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.
Discover how to revolutionize processing performance, data intelligence, customer experiences, and GRC.
The future of financial services will belong to those who can capture and capitalize on data. And it all begins with employing modern data strategies in four critical areas.
You’ll learn how to:
Leverage AI, machine learning and predictive analytics.
Get scalable, high-speed access to vast amounts of data.
Respond faster, become more competitive, and attract new customers.
Published By: Gigamon
Published Date: Sep 03, 2019
The IT pendulum is swinging to distributed computing environments, network perimeters are dissolving, and
compute is being distributed across various parts of organizations’ infrastructure—including, at times, their extended
ecosystem. As a result, organizations need to ensure the appropriate levels of visibility and security at these remote
locations, without dramatically increasing staff or tools. They need to invest in solutions that can scale to provide
increased coverage and visibility, but that also ensure efficient use of resources. By implementing a common
distributed data services layer as part of a comprehensive security operations and analytics platform architecture
(SOAPA) and network operations architecture, organizations can reduce costs, mitigate risks, and improve operational
Getting complex decisions right across complicated operational networks is the key to optimum performance. Find out how one of the UK’s biggest bus operators is using data and analytics to make better decisions and optimise the use of resources across their network.
Read this story to discover:
• how data and analytics can transform operational performance
• the benefits of using decision-support tools in the middle office
• key lessons for getting your plans for digital transformation right.
"We live and surf in a cyber world where attacks like APT, DDOS, Trojans and Ransomware are common and easy to execute. Domain names are an integral part of any business today and apparently an integral part of an attacker's plan too.
Domain names are carriers of malwares, they act as Command and Control servers and malware's ex-filtrate data too. In today's threat landscape - predicting threats, spotting threats and mitigating them is super crucial.. This is called Visibility and Analytics.
Watch this on demand session with our Cisco cloud security experts Shyam Ramaswamy and Fernando Ferrari as they talk about how Cisco Umbrella and The Umbrella Research team detect anomalies, block threats and identify compromised hosts. The experts also discuss how effectively Cisco spot, react, filter out IOC, block the network communications of a malware; identify and stop a phishing campaign (unknown ones too).
The current trend in manufacturing is towards tailor-made products in smaller lots with shorter delivery times. This change may lead to frequent production modifications resulting in increased machine downtime, higher production cost, product waste—and the need to rework faulty products.
To satisfy the customer demand behind this trend, manufacturers must move quickly to new production models. Quality assurance is the key area that IT must support.
At the same time, the traceability of products becomes central to compliance as well as quality. Traceability can be achieved by interconnecting data sources across the factory, analyzing historical and streaming data for insights, and taking immediate action to control the entire end-to-end process. Doing so can lead to noticeable cost reductions, and gains in efficiency, process reliability, and speed of new product delivery. Additionally, analytics helps manufacturers find the best setups for machinery.
Today, you can improve product quality and gain better control of the entire
manufacturing chain with data virtualization, machine learning, and advanced
data analytics. With all relevant data aggregated, analyzed, and acted on, sensors,
devices, people, and processes become part of a connected Smart Factory
•? Increased uptime, reduced downtime
•? Minimized surplus and defects
•? Better yields
•? Reduced cost due to better quality
•? Fewer deviations and less non-conformance
Global producer of polycrystalline silicon for semiconductors, Hemlock Semiconductor needed to accelerate process optimization and eliminate cost. With TIBCO® Connected Intelligence, Hemlock achieved centralized, self-service, governed analysis; revenue gains; cost savings; and more.
Fueled by double-digit growth in the markets it serves, Hemlock Semiconductor is adapting to the increasing commoditization within the polysilicon industry and better positioning itself to compete. A key factor in this plan is to equip process-knowledgeable personnel with the skills and tools to accelerate delivery of process optimizations and associated cost elimination.
Hemlock turned to a TIBCO® Connected Intelligence solution to address the challenges. By implementing TIBCO Spotfire® and TIBCO® Streaming analytics, TIBCO® Data Science, and TIBCO® Data Virtualization, the company created more self-service analytics. Adding TIBCO BusinessWorks™ integration let the company realize the vision of connect
IBM has been named a Leader in Gartner's Magic Quadrant for Data & Analytics Services.
