analytical

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By: Carbon Black     Published Date: Apr 11, 2018
Adversaries, and cybercriminal organizations in particular, are building tools and using techniques that are becoming so difficult to detect that organizations are having a hard time knowing that intrusions are taking place. Passive techniques of watching for signs of intrusion are less and less effective. Environments are complicated, and no technology can find 100 percent of malicious activity, so humans have to “go on the hunt.” Threat hunting is the proactive technique that’s focused on the pursuit of attacks and the evidence that attackers leave behind when they’re conducting reconnaissance, attacking with malware, or exfiltrating sensitive data. Instead of just hoping that technology flags and alerts you to the suspected activity, you apply human analytical capacity and understanding about environment context to more quickly determine when unauthorized activity occurs. This process allows attacks to be discovered earlier with the goal of stopping them before intruders are able t
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     Carbon Black
By: Carbon Black     Published Date: Aug 14, 2018
Threat hunting is the proactive technique that’s focused on the pursuit of attacks and the evidence that attackers leave behind when they’re conducting reconnaissance, attacking with malware, or exfiltrating sensitive data. Instead of just hoping that technology flags and alerts you to the suspected activity, you apply human analytical capacity and understanding about environment context to more quickly determine when unauthorized activity occurs. This process allows attacks to be discovered earlier with the goal of stopping them before intruders are able to carry out their attack objectives.
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     Carbon Black
By: Dassault Systèmes     Published Date: Jul 21, 2017
Obtaining a first-mover competitive advantage or faster time-to-market requires a new wave in analytics. Dassault Systèmes remains a leading innovator in Product Lifecycle Management (PLM) and has invested heavily in analytical technologies to further drive business benefits for its customers in the related areas of planning, simulation, insight and optimization. This white paper examines the challenges peculiar to PLM and why Dassault Systèmes’ EXALEAD offers the most appropriate solution. It also clearly positions EXALEAD PLM Analytics alongside related technologies like BI, data-warehousing and Big Data solutions. Understand and implement PLM Analytics to access actionable information, support accurate decision-making, and drive performance.
Tags : product solutions, lifecycle management, tech products, data management tools, pdm, plm, process automation, product development speed, manufactures
     Dassault Systèmes
By: Teradata     Published Date: May 02, 2017
A Great Use of the Cloud: Recent trends in information management see companies shifting their focus to, or entertaining a notion for the first time of a cloud-based solution. In the past, the only clear choice for most organizations has been on-premises data—oftentimes using an appliance-based platform. However, the costs of scale are gnawing away at the notion that this remains the best approach for all or some of a company’s analytical needs. This paper, written by McKnight Consulting analysts William McKnight and Jake Dolezal, describes two organizations with mature enterprise data warehouse capabilities, that have pivoted components of their architecture to accommodate the cloud.
Tags : data projects, data volume, business data, cloud security, data storage, data management, cloud privacy, encryption, security integration
     Teradata
By: IBM     Published Date: Jul 05, 2016
Today's data-driven organization is faced with magnified urgency around data volume, user needs and compressed decision time frames. In order to address these challenges, while maintaining an effective analytical culture, many organizations are exploring cloud-based environments coupled with powerful business intelligence (BI) and analytical technology to accelerate decisions and enhance performance.
Tags : ibm, datamart on demand, analytics, cloud, hybrid cloud, business insight, knowledge management, enterprise applications, data management, business technology, data center
     IBM
By: IBM     Published Date: Jul 21, 2016
IBM's recently released DB2 version 11.1 for Linux, Unix and Windows (LUW) is a hybrid database that IBM says can handle transactional and analytic workloads thanks to its BLU Acceleration technology, which features an in-memory column store for analytical workloads that can scale across a massively parallel cluster.
Tags : ibm, db2. analytics, mpp, data wharehousing
     IBM
By: IBM APAC     Published Date: Aug 25, 2017
The world of business analytics is evolving rapidly, and while there are multiple emerging trends of note, two stand out as particularly impactful. First, there is an expanding and increasingly diverse audience of users that are becoming more analytically active. From mid-level Line-of-Business staff to senior executives on mahogany row, more users in more job functions are taking an increased level of ownership in the insight that fuels their decisions and the underlying data that supports that insight.
