations. Finally, it discusses the AWS Partner Network and how partners can assist with solutions in areas like storage, as well as the AWS Marketplace for accessing third-party software.

An Overview of Best Practices for Large Scale Migrations

Amazon Web Services

Keynote: What Transformation Really Means for the Enterprise - AWS Transforma...

Amazon Web Services

Digital transformation means something new every decade. This sort of constant change is stressful for any organization, but especially for the large enterprise. Because while nearly every enterprise began as a small, scrappy team, success means growth, and growth means accumulation—more technology, more processes, more people, and more red tape. In this session, we’ll give an executive-level view of how the cloud removes the stressful burden of on-premise applications, legacy technology, and outdated processes from the enterprise. We’ll examine what digital transformation really means, and offer prescriptive guidance around decluttering the enterprise, security, culture, and more. AWS enables every enterprise to invest in strategic innovation and modernization. With the AWS cloud, enterprises become more agile, more efficient, and are better equipped to keep pace with constant change. As a partner, AWS enables every enterprise to live its own version of the Amazon Story—one of growth without burdensome accumulation, success without slowness, and constant innovation.

GPS: Starting Out with the AWS Partner Network - GPSBUS223 - re:Invent 2017

Amazon Web Services

GPSBUS223-Starting Out with the AWS Partner Network

Amazon Web Services

From Cloud Cost Management to Financial Agility: The Journey to Success - ENT...

Amazon Web Services

Cloud is the new normal - it continues to deliver amazing new technologies and drive us to innovate our operational models. Cloud also gives us new capabilities to see the tremendous financial impact to our businesses. As you journey into the cloud, your teams will need to wield the cloud power responsibly. They will need more visibility into the financial impact of their resource usage in order to make the best decisions for today and for the longer term. Join Cloudability and HERE Technologies as we guide you through the journey to financial agility on the cloud as we have seen it play it out in hundreds of customers. You’ll walk away with the steps you need to take and the mindset your teams will need to adopt in order to achieve financial agility. Topics include: - Discovering and validating your goals (needs, requirements, responsibilities) - Analyzing and closing the gaps between your goals and your reality - Developing a new operational model that provides the financial agility and predictability - HERE Technologies case study Session Sponsored by Cloudability

GPSBUS202_Driving Customer Value with Big Data Analytics

Amazon Web Services

The document discusses how AWS and its partners can help customers drive value through big data analytics. It provides an overview of the big data opportunity and why AWS is well-suited for big data solutions. Examples are given of AWS partners like Snowflake and Cloudwick that have built valuable big data solutions for customers using AWS services. The document recommends that partners focus on building solutions, not just tools, and leverage the full AWS platform and ecosystem to create differentiated solutions and deliver higher customer value.

Journey to Outcomes

Amazon Web Services LATAM

This document summarizes Amazon Web Services professional services and how they can help organizations adopt cloud technologies. It outlines AWS' engagement model which includes aligning stakeholders on goals, launching pilots to validate outcomes, scaling successful pilots, and continuously optimizing to create new value. The first step is to align stakeholders through workshops to define outcomes and critical next steps over 2 weeks to get agreement to move forward.

Leveraging a Cloud Policy Framework - From Zero to Well Governed - ENT318 - r...

Amazon Web Services

Governing cloud infrastructure at scale requires software that enables you to capture and drive management from internal policies, best practices, and reference architectures. A policy-driven management and governance strategy is critical to successfully operate in cloud and hybrid environments. As infrastructure grows, you might leverage knowledge that extends beyond the organization. An open-source “cloud policy framework” enables users to leverage a community that can help define and tune best practice policies, and help SaaS vendors and ISVs capture the best way to manage an application and share it with customers. A well-defined management and governance strategy enables you to put automation in place that keeps your cloud running securely and efficiently without having to take it on as a full-time job. This session discusses the development of a “cloud policy framework” that enables users to leverage open source rule definition organizations can use to govern their cloud. Learn best practice policies for managing all aspects of services, applications, and infrastructure across cost, availability, performance, security and usage. Session sponsored by CloudHealth Technologies

