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Building a Data Lake on AWS

Published By: AWS     Published Date: Nov 02, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it’s readily available to be categorized, processed, analyzed, and consumed by diverse groups within an organization. Since data - structured and unstructured - can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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AWS

Next-Gen BI for Healthcare and Life Sciences on AWS

Published By: AWS     Published Date: Dec 15, 2017
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time. AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance. In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences. Join this webinar to learn: How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development. How AWS supports BI solutions f
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AWS

Make Faster and More Precise Decisions in a Real-Time World

Published By: AWS     Published Date: Apr 27, 2018
Until recently, businesses that were seeking information about their customers, products, or applications, in real time, were challenged to do so. Streaming data, such as website clickstreams, application logs, and IoT device telemetry, could be ingested but not analyzed in real time for any kind of immediate action. For years, analytics were understood to be a snapshot of the past, but never a window into the present. Reports could show us yesterday’s sales figures, but not what customers are buying right now. Then, along came the cloud. With the emergence of cloud computing, and new technologies leveraging its inherent scalability and agility, streaming data can now be processed in memory, and more significantly, analyzed as it arrives, in real time. Millions to hundreds of millions of events (such as video streams or application alerts) can be collected and analyzed per hour to deliver insights that can be acted upon in an instant. From financial services to manufacturing, this rev
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AWS

Make Faster and More Precise Decisions in a Real-Time World

Published By: AWS     Published Date: May 18, 2018
We’ve become a world of instant information. We carry mobile devices that answer questions in seconds and we track our morning runs from screens on our wrists. News spreads immediately across our social feeds, and traffic alerts direct us away from road closures. As consumers, we have come to expect answers now, in real time. Until recently, businesses that were seeking information about their customers, products, or applications, in real time, were challenged to do so. Streaming data, such as website clickstreams, application logs, and IoT device telemetry, could be ingested but not analyzed in real time for any kind of immediate action. For years, analytics were understood to be a snapshot of the past, but never a window into the present. Reports could show us yesterday’s sales figures, but not what customers are buying right now. Then, along came the cloud. With the emergence of cloud computing, and new technologies leveraging its inherent scalability and agility, streaming data
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AWS

eBook: Modern Data Warehousing on AWS

Published By: AWS     Published Date: Jun 20, 2018
Data and analytics have become an indispensable part of gaining and keeping a competitive edge. But many legacy data warehouses introduce a new challenge for organizations trying to manage large data sets: only a fraction of their data is ever made available for analysis. We call this the “dark data” problem: companies know there is value in the data they collected, but their existing data warehouse is too complex, too slow, and just too expensive to use. A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated q
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AWS

Modern Data Warehousing on AWS

Published By: AWS     Published Date: Aug 20, 2018
A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated querying: ability to run a query across heterogeneous sources of data • Data consumption: support numerous types of analysis - ad-hoc exploration, predefined reporting/dashboards, predictive and advanced analytics
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AWS

Getting Started with Amazon Redshift - Best Practices

Published By: AWS     Published Date: Sep 04, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics.
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AWS

Optimizing Amazon Redshift, A Real-World Guide

Published By: AWS     Published Date: Sep 04, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technology
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AWS

How to Enable High-Performance ELT Processing

Published By: AWS     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
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AWS

Building a data lake on Amazon Web Services (AWS)

Published By: AWS     Published Date: Oct 26, 2018
Today’s organisations are tasked with analysing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organisations are finding that in order to deliver analytic insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store enormous amounts of data in a central location, so it’s readily available to be categorised, processed, analysed, and consumed by diverse groups within an organisation? Since data—structured and unstructured—can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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data, lake, amazon, web, services, aws
    
AWS

Enhance the Availability & Performance of SAP HANA Apps

Published By: AWS     Published Date: Oct 30, 2018
Enhance the Availability & Performance of SAP HANA Apps Abstract: SAP HANA delivers powerful analytics capabilities that can help you improve business performance and drive digital transformation. You can more easily build reliable and performant SAP HANA-powered landscapes with SUSE Linux Enterprise Server for SAP Applications and Amazon Web Services (AWS). That’s because SUSE can help you achieve near zero downtime and sustain high-performance levels, while AWS delivers a broad and deep set of cloud services that are certified to fulfill the compute, memory, and storage requirements of SAP HANA.
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availability, performance, sap, hana, apps
    
