Empowering the Automotive Industry through Intelligent Orchestration
With the increasing complexity and volume of cyberattacks, organizations must have the capacity to adapt quickly and confidently under changing conditions. Accelerating incident response times to safeguard the organization's infrastructure and data is paramount. Achieving this requires a thoughtful plan- one that addresses the security ecosystem, incorporates security orchestration and automation, and provides adaptive workflows to empower the security analysts.
In the white paper "Six Steps for Building a Robust Incident Response Function" IBM Resilient provides a framework for security teams to build a strong incident response program and deliver organization-wide coordination and optimizations to accomplish these goals.
US ground forces handle massive amounts of information and data while working under unpredictable conditions. These conditions don’t always allow military intelligence analysts access to a technologically reliable way to share information. AI can help develop a comprehensive intelligence picture and a true sense of cognitive situational understanding (CSU). These technologies can help analyze the massive amounts of data the military receives. And because AI programs are constantly adding new capabilities and tools, they can help the military prepare for the battlefield of the future. Read how.
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.
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.
"Read the guide to learn five ways to overcome challenges to programmatic ads, including how to:
· Bring marketers, creatives, IT, and data analysts together to ensure success
· Save money and time while improving engagement and conversion
· Customize multiple versions of one campaign and serve ads with strong creative in real time"
Published By: Gigamon
Published Date: Oct 25, 2017
Read the Joint Solution Brief Accelerate Threat Detection and Response to learn how Gigamon helps Splunk Enterprise users effectively analyze and remediate network security threats. Benefits include enhanced visibility and deeper, faster security analytics from precise, targeted network metadata generated from the traffic flowing in your network. Also learn how automation of common security tasks, across the Gigamon platform and third-party security tools, from within the Splunk platform helps increase analyst efficiency and reduce errors.
If you are working with massive amounts of data, one challenge
is how to display results of data exploration and analysis in a
way that is not overwhelming. You may need a new way to look
at the data – one that collapses and condenses the results in an
intuitive fashion but still displays graphs and charts that decision
makers are accustomed to seeing. And, in today’s on-the-go
society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time.
SAS® Visual Analytics is a data visualization and business
intelligence solution that uses intelligent autocharting to help
business analysts and nontechnical users visualize data. It
creates the best possible visual based on the data that is
selected. The visualizations make it easy to see patterns and
trends and identify opportunities for further analysis.
Creating predictive analytics from alternative data has become the current focus of the biggest quant trading firms in the industry
The democratization of financial services data and technology, together with more intense competition, makes the needs of today’s market participants vastly different from those of previous generations. Firms must locate untapped sources of data for both public and non-public companies. This alternative data, such as payment data and other non-public information, from sources beyond the common channels, can be a predictive indicator of market performance; a difference maker in assisting firms as they develop models to evaluate their investments.
By combining our unique data sets with advanced analytics, traders, analysts and managers can seek predictive signals and actionable information utilizing their own models.
View our research report to learn how alternative data, our 'Information Alpha,' can help you earn differentiated investment returns.
Published By: Sage EMEA
Published Date: Jan 29, 2019
Transform your finance operations into a strategic, data-driven engine
Data inundation and information overload have burdened practically every largescale enterprise today, providing great amounts of detail but often very little context on which executives can act. According to the Harvard Business Review,1 less than half of an organisation’s structured data is actively used in making decisions.
The burden is felt profoundly among finance executives, who increasingly require fast and easy access to real-time data in order to make smart, timely, strategic decisions. In fact, 80% of analysts’ time is spent simply discovering and preparing data, and the average CFO receives information too late to make decisions 24% of the time.2
Published By: MarkLogic
Published Date: Jun 09, 2017
Your high-stakes data projects don’t have to end – as analysts predict – in failure. Don’t just rely on legacy technology and outdated thinking - the key is to start your next data project armed with the right technology and mindset to succeed.
This paper will give you insights and guidelines to help you learn how to leverage all of your data to reach your data integration objectives with less time and expense than you might imagine. Change is good, and in this paper we’ll give you real-world examples of organizations that embraced change and found success.
Published By: IBM APAC
Published Date: Aug 22, 2017
For any sized organization, securing data and networks today is a daunting task. New vulnerabilities are discovered almost daily; new malware strains are developed as soon as a detection script is written for the old ones; and cybercriminals can buy prepackaged exploit kits on the Darknet backed by professional support teams. As a security analyst, you need more than a few point solutions designed to defend the network’s edge. You need visibility, perspective and an innate sense of when things just don’t seem right.
Published By: Cognizant
Published Date: Oct 23, 2018
The implications of AI’s unique approach are profound: AI can learn by example rather than through brute-force programming; can understand human intention and emotions and act accordingly; and can handle extraordinarily complex relationships of data that are beyond the capability of human analysts working alone.
AI can multiply what we currently do and take us to experiences we’ve never had before, at a speed and scale that will change entire industries. In these case studies, we’re pleased to present a range of real-world examples to guide your imagination. Here, you’ll find situations where companies like yours found AI to be part of the solution. These examples show how AI can enhance an existing application, workflow or process and reduce friction.