Moving Forward with AI

Amazon Web Services

The document provides an overview of artificial intelligence (AI) and machine learning, including key milestones in the development of AI and deep learning techniques. It discusses early pioneers in AI from the 1950s and developments that enabled recent advances, such as increased data, GPUs, cloud computing, and algorithms. Examples are given of applying deep learning techniques to problems like image recognition, natural language processing, and generating images/text. The document also discusses Amazon AI services for vision, speech, text analysis and language translation that make ML accessible.

AWS re:Invent 2017 | CloudHealth Tech Session

CloudHealth by VMware

Innovations and The Cloud

Adrian Hornsby

The document discusses innovations in artificial intelligence and cloud computing. It describes how AI has advanced from early neural networks in the 1950s to today's deep learning algorithms powered by large datasets, GPUs, cloud computing, and AWS services. The document outlines several AWS AI services including Amazon Rekognition for image analysis, Amazon Polly for text-to-speech, and Amazon Lex for conversational interfaces. It emphasizes that AWS aims to put AI in the hands of every developer.

Keynote

Amazon Web Services

This document contains an agenda for an AWS event titled "AWSome Day" being held in Stockholm, Sweden. The agenda includes a keynote, sessions on AWS foundations, infrastructure, databases, security best practices, and tools. There will also be technical and business tracks running in parallel sessions. The document provides contact information and notes that slides from the event will be available after it concludes. It encourages attendees to complete a post-event survey and mentions an additional security and compliance session for the public sector.

AWS Cloud Migration Insights Forum

Amazon Web Services

Cloud migration is more than simply a business efficiency or a cost-saving measure. It’s a critical step towards digital transformation, innovation and operational resilience that has opened up opportunities for those who’ve embraced cloud adoption. Whether you are looking to embark on your cloud migration or scaling the number of applications you’re moving to the cloud, it does not need to be a daunting task or one that you go at alone. AWS offers 10 years of experience helping businesses to efficiently move their legacy on-premises systems to the cloud. We work closely alongside numerous local delivery partners to help you meet your business needs. Our Cloud Migration insights forum helps you to learn how to simplify your cloud journey with AWS.

AWSome Day - Opening Keynote

Adrian Hornsby

Keynote - AWSome Day Copenhagen

Amazon Web Services

NEW LAUNCH! Introducing Amazon MQ Managed Message Broker Service for ActiveMQ...

Amazon Web Services

Amazon MQ is a new managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud. Amazon MQ manages the work involved in setting up an ActiveMQ message broker, from provisioning the infrastructure, to installing the software and ongoing maintenance. It supports industry-standard messaging APIs and protocols, so you can switch from any message broker to Amazon MQ without re-writing the supported applications. This session provides an overview of how Amazon MQ makes enterprise messaging and migration more manageable. You’ll learn how you can use Amazon MQ to launch a production-ready message broker in minutes. Guest speakers from Volvo WirelessCar and GE will share how they’re using messaging in their own applications and systems, and the advantages enabled by a managed ActiveMQ service on AWS.

Similar to How to Confidently Unleash Data to Meet the Needs of Your Entire Organization - ABD222 - re:Invent 2017 (20)

The Enterprise Fast Lane - What Your Competition Doesn't Want You to Know abo...

Women in Big Data

ENT212-An Overview of Best Practices for Large-Scale Migrations

Introduction: AWS-Enabled Enterprise Storage Solutions

An Overview of Best Practices for Large Scale Migrations

Keynote: What Transformation Really Means for the Enterprise - AWS Transforma...