AWS

Safeguard your Life Sciences data with Druva and AWS

Published By: AWS     Published Date: Nov 08, 2018
In this webinar, you will learn how Allergan used Druva and AWS during the acquisition of ZELTIQ Aesthetics. You will hear how Allergan protected against accidental and purposeful data loss, and how backup data can be used for eDiscovery and forensic analysis.
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AWS

How to Enhance Your Data and Analytics Process

Published By: AWS     Published Date: Nov 15, 2018
It isn’t always easy to keep pace with today’s high volume of data, especially when it’s coming at you from a diverse number of sources. Tracking these analytics can place a strain on IT, who must provide the requested information to C-suite and analysts. Unless this process can happen quickly, the insights grow stale. Download your complimentary ebook now to see how Matillion ETL for Amazon Redshift makes it easy for technical and business users alike to participate and own the entire data and analysis process. With Matillion ETL for Amazon Redshift, everyone from CTOs to marketing analysts can generate valuable business intelligence by automating data and analytics orchestrations.
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AWS

8 Must-have Features for Enhancing Your Data Visualization

Published By: AWS     Published Date: Nov 15, 2018
"Getting the right analytics, quickly and easily, is important to help grow your organization. But analytics isn’t just about collecting and exploring data. The truly important step resides in converting this data into actionable insights. Acquiring these insights requires some planning ahead. While ease of deployment, time-to-insight, and cost are all important, there are several more assessments you need to take before choosing the right solution. Learn the 8 must-have features to look for in data visualization. Download this white paper to learn how TIBCO® Spotfire® in AWS Marketplace assist in providing you advanced, cost-effective analytics."
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AWS

Achieving 93% Faster Time to Insight with the Power of Artificial Intelligence

Published By: AWS     Published Date: Jan 03, 2019
Managing your data can be a challenge, but establishing an analytics solution that every user can navigate, regardless of skillset, is where organizations often need help. TIBCO® Spotfire® features AI-driven data visualizations and dashboards, which helps enables each organizational role to discover and deliver valuable insights with ease. Riteway Sales and Marketing, which helps many Southeastern supermarkets execute strategies, leveraged the power of TIBCO Spotfire to better understand individual product performance throughout their stores, achieving exponentially faster time to insight than their previous solution allowed. Watch this on-demand webinar to learn how TIBCO Spotfire, when leveraged on Amazon Web Services cloud, can help you generate deep insights in minutes. You’ll learn: • How to generate relevant, actionable insights from any data, anywhere • Some of the best practices for leveraging AI-driven visual and predictive analytics solutions in the cloud • How to
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AWS

Insights for Infrastrucutre

Published By: AWS     Published Date: Nov 15, 2018
Today’s IT teams spend far too much time struggling against increasing system complexity and tools failing to make monitoring easier and more reliable. To combat these challenges, both admins and site reliability engineers need a clear view of infrastructure performance and availability. Splunk® Insights for Infrastructure (SII) is an analytics-driven monitoring solution that provides the seamless experience organizations need for infrastructure monitoring on the AWS cloud. Download this product brief and discover how SII offers: • An easy install within minutes—available as a free download • Detailed investigations through granular metrics • Seamless monitoring and troubleshooting
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AWS

Top 3 Reasons for TIBCO Cloud Integration

Published By: AWS     Published Date: Nov 16, 2018
"Migrating to the cloud? Already living there? TIBCO Cloud Integration is an Integration Platform as a Service (iPaaS) that enables businesses like yours to connect applications easily and securely—no coding required. TIBCO Cloud Integration allows you to extend beyond connectivity to the cloud into IoT application services, analytics, and machine learning. Download this data sheet to see the top 3 reasons to choose TIBCO Cloud Integration for: • A modern platform • True open source innovation • Proven experience at enterprise scale"
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AWS

