Today, deep learning is at the forefront of most machine learning implementations across a broad set of business verticals. Driven by the highly flexible nature of neural networks, the boundary of what is possible has been pushed to a point where neural networks outperform humans in a variety of tasks, such as classifying objects in images or mastering video games in a matter of hours. This guide outlines the end-to-end deep learning process implemented on Amazon Web Services (AWS). We discuss challenges in executing deep learning projects, highlight the latest and greatest technology and infrastructure offered by AWS, and provide architectural guidance and best practices along the way.
This paper is intended for deep learning research scientists, deep learning engineers, data scientists, data engineers, technical product managers, and engineering leaders.
Published By: Cisco EMEA
Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
Big Data is not just a big buzzword. Government agencies have been collecting large amounts of data for some time and analyzing the data collected to one degree or another. Big data is a term that describes high volume, variety and velocity of information that inundates an organization on a regular basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and better services.
Download this asset to learn the volume and variety of data available today is creating new opportunities to improve your customers’ lives – from personalized recommendations to targeted advertising and intelligent services.
Sponsored by: HPE and Intel®
Published By: Pentaho
Published Date: Nov 04, 2015
Amid unprecedented data growth, how are businesses optimizing their data environments to ensure data governance while creating analytic value? How do they ensure the delivery of trusted and governed data as they integrate data from a variety of sources?
If providing appropriately governed data across all your data sources is a concern, or if the delivery of consistent, accurate, and trusted analytic insights with the best blended data is important to you, then don’t miss “Delivering Governed Data For Analytics At Scale,” an August 2015 commissioned study conducted by Forrester Consulting on behalf of Pentaho.
Published By: Oracle CX
Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better
Published By: Oracle CX
Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business,
mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and
enough compute power to deliver the performance required in a rapidly evolving digital marketplace.
Customers increasingly drive the speed of business, and organizations need to engage with customers
on their terms. The need to manage sensitive information with high levels of security as well as
capture, analyze, and act upon massive volumes of data every hour of every day has become critical.
These challenges will dramatically change the way that IT systems are designed, funded, and run
compared to the past few decades. Databases and Java have become the de facto language in which
modern, cloud-ready applications are written. The massive explosion in the volume, variety, and
velocity of data increases the need for secure and effective analytics so that organizations can make
Automation Anywhere’s flagship product is Automation Anywhere Enterprise – a RPA platform offering a variety of tools to help organisations develop, operate and manage RPA bots that automate data entry, data gathering and other repetitive, routine tasks usually carried out as part of high-volume, repetitive work (for example, service fulfilment work in call centres, shared-service centres, and back-office processing environments). Automation Anywhere Enterprise bots can add value both in unattended (server-based, lights-out operation) and attended (desktop-based, interactive) deployment configurations.
In this report, MWD Advisors digs deeper into the features and capabilities of Automation Anywhere’s product portfolio, analysing its fast-growth trajectory and highlighting large-scale implementations.
Published By: Dell EMC
Published Date: Nov 09, 2015
While the EDW plays an all-important role in the effort to leverage big data to drive business value, it is not without its challenges. In particular, the typical EDW is being pushed to its limits by the volume, velocity and variety of data.
Download this whitepaper and see how the Dell™ | Cloudera™ | Syncsort™ Data Warehouse Optimization – ETL Offload Reference Architecture can help.
Published By: Dell EMC
Published Date: Oct 08, 2015
To compete in this new multi-channel environment, we’ve seen in this guide how retailers have to adopt new and innovative strategies to attract and retain customers. Big data technologies, specifically Hadoop, enable retailers to connect with customers through multiple channels at an entirely new level by harnessing the vast volumes of new data available today. Hadoop helps retailers store, transform, integrate and analyze a wide variety of online and offline customer data—POS transactions, e-commerce transactions, clickstream data, email, social media, sensor data and call center records—all in one central repository.
U.S. Flood is a high-gradient, intricate peril incorporating various sources, and causing a variety of effects. It requires sophisticated models, data science, and analytics technology to properly understand and assess each risk.
Published By: IBM APAC
Published Date: Jun 21, 2019
Moving major, business-supporting applications to the cloud can be a challenge for a variety of reasons. You may have concerns about the physical migration of data, as data loss or business disruption stemming from a migration issue would be a disaster for the business. Security is another typical concern, as a data breach of your most sensitive applications—like SAP or Oracle— could prove highly damaging. Akin to security, data sovereignty is an issue for many businesses. Stringent compliance laws in some jurisdictions are dictating data “residency”; and in the cloud, it is not always clear where the data is housed.
Among managed cloud service users, 68% state that using such services helps them to better manage resource allocation and make SAP and Oracle costs more predictable.
In this paper, we will look at common concerns over deploying and optimally managing business-critical, legacy applications in the cloud. We consider the benefits of managed cloud services, and how your
What is a Data Lake?
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.
Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is 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.
Download to find out more now.
PwC surveyed 235 IT leaders and interviewed another 35 from large, medium, and small enterprises to understand the buying decisions of IT leaders, across a wide variety of networking components (i.e., switches, SDN, and infrastructure monitoring solutions) within the data center. This report highlights the survey and interview insights to help Enterprise IT leaders understand the trends and implications of multi cloud environments.