According to the report, by 2022, 90% of corporate strategies are expected to view information as a critical enterprise asset, and analytics as an essential competency. Data and analytics service providers can help leaders accelerate and transform their ability to deliver data-driven insights and innovation solutions to businesses. Get complimentary access to Gartner's latest Magic Quadrant report for Data & Analytics Service Providers.
Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.
I Big Data e gli analytics workloads sono la nuova frontiera per le aziende. I dati vengono raccolti da fonti che non esistevano 10 anni fa. Tutti i dati dei telefoni cellulari, i dati generati dalle macchine e i dati relativi all’interazione con i siti vengono raccolti e analizzati. Inoltre, con i budget IT sempre più sotto pressione, l’impatto ambientale dei Big Data non fa che aumentare e pone grandi sfi de per i sistemi storage.
Questo documento fornisce informazioni sulle problematiche che le applicazioni dei Big Data pongono sullo storage e su come scegliere le più corrette infrastrutture per ottimizzare e consolidare le applicazioni dei Big Data e degli analytics, senza prosciugare le fi nanze.
Organizations are charging ahead with investments in cloud and analytics to deliver agility, scalability and cost savings. With computing power advancements and continuous growth of data, cloud provides the elastic workloads and flexibility required for modern business. However, the environment of flexibility and choice that cloud provides also creates complexity and challenges.
In this white paper, learn how organizations are applying expertise and using the latest methods to move analytics to the cloud, including:
• Why are organizations moving analytic work to the cloud?
• What are the key challenges and misconceptions?
• How do IT leaders provide choice while maintaining control?
Envision this situation at a growing bank. Its competitive landscape demands an agile
response to evolving customer needs. Fortunately, analytically minded professionals in
different divisions are seeing results that positively affect the bottom line.
• A data scientist in the business development team analyzes data to create customized
• experiences for premium customers.
• A digital marketer tracks and influences the customer journey for prospective
• mortgage customers.
• A risk analyst builds risk models for the bank’s loan portfolios.
• A data analyst examines data about local customers.
• A technical architect defines a new system to protect bank data from internal and
• external cyberthreats.
• An application developer builds a new mobile app for online customer portfolio
Between them, these employees might be using more than a dozen packages for
analytics and data management.
TIBCO Data Virtualization is a proven approach used by four of the top five integrated energy companies to deliver more analytic data sooner from across upstream and downstream operations. Specific use cases described include: •? Offshore Platform Data Analytics •? Well Maintenance and Repair •? Cross Refinery Web Data Services •? SAP Master Data Quality If you are an energy company facing similar data and analytic challenges, consider TIBCO Data Virtualization.
While interest in Machine Learning/Artificial Intelligence/ (ML/AI) has never been higher, the number of companies deploying it is only a subset, and successful implementations a smaller proportion still. The problem isn’t the technology; that part is working great. But the mere presence and provision of tools, algorithms, and frameworks aren’t enough. What’s missing is the attitude, appreciation, and approach necessary to drive adoption and working solutions.
To learn more, join us for this free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and panelists Jen Stirrup, Lillian Pierson, and special guest from Cloudera Fast Forward Labs, Alice Albrecht. Our panel members are seasoned veterans in the database and analytics consulting world, each with a track record of successful implementations. They’ll explain how to go beyond the fascination phase of new technology towards the battened down methodologies necessary to build bulletproof solutions th
Why data-driven businesses stand out from the crowd.
Why Should the Target Audience Care?
Enterprises need to become more data-driven by using more mature analytics tools to stand out from the crowd
Smart, effective customer analytics tools helps organizations reap the rewards of increased customer satisfaction and brand loyalty. Neglecting advances in customer analytics technology could seriously impact a company's ability to compete in the future marketplace. Where do your customers and prospects sit on the customer analyticsmaturity scale? Are they leaders or are they laggards?