Self-service Analytics for Financial Services Organizations

Published By: AWS     Published Date: Nov 28, 2018
Financial institutions run on data: collecting it, analyzing it, delivering meaningful insights, and taking action in real time. As data volumes increase, organizations demand a scalable analytics platform that can meet the needs of data scientists and business users alike. However, managing an on-premises analytics environment for a large and diverse user base can become time-consuming, costly, and unwieldy. Tableau Server on Amazon Web Services (AWS) is helping major Financial Services organizations shift data visualization and analytics workloads to the cloud. The result is fewer hours spent on manual work and more time to ask deeper questions and launch new data analyses, with easily-scalable support for large numbers of users. In this webinar, you’ll hear how one major asset management company made the shift to cloud data visualization with Tableau Server on AWS. Discover lessons learned, best practices tailored to Financial Services organizations, and starting tactics for scalable analytics on the cloud.
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AWS

Protect Customer Privacy While Enriching Data Analytics

Published By: AWS     Published Date: Dec 17, 2018
Watch this webinar to learn how Tr?v Insurance Solutions, an insurance agency licensed to sell on-demand property and casualty insurance products, adopted DgSecure on Amazon Web Services (AWS) to anonymize production data to help comply with GDPR and other data privacy regulations. The solution helps Tr?v meet privacy standards while enabling its analytics teams to use data to better serve its clients.
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AWS

A Governed Self-Service Data Platform Accelerates Insights

Published By: AWS     Published Date: Dec 17, 2018
Watch this webinar to learn best practices from Zaloni for creating flexible, responsive, and cost-effective data lakes for advanced analytics that leverage Amazon Web Services (AWS).
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AWS

How FINRA Gains Real-Time Insights To Safeguard US Financial System With Splunk On AWS

Published By: AWS     Published Date: Dec 17, 2018
Watch this webinar to understand how FINRA leverages Splunk with a variety of AWS services such as Amazon Kinesis Data Firehose and AWS Lambda as the data analytics destination to gain real-time insights for powerful visualizations, comprehensive reporting and meaningful alerts.
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AWS

Transition from Commercial Databases to AWS

Published By: AWS     Published Date: Aug 06, 2019
Old-guard database providers are expensive, proprietary, have high lock-in costs, and impose restrictive licensing terms. The challenge to date has been to achieve the same performance and availability of commercial-grade databases on open source databases such as MySQL, PostgreSQL, and MariaDB. Examine key considerations that go into any database migration decision and specific use cases—in Financial Services and Healthcare Analytics implementations—where Datavail carefully managed database migrations from traditional database providers to the cloud—and in particular Amazon Aurora. Download the eBook to learn about: Migration considerations and strategies including lift and shift, re-platforming, and re-factoring Security and compliance functionality enabled by Amazon Aurora Performance and scalability opportunities enabled by AWS
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AWS

Automate Data Analytics with Panoply and Amazon Web Services

Published By: AWS     Published Date: Oct 04, 2019
Speakers include: Stephen Mayne, Solutions Architect, Amazon Web Services, Inc.( AWS), Jason Harris, Evangelist, Panoply, and Audren de Valbray, Data and Insights Director, Motorsport Network.
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AWS

Provide Trusted Data to the Business and Modernize Analytics

Published By: AWS     Published Date: Oct 07, 2019
Hear from speakers: Danielle Greshock, Sr. Manager, Amazon Web Services, Inc. (AWS) Vincent Lam, Head of Cloud Product Marketing, Talend Andy McPhee, Data & Analytics Engineering Director, AstraZeneca
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AWS

How Pokémon Secures Data for Hundreds of Millions of Users with Sumo Logic

Published By: AWS     Published Date: Oct 07, 2019
Pokémon experienced massive growth in the number of downloads for their most popular gaming app. Ensuring customer data was managed, secured, and private was a top priority for their Information Security team. Join us to learn how Pokémon leveraged Sumo Logic on AWS to implement a security analytics solution to scale with their rapid growth. Pokémon will also discuss how they strengthened their overall security posture, gained a unified view of operations, and delivered on their core values of trust and child safety.
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AWS
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