GPS: Starting Out with the AWS Partner Network - GPSBUS223 - re:Invent 2017

GPSBUS223-Starting Out with the AWS Partner Network

From Cloud Cost Management to Financial Agility: The Journey to Success - ENT...

GPSBUS202_Driving Customer Value with Big Data Analytics

Journey to Outcomes

Leveraging a Cloud Policy Framework - From Zero to Well Governed - ENT318 - r...

Moving Forward with AI

AWS re:Invent 2017 | CloudHealth Tech Session

Innovations and The Cloud

Keynote

AWS Cloud Migration Insights Forum

AWSome Day - Opening Keynote

Keynote - AWSome Day Copenhagen

NEW LAUNCH! Introducing Amazon MQ Managed Message Broker Service for ActiveMQ...

More from Amazon Web Services

Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...

Amazon Web Services

Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS. In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.

Big Data per le Startup: come creare applicazioni Big Data in modalità Server...

Amazon Web Services

La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup. Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti. Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.

Esegui pod serverless con Amazon EKS e AWS Fargate

Amazon Web Services

Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi

Costruire Applicazioni Moderne con AWS

Amazon Web Services

Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.

Come spendere fino al 90% in meno con i container e le istanze spot

Amazon Web Services

L’utilizzo dei container è in continua crescita. Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili. I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!

Open banking as a service

Amazon Web Services

In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th. Event Agenda : Open banking so far (short recap) • PSD2, OB UK, OB Australia, OB LATAM, OB Israel Intro to Open Finance marketplace • Scope • Features • Tech overview and Demo The role of the Cloud The Future of APIs • Complying with regulation • Monetizing data / APIs • Business models • Time to market One platform for all: a Strategic approach Q&A

Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...

Amazon Web Services

Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc. AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta. Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.

OpsWorks Configuration Management: automatizza la gestione e i deployment del...

Amazon Web Services

Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity. AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet. Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.

Microsoft Active Directory su AWS per supportare i tuoi Windows Workloads

Amazon Web Services

Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.

Computer Vision con AWS

Amazon Web Services

Database Oracle e VMware Cloud on AWS i miti da sfatare

Amazon Web Services

Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti. Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi. La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.

Crea la tua prima serverless ledger-based app con QLDB e NodeJS

Amazon Web Services

Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti. Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire. Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito. In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.

API moderne real-time per applicazioni mobili e web

Amazon Web Services

Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline. Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.

Database Oracle e VMware Cloud™ on AWS: i miti da sfatare

Amazon Web Services

Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi. La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali. In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.

Tools for building your MVP on AWS

Amazon Web Services

1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS). 2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels. 3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.

How to Build a Winning Pitch Deck

Amazon Web Services

This document discusses pitch decks and fundraising materials. It explains that venture capitalists will typically spend only 3 minutes and 44 seconds reviewing a pitch deck. Therefore, the deck needs to tell a compelling story to grab their attention. It also provides tips on tailoring different types of decks for different purposes, such as creating a concise 1-2 page teaser, a presentation deck for pitching in-person, and a more detailed read-only or fundraising deck. The document stresses the importance of including key information like the problem, solution, product, traction, market size, plans, team, and ask.

Building a web application without servers

Amazon Web Services

This document discusses building serverless web applications using AWS services like API Gateway, Lambda, DynamoDB, S3 and Amplify. It provides an overview of each service and how they can work together to create a scalable, secure and cost-effective serverless application stack without having to manage servers or infrastructure. Key services covered include API Gateway for hosting APIs, Lambda for backend logic, DynamoDB for database needs, S3 for static content, and Amplify for frontend hosting and continuous deployment.

Fundraising Essentials

Amazon Web Services

This document provides tips for fundraising from startup founders Roland Yau and Sze Lok Chan. It discusses generating competition to create urgency for investors, fundraising in parallel rather than sequentially, having a clear fundraising narrative focused on what you do and why it's compelling, and prioritizing relationships with people over firms. It also notes how the pandemic has changed fundraising, with examples of deals done virtually during this time. The tips emphasize being fully prepared before fundraising and cultivating connections with investors in advance.