This e-book presents how 10 organizations are using artificial intelligence to accelerate decision making, improve business processes, enhance user engagement, reduce costs and drive remarkable growth and profitability.
How are organizations balancing self-service analytics and data governance today? What are the trends for tomorrow?
Many organizations are on their way to achieving self-service analytics maturity through the use of intuitive data visualization technologies aimed at non-technical users; as well as various tactics that reduce reliance on IT. But handing the analytics reins entirely to business users can make governance nearly impossible. As a result, organizations are increasing investments in modern analytics platforms that enable a balance between IT governing and curating data, empowering business users to derive insights from data mostly on their own and without delay.
Join guest speaker, Forrester Research VP and Principal Analyst, Boris Evelson and Oracle Analytics Senior Group Director, Jose Villacis as they discuss insights from an Oracle-commissioned study of North American enterprise analytics leaders.
The Summer 2018 security report is about change: what’s new and unusual in DDoS attacks, where are the surprising data patterns, and how should enterprises and security professionals prepare for the unexpected. Looking back at November 2017 to April 2018, as well as year-over-year changes, Akamai analysts identified data trends that spotlight the new and unfamiliar. The Summer 2018 State of the Internet / Security: Web Attacks report covers atypical attack methods, credential abuse attacks and law enforcement prosecution of DDoS-for-hire platforms. Guest writer Rik Ferguson also explores future threat scenarios.
Finally, the Integrate SID for your records (and in case you need it) for this program is: 0E9175.
Anything else you need to hit the ground running with this program?
In this whitepaper, we describe how executive and IT management can get and maintain control of their company's data architecture to help meet business objectives. We describe the relationship between data integration projects and data architecture concepts and practices. We describe how the business planning and IT development processes that direct and leverage data integration projects depend on tooling. We describe breakthrough ways in which data architects, business analysts, programmers, and business users can collaborate to address their organization's pressing business challenges.
Mainframes continue to provide high business value by combining efficient transaction processing with high-volume access to critical enterprise data. Business organizations are linking mobile devices to mainframe processing and data to support digital applications and drive business transformation. In this rapidly growing scenario, the importance of providing excellent end-user experience becomes critical for business success.This analyst announcement note covers how CA Technologies is addressing the need for providing high availability and a fast response time by optimizing mainframe performance with new machine learning and analytics capabilities.
Traditional organizations across the globe are transforming to compete against digital-only players, in restructuring to put the customer first. The world’s buying behavior - and people’s behavior in relation to technology - is quickly changing in connection with online distribution channels, smart devices, and their interplay with offline touchpoints. Siloed business systems and their old reporting lines need to shift, and synchronize - fast.
Whilst businesses of all kinds are utilizing data analytics, many are still only using it to make simple changes that lead to a set of rigid processes. Whereas the more customer-focused organizations are realizing that to deliver exceptional experiences, they need to be able to react to customer data in real-time and predict what might happen next. And that means going beyond simple analytics.
Read our whitepaper to discover what analyst firm Forrester has identified as the Enterprise Insight Platform, technology designed to enable companies to transform into truly data-driven businesses.
Alice Bluebird, a quirky security analyst for hire, is hunting down a nation state of hackers thirsty for the recipes of Frothly, a cutting-edge craft brewery. Follow Alice as she works to solve the mystery of the breach. Did she catch the incident before the hackers managed to steal Frothly’s super secret formulas? Did the hackers act alone or — scarier yet In this light hearted graphic novel “Through the Looking Glass Table”, discover how machine data, as well as an analytics-driven platform, log management, SIEM, UEBA and SOAR solutions, can help anyone — IT managers and sophisticated SOC analysts — better understand and respond to incidents, breaches, phishing attempts, insider threats and more.— did they have help from the inside?
Published By: Trifacta
Published Date: Oct 25, 2018
The rise of the self-service analytics era has called for a more flexible, iterative approach to data preparation. But as you and your team look to invest in modern data preparation solutions, understanding how to best evaluate these technologies can be difficult. In Ovum’s first Decision Matrix report on self-service data preparation, analyst Paige Bartley takes a comprehensive look at the eight major data preparation vendors by assessing each company’s technology and execution.
Download this report to learn:
Which vendors Ovum ranks as leaders in self-service data prep
The strengths, weaknesses, opportunities and threats of all 8 data prep vendors
A detailed overview of the criteria Ovum utilized in their evaluation
Published By: Trifacta
Published Date: Feb 12, 2019
Over the past few years, the evolution of technology for storing, processing and analyzing data has been absolutely staggering. Businesses now have the ability to work with data at a scale and speed that many of us would have never thought was possible. Yet, why are so many organizations still struggling to drive meaningful ROI from their data investments? The answer starts with people. In this latest Data Science Central webinar, guest speakers Forrester Principal Analyst Michele Goetz and Trifacta Director of Product Marketing Will Davis focus on the roles and responsibilities required for today’s modern dataops teams to be successful. They touch on how new data platforms and applications have fundamentally changed the traditional makeup of data/analytics organizations and how companies need to update the structure of their teams to keep up with the accelerate pace of modern business. Watch this recorded webcast to learn: What are the foundational roles within a modern dataops team a
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