Published By: Panduit
Published Date: Sep 03, 2015
Capacity planning is one of the most difficult aspects of building a data center today, given the complexity and number of variables to consider.
This new White Paper, from leading solutions and innovation provider Panduit, brings fresh insight into the central issues facing data center planners both for initial “build” and for future growth, with valuable “real life” examples drawn from actual customer case studies.
Download now to understand how best to:
• Avoid capacity fragmentation: identify areas of “lost” or “stranded” capacity
• Establish “best fits” for capacity in your center
• Maintain equilibrium between the four critical elements of any effective data center management plan
• Implement proactive planning: speed decision-making and deployment
• Optimize existing resources
• Improve data center operations and efficiency
• Reduce OPEX
• Avoid unnecessary CAPEX by extending the life of your center.
It has been obvious for some time that the power distribution system within the data center is the key opportunity to focus upon in order to actively manage the rising costs of power and more specifically, identify problems and waste in real-time.
With future-thinking organizations sharing knowledge between Facilities and IT, the push for more intelligence within this rack-based power infrastructure has become urgent with higher rack power densities. In fact, proactive power management at all stages in the distribution chain within enterprise data centers has become the requirement to feed efficiency studies and data center infrastructure management (DCIM) style optimization initiatives.
The Internet of Things is growing fast: By 2025, IoT devices will transmit an estimated 90 zettabytes of data to their intended targets, according to IDC. Armed with information, businesses can revolutionise everything from fraud detection to customer service. But first, they need an architecture that supports real-time analytics so they can gain actionable insights from their IoT data.
Read the complete report sponsored by Google Cloud, and learn how to mitigate key IoT-related challenges.
Published By: Attunity
Published Date: Nov 15, 2018
With the opportunity to leverage new analytic systems for Big Data and Cloud, companies are looking for ways to deliver live SAP data to platforms such as Hadoop, Kafka, and the Cloud in real-time. However, making live production SAP data seamlessly available wherever needed across diverse platforms and hybrid environments often proves a challenge.
Download this paper to learn how Attunity Replicate’s simple, real-time data replication and ingest solution can empower your team to meet fast-changing business requirements in an agile fashion. Our universal SAP data availability solution for analytics supports decisions to improve operations, optimize customer service, and enable companies to compete more effectively.
Published By: Attunity
Published Date: Nov 15, 2018
Change data capture (CDC) technology can modernize your data and analytics environment with scalable, efficient and real-time data replication that does not impact production systems.
To realize these benefits, enterprises need to understand how this critical technology works, why it’s needed, and what their Fortune 500 peers have learned from their CDC implementations. This book serves as a practical guide for enterprise architects, data managers and CIOs as they enable modern data lake, streaming and cloud architectures with CDC.
Read this book to understand:
? The rise of data lake, streaming and cloud platforms
? How CDC works and enables these architectures
? Case studies of leading-edge enterprises
? Planning and implementation approaches
Location has become paramount to building new apps, services, experiences and business models. If data is the new oil, then location is the crude oil. This is why most of the top location platform players have been developing technologies to power next-generation autonomous mobility systems. And the “richness” of location data and real-time intelligence are becoming strong monetization opportunities.
The 2018 Counterpoint Research Location Ecosystems Update compared 16 location platform vendors, including Google, TomTom and Mapbox. Learn why the HERE Open Location Platform – described as super-rich, always up-to-date, and a neutral offering – is a leader in the location data arena.
How do you keep people safe in a ‘once in a 1,000 years’ weather event? Hurricane Harvey was a category four hurricane which struck the coast of Texas, eastern Texas and southwestern Louisiana in August 2017.
HERE was able to track the storm and accurately report more than 2,100 road closures and blockages in real-time helping people stay out of harm’s way.
HERE is the world’s leading provider of traffic incident information to the automotive industry. This eBook shows how HERE’s deploys its people and artificial intelligence to gather the data, check it for accuracy and produce insights which keeps drivers safe.
Car data consumption is critically important to auto manufacturers. As more vehicles are produced with built-in infotainment systems, the cost of supplying them with live information and real-time updates via a data connection grows ever greater.
Auto manufacturers need to be able to enhance the driving experience with smart traffic, navigation, and entertainment services, while reducing costs and data volumes.
HERE is the world’s leading provider of traffic data to the automotive industry. This eBook shows how HERE optimizes traffic solutions and it outlines how data use modelling, standardization, and good data management can help reduce usage.
Sage Business Cloud Enterprise Management offers you a comprehensive, real-time solution that delivers accurate, up-to-date data that identifies and mitigates the consequences of product recalls and other supply chain issues.
With Sage Business Cloud Enterprise Management, your food and beverage business will have a faster, simpler and flexible way to keep the costs and reputational damage of recalls to a minimum.
To stay ahead of the competition in a global marketplace, firms are increasingly speeding up operations, in many cases adopting real-time systems and tools to allow for instant decision-making and faster business cycles. Download here to learn how.
Effective workload automation that provides complete management level visibility into real-time events impacting the delivery of IT services is needed by the data center more than ever before. The traditional job scheduling approach, with an uncoordinated set of tools that often requires reactive manual intervention to minimize service disruptions, is failing more than ever due to todays complex world of IT with its multiple platforms, applications and virtualized resources.
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.
Data integration (DI) may be an old technology, but it is far from extinct. Today, rather than being done on a batch basis with internal data, DI has evolved to a point where it needs to be implicit in everyday business operations. Big data – of many types, and from vast sources like the Internet of Things – joins with the rapid growth of emerging technologies to extend beyond the reach of traditional data management software. To stay relevant, data integration needs to work with both indigenous and exogenous sources while operating at different latencies, from real time to streaming. This paper examines how data integration has gotten to this point, how it’s continuing to evolve and how SAS can help organizations keep their approach to DI current.
The spatial analytics features of the SAP HANA platform can help you supercharge your business with location-specific data. By analyzing geospatial information, much of which is already present in your enterprise data, SAP HANA helps you pinpoint events, resolve boundaries locate customers and visualize routing. Spatial processing functionality is standard with your full-use SAP HANA licenses.
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit
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.
DatacenterDynamics is a brand of DCD Group, a global B2B media and publishing company that develops products to help senior professionals in the world's most ICT dependent organizations make risk-based infrastructure and capacity decisions.
Our portfolio of live events, online and print publishing, business intelligence and professional development brands are centred on the complexities of technology convergence. Operating in 42 different countries, we have developed a unique global knowledge and networking platform, which is trusted by over 30,000 ICT, engineering and technology professionals.
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