AWS_HK_StartupDay_Building Interactive websites while automating for efficien...

Amazon Web Services

This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.

Introduzione a Amazon Elastic Container Service

Amazon Web Services

Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.

More from Amazon Web Services (20)

Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...

Big Data per le Startup: come creare applicazioni Big Data in modalità Server...

Esegui pod serverless con Amazon EKS e AWS Fargate

Costruire Applicazioni Moderne con AWS

Come spendere fino al 90% in meno con i container e le istanze spot

Open banking as a service

Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...

OpsWorks Configuration Management: automatizza la gestione e i deployment del...

Microsoft Active Directory su AWS per supportare i tuoi Windows Workloads

Computer Vision con AWS

Database Oracle e VMware Cloud on AWS i miti da sfatare

Crea la tua prima serverless ledger-based app con QLDB e NodeJS

API moderne real-time per applicazioni mobili e web

Database Oracle e VMware Cloud™ on AWS: i miti da sfatare

Tools for building your MVP on AWS

How to Build a Winning Pitch Deck

Building a web application without servers

Fundraising Essentials

AWS_HK_StartupDay_Building Interactive websites while automating for efficien...

Introduzione a Amazon Elastic Container Service

How to Confidently Unleash Data to Meet the Needs of Your Entire Organization - ABD222 - re:Invent 2017

1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. AWS re:Invent How to Confidently Unleash Data to Meet the Needs of Your Entire Organization D A R E N T H A Y N E , C H I E F T E C H N O L O G Y O F F I C E R D O M O

12. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Built for everyone MANAGERSCXOs ANALYSTS ITOPS HRSERVICESSALESFINANCE MARKETING COLLABORATION PORTIONS OF ENTERPRISE APPLICATION MARKET DATA INTEGRATION TOOLS DATA MANAGEMENT TRADITIONAL BI & ANALYTICS + Open Data Platform + Predictive & Prescriptive + Mobile-first + Any Data, Any User + Built-in Collaboration + Real-time, Scalable, Secure Built for ALL users

15. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. A Modern Data Platform • Massively and economically scales • Connects to data wherever it is • Empowers individuals to explore and derive insights • Facilitates collaboration • Doesn’t pit governance against data access • Greatly facilitates a culture change

16.

21. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Don’t sacrifice what’s important to IT • Data Governance can be maintained and expanded • Shadow IT can be corralled • Legacy data and analytics assets can be better leveraged • Automate many manually intensive and repetitive tasks • Common layer for managing data entitlements • Reduce costs by leveraging more cost-effective IT infrastructure

26.

28. the human intelligence advantage

29. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. about randstad top 3 32,280 4,752 626,300 €20.7b internal employees branch offices & inhouse locations average talent on assignment weekly in revenue in market share in 10+ countries over 90% coverage of the global HR services market strategic building blocks strong concepts best people excellent execution superior brands randstad alliance partners

30. 30

31. 31

35. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Driving Culture Change • Empower everyone with access to real-time data and insights • Arm them with powerful – yet easy-to-use – analytics • Align your organization around your single source of truth • Maintain governance and control of your data • Be the hero

36. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. The choice is in your hands… Continue to let it happen to you OR Become the innovative leader to transform your role and the future direction of your company

How to Confidently Unleash Data to Meet the Needs of Your Entire Organization - ABD222 - re:Invent 2017

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to How to Confidently Unleash Data to Meet the Needs of Your Entire Organization - ABD222 - re:Invent 2017

Similar to How to Confidently Unleash Data to Meet the Needs of Your Entire Organization - ABD222 - re:Invent 2017 (20)

More from Amazon Web Services

More from Amazon Web Services (20)

How to Confidently Unleash Data to Meet the Needs of Your Entire Organization - ABD222 - re:Invent 2017