Published By: Evariant
Published Date: Sep 07, 2016
Marketers face a unique challenge to allocate resources across a variety of tactics to target key audiences that need their product or service – with limited information on what combination of products or services will have the optimum impact, which target audience members are ideal fits, and what allocations will provide the best return on investment to the organization. Healthcare has its own myriad of challenges, including many local, regional, and national options for consumers, service line variations, and disparate demographics. The good news is that there is an emerging understanding of digital and multichannel marketing, and ample opportunity to define best practices, systematically calculate marketing effectiveness and return on marketing investment (ROMI), and use technology and data to create great business outcomes.
Increasingly complex networks, require more than a one-size-fitsall
approach to ensuring adequate performance and data integrity.
In addition to the garden-variety performance issues such as slow
applications, increased bandwidth requirements, and lack of visibility
into cloud resources, there is also the strong likelihood of a malicious
While many security solutions like firewalls and intrusion detection
systems (IDS) work to prevent security incidents, none are 100 percent
effective. However, there are proactive measures that any IT team can
implement now that can help ensure that a successful breach is found
quickly, effectively remediated, and that evidential data is available in
the event of civil and/or criminal proceedings.
Empowered with mobile and cloud-based access to a myriad of products and services, customers now have a variety of options at their fingertips with regards to partnerships. Enterprises that do not follow the ever-changing tastes and preferences of their customers, or that wait too long to react, will fall behind and fail. Across functions, business professionals readily require big data tools and insights to understand and serve these customers. It is no longer an option for business users to rely on IT to deliver customer and other relevant analytics. On the flipside, handing the analytics reins entirely to business users can make governance nearly impossible. Organizations must find balance in a new approach in which IT mostly governs and curates data while business users are empowered to derive insights from data mostly ontheir own without delay.
Guru Labels, a specialist label printing company, deploys Sage Business Cloud Enterprise Management to replace a variety of stand-alone systems with a single, integrated solution that could bring together data from Guru Labels’ manufacturing, inventory, purchasing, finance, CRM an sales systems. It enables the business to improve job scheduling, reduce costs, retain margins and provide rapid responses to quotes that ultimately leads to high customer satisfaction rates.
The enormous volume, velocity and variety of data flooding the enterprise, along with the push for analytics and business intelligence, is creating a massive challenge that is overwhelming traditional storage approaches. As the demand for capacity continues to escalate, companies must be able to effectively and dynamically manage the storage supply, but also the demand for storage resources. The key is to optimize the infrastructure through standardization and virtualization, and replace manual tasks with policy-based automation.
For more and more organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements.
In fact, hybrid cloud is the new norm for IT. IDC says more than 80% of enterprise IT organizations will commit to hybrid cloud by 20171, and 70% of IT decision-makers say they will always have a mix of traditional IT and cloud architectures.2 With important applications and workloads architected across both on-premises and hybrid, public and private cloud environments, business and IT stakeholders must be able to access data with equal efficiency, reliability and speed—regardless of physical location, infrastructure type or time frame.
Every day, torrents of data inundate IT organizations and overwhelm
the business managers who must sift through it all to
glean insights that help them grow revenues and optimize
profits. Yet, after investing hundreds of millions of dollars into
new enterprise resource planning (ERP), customer relationship
management (CRM), master data management systems (MDM),
business intelligence (BI) data warehousing systems or big data
environments, many companies are still plagued with disconnected,
“dysfunctional” data—a massive, expensive sprawl of
disparate silos and unconnected, redundant systems that fail to
deliver the desired single view of the business.
To meet the business imperative for enterprise integration and
stay competitive, companies must manage the increasing variety,
volume and velocity of new data pouring into their systems from
an ever-expanding number of sources. They need to bring all
their corporate data together, deliver it to end users as quickly as
possible to maximize
Published By: MobileIron
Published Date: Mar 21, 2017
Over the past few years, organizations have used a variety of tools and technologies
to enable basic mobile device management (MDM) and essential apps like email and
calendar. But those capabilities are inadequate for companies that want to move beyond
the basics and transform their business processes by securely moving apps and data
to the cloud. For AirWatch customers, this means they should start evaluating leading
enterprise mobility management (EMM) platforms like MobileIron in order to achieve
their mobile transformation goals. Our platform is 100% focused on building today’s
modern enterprise architecture, which is quickly shifting core business processes away
from legacy technologies and standardizing on mobile devices and cloud services.
Anytime, anywhere access to work is now a basic need for the modern workforce. Whether remote, in the field or in the office, workers are no longer physically connected to your network or data center. Today’s employees work in a digital workspace that features virtualized laptops, desktop and workstations; a variety of personal systems and smart devices that may be part of BYOD programs and a diverse app ecosystem with desktop, remote, mobile, SaaS and Universal apps. In this mobile-cloud world, new and unpredictable forms of malicious software continue to evolve. Traditional network security, perimeter protection and firewalls are no longer enough to combat these new threats to the corporate IT infrastructure and company data integrity.
Published By: Datastax
Published Date: Dec 27, 2018
Today’s data volume, variety, and velocity has made relational database nearly obsolete for handling certain types of workloads. But it’s also put incredible strain on regular NoSQL databases. The key is to find one that can deliver the infinite scale and high availability required to support high volume, web-scale applications in clustered environments. This white paper details the capabilities and uses case of an Active Everywhere database