More sophisticated cameras and vehicle sensors are enabling new ADAS features and the deployment of highly autonomous vehicles. However, reactive decisions and camera-based systems struggle when lane markings fade, snow or dirt covers the road, and the environment changes.
Map-based Lane Keeping with HERE HD Live Map from VSI Labs examines how HD map assets can improve the safety and performance of automated vehicle features.
Download this free report to learn:
• How map data improves the performance and safety of ADAS features
• How map-based systems outperform computer vision only system
• The architecture of VSI’s map-based lane keeping system
Infinidat provides the difference you seek in a data storage solution for media and entertainment organizations. New demands have everyone in the industry feeling the impact of high latency storage and its impact on efficiently delivering speed to market on new and dense workload management. The Infinidat unified storage architecture enables the scale, performance and best overall TCO required to deliver an extreme competitive advantage to media and entertainment companies.
When data center architecture extends beyond even moderate amounts of sophistication and complexity, it becomes a daunting challenge for operators to understand what is going on by relying on common tools and processes alone.
Read this eGuide for five recommendations that can help you make sense of your data.
As modernized data centers scale up and out, there is a strong potential for growing complexity as well. IT teams need to be vigilant in simplifying architectures and operations as the technological landscape changes.
While the potential of monitoring and analytics in your data center is huge, to take advantage, you'll need an architecture that can handle shifting traffic patterns.
In this expert eGuide, you'll discover three ways of simplifying architectures, and how they can help you reduce complexity, improve workforce efficiency, and ease administration.
Published By: Cohesity
Published Date: Aug 09, 2019
As organizations continue to look for ways to increase business agility, a need for a modern database architecture that can rapidly respond to the needs of business is more apparent than ever. While an RDBMS still serves as a lifeline for many organizations, the adoption of technologies such as NoSQL and Hadoop are enabling organizations to best address database performance and scalability requirements while also satisfying the goals of embracing hybrid cloud and becoming more data-driven. And with organizations relying so heavily on these new technologies to yield rapid insights that positively impact the business, the need to evaluate how those new technologies are managed and protected is essential. Hadoop and NoSQL workloads are now pervasive in production environments and require “production-class” data protection, yet few data protection solutions offer such capabilities today.
Published By: Cohesity
Published Date: Aug 09, 2019
IT organizations everywhere are undergoing significant transformation to keep pace with the needs of their businesses. They’re tasked with
consolidating data centers and migrating both workloads and data to the cloud. The transition has been easier for some than others.
As hybrid architectures increasingly become the norm, how are enterprises gaining complete visibility, simplifying management, and making use
of all of their data—both on-premises and in the cloud?
Five enterprises explain how they’ve replaced multiple products that created legacy data silos with Cohesity – a single, hyperconverged softwaredefined
platform with native Microsoft Azure integration for simplified secondary data and applications. For them, Cohesity and Azure together
boost IT agility while lowering costs, solving critical secondary data challenges from long-term retention, storage tiering, test/dev, disaster
recovery and cloud-native backup in a proven hybrid cloud architecture.
Published By: Cohesity
Published Date: Aug 09, 2019
Data for secondary workloads – backup, test/dev, disaster recovery, and archiving to name a few – have become siloed the same way application data has, leading to multiple point solutions to manage an increasing amount of data.
This white paper looks at the evolution of these challenges and offers practical advice on ways to store, manage and move secondary data in hybrid cloud architectures while extracting the hidden value it can provide.
Published By: Cisco EMEA
Published Date: Nov 13, 2017
The HX Data Platform uses a self-healing architecture that implements data replication for high availability, remediates hardware failures, and alerts your IT administrators so that problems can be resolved quickly and your business can continue to operate. Space-efficient, pointerbased snapshots facilitate backup operations, and native replication supports cross-site protection. Data-at-rest encryption protects data from security risks and threats. Integration with leading enterprise backup systems allows you to extend your preferred data protection tools to your hyperconverged environment.
Nimble Secondary Flash array represents a new type of data storage, designed to maximize both capacity and performance. By adding high-performance flash storage to a capacity-optimized architecture, it provides a unique backup platform that lets you put your backup data to work.
Nimble Secondary Flash array uses flash performance to provide both near-instant backup and recovery from any primary storage system. It is a single device for backup, disaster recovery, and even local archiving. By using flash, you can accomplish real work such as dev/test, QA, and analytics.
Deep integration with Veeam’s leading backup software simplifies data lifecycle management and provides a path to cloud archiving.
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
This paper explores the results of a survey, fielded in April 2013, of 304 data managers and professionals, conducted by Unisphere Research, a division of Information Today Inc. It revealed a range of practical approaches that organizations of all types and sizes are adopting to manage and capitalize on the big data flowing through their enterprises.
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
Over the course of several months in 2011, IDC conducted a research study to identify the opportunities and challenges to adoption of a new technology that changes the way in which traditional business solutions are implemented and used. The results of the study are presented in this white paper.
Forrester conducted in-depth surveys with 330 global BI decision-makers and found strong correlations between overall company success and adoption of innovative BI, analytics, and big data tools. In this paper, you will learn what separates the leading companies from the rest when it comes to exploiting innovative technologies in BI and analytics, and what steps you can take to either stay a leader or join their ranks.
This white paper, produced in collaboration with SAP, provides insight into executive perception of real-time business operations in North America. It is a companion paper to Real-time Business: Playing to win in the new global marketplace, published in May 2011, and to a series of papers on real-time business in Europe, Asia-Pacific and Latin America.
Leading companies and technology providers are rethinking the fundamental model of analytics, and the contours of a new paradigm are emerging. The new generation of analytics goes beyond Big Data (information that is too large and complex to manipulate without robust software), and the traditional narrow approach of analytics which was restricted to analysing customer and financial data collected from their interactions on social media. Today companies are embracing the social revolution, using real-time technologies to unlock deep insights about customers and others and enable better-informed decisions and richer collaboration in real-time.
Published By: HPE Intel
Published Date: Jan 11, 2016
A famous architect once said that the origin of architecture was defined by the first time “two bricks were put together well.” And the more bricks you have, the more important putting them together well becomes. The same holds true in our data centers. The architecture of our compute, storage and network devices has always been important, but as the demands on our IT infrastructures grow, and we add more “bricks,” the architecture becomes more critical.
Today’s data centers are expected to deploy, manage, and report on different tiers of business applications, databases, virtual workloads, home
directories, and file sharing simultaneously. They also need to co-locate multiple systems while sharing power and energy. This is true for large as
well as small environments. The trend in modern IT is to consolidate as much as possible to minimize cost and maximize efficiency of data
centers and branch offices. HPE 3PAR StoreServ is highly efficient, flash-optimized storage engineered for the true convergence of block, file,
and object access to help consolidate diverse workloads efficiently. HPE 3PAR OS and converged controllers incorporate multiprotocol support
into the heart of the system architecture
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