Read "Customer Analytics: The 20 Attributes that Lead to Business Success" for insights into:
• the key drivers needed within an organisation that help grow customer analytics maturity
• why companies using paid analytics solutions experience more tangible benefits than those using free analytics
• how to distinguish customer analytics leaders from laggards
Like the oxygen we breathe, journey analytics brings life to the customer behind those devices, over time getting to know their favorite pastry choice, when they’re most likely to buy gas, and how long they stay online while in the station’s café.
WHY SHOULD THE TARGET AUDIENCE CARE?
Business struggle to gain a holistic customer view — the skills to identify actionable insights from multichannel data are in short supply. If they could gain a holistic view of customer attributes and behaviors, they could make sure they get the right content at the right time.
If you want your customers to enjoy seamless, personalized experiences, you need to treat them like people. That means marketing to the person — not the device. When you know a customer’s interests, wants, and needs — perhaps even before they do — you’ve succeeded at becoming a true experience business. For some, this may require a shift from analytics as a tool to analytics as a way of life. It may also m
Today’s C-level executives expect data and analytics to provide them with speed and agility to deliver competitive advantage and to disrupt new markets. But, in today’s complex data environment exists a near paradox between these expectations, that companies will be able to rapidly deliver value using data and analytics--and the complexities of the data landscape, making it more difficult to find, govern, connect to and access the data needed to deliver that value.
Once thing is clear: if management expectation is to be met, simplifying connectivity is a must.In this white paper, veteran analyst Mike Ferguson, Managing Director of Intelligent Business Strategies explores how simplifying data access –connectivity –aligns expectations with data realities thus decreasing time to value.
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.
Published By: Mindfire
Published Date: May 07, 2010
In this report, results from well over 650 real-life cross-media marketing campaigns across 27 vertical markets are analyzed and compared to industry benchmarks for response rates of static direct mail campaigns, to provide a solid base of actual performance data and information.
Although data and analytics are highlighted throughout the popular press as well as in trade publications, too many managers think the value of this data processing is limited to a few numerically intensive fields such as science and finance. In fact, big data and the insights that emerge from analyzing it will transform every industry, from “precision farming” to manufacturing and construction. Governments must also be alert to the value of data and analytics as the enabler for smart cities. Institutions that master available data will leap ahead of their less statistically adept competitors through many advantages: finding hidden opportunities for efficiency, using data to become more responsive to clients, and developing entirely new and unanticipated product lines. The average time spent by most companies on the S&P 500 Index has decreased from an average of 60 to 70 years to only 22 years. There are winners and losers in the changes that come with the evolution of both technology
Why your data catalog won’t deliver significant ROI
According to Gartner, organizations that provide access to a curated catalog of internal and external data assets will derive twice as much business value from their analytics investments by 2020 than those that do not.
That’s a ringing endorsement of data catalogs, and a growing number of enterprises seem to agree. In fact, the global data catalog market is expected to grow from US$210.0 million in 2017 to US$620.0 million by 2022, at a Compound Annual Growth Rate (CAGR) of 24.2%.
Why such large and intensifying demand for data catalogs? The primary driver is that many organizations are working to modernize their data platforms with data lakes, cloud-based data warehouses, advanced analytics and various SaaS applications in order to grow profitable digital initiatives. To support these digital initiatives and other business imperatives, organizations need more reliable, faster access to their data.
However, modernizing data plat
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.
Published By: Cisco EMEA
Published Date: Mar 05, 2018
The competitive advantages and value of BDA are now widely acknowledged and have led to the shifting of focus at many firms from “if and when” to “where and how.” With BDA applications requiring more from IT infrastructures and lines of business demanding higher-quality insights in less time, choosing the right infrastructure platform for Big Data applications represents a core component of maximizing value. This IDC study considered the experiences of firms using Cisco UCS as an infrastructure platform for their BDA applications. The study found that Cisco UCS contributed to the strong value the firms are achieving with their business operations through scalability, performance, time to market, and cost effectiveness. As a result, these firms directly attributed business benefits to the manner in which Cisco UCS is deployed in the infrastructure.