Tags : data integration, data security, data optimization, data virtualization, database security
     IBM APAC
By: EMC Corporation     Published Date: May 27, 2014
ESG Whitepaper: New security risks and old security challenges often overwhelm legacy security controls and analytical tools. This ESG white paper discusses why today's approach to security management—that depends on up-to-the-minute situational awareness and real-time security intelligence—means organizations are entering the era of big data security analytics.
Tags : emc, security operations, security analytics, intelligence-driven security, threat detection, security monitoring, critical incident response, security, data center
     EMC Corporation
By: Teradata     Published Date: May 12, 2015
We evaluate vendors that provide applications that integrate executional, operational and analytical marketing processes. Companies seeking a solution that integrates campaign management, marketing resource management and analytics should review this research.
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     Teradata
By: IBM Watson Health     Published Date: Jun 14, 2017
Learn how IBM Watson Health clinical application advisors helped Floyd Health Care System take full advantage of the platform’s many benefits. Business Challenge As part of its journey toward population health management, Floyd wanted to optimize the way it used the IBM® Phytel® solution from IBM Watson Health™ and take advantage of its analytical tools. Transformation With help from an IBM Watson Health clinical application advisor, Floyd expanded its IBM solutions and used their unique capabilities to progress toward a more robust population healthcare model by adding care coordination activities and improving key process measures.
Tags : floyd health care system, ibm, ibm watson health, analytics, healthcare
     IBM Watson Health
By: IBM     Published Date: Oct 17, 2016
Why do organizations seek to design effective multi-channel customer journeys? Because customers today demand it. Download this research study from Hypatia Research Group to learn how global organizations are successfully utilizing various analytical techniques like descriptive, diagnostic, predictive, prescriptive and cognitive analysis to create a successful omni-channel customer journey.
Tags : ibm, commerce, analytics, customer analytics, insights, research, customer journey, enterprise applications, business technology
     IBM
By: IBM     Published Date: Jan 30, 2017
Workforce analytics presents a world of opportunities to improve business effectiveness that we have only begun to explore. This report provides practical guidance on the critical 10 steps for the first 100 days of setting up an analytically enabled HR function.
Tags : ibm, analytics, workforce analytics
     IBM
By: IBM     Published Date: Feb 27, 2017
Why do organizations seek to design effective multi-channel customer journeys? Because customers today demand it. Download this research study from Hypatia Research Group to learn how global organizations are successfully utilizing various analytical techniques like descriptive, diagnostic, predictive, prescriptive and cognitive analysis to create a successful omni-channel customer journey.
Tags : hypatia research group, cognitive analysis, predictive analysis, customer journey
     IBM
By: IBM     Published Date: Oct 17, 2017
Banks today are continuously challenged to meet rigorous regulatory requirements. They must implement strict governance programs that enable them to comply with a wide variety of regulations stemming from the financial crisis that began in 2007, including the DoddFrank Act, Basel Committee on Banking Supervision regulations, the General Data Protection Regulation (GDPR), the Revised Payment Services Directive (PSD2) and the revised Markets in Financial Instruments Directive (MiFID2). Many of these new regulations are spurring banks to rethink how data from across the enterprise flows into the aggregated risk and capital reports required by regulatory agencies. Data must be complete, correct and consistent to maintain confidence in risk reports, capital reports and analytical analyses. At the same time, banks need ways to monetize, grant access to and generate insight from data
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     IBM
By: Alteryx, Inc.     Published Date: Apr 21, 2017
Data Analytics has become critical for many business decision makers. However, many of these managers and data analysts still rely on spreadsheets and other legacy-era tools that fall far short of current needs. As a result, they also rely heavily on a virtual army of data specialists and scientists, working under the auspices of a centralized analytics group, to prepare, blend, analyze, and even report on the critical data they need for decision making. Download this new paper to get the details behind self-service data analytics, and how it lets business analysts: Take charge of the entire analytical process, instead of relying on other departments Overcome limitations of legacy tools to save time and prevent errors Make more comprehensive and insightful business decisions at speed
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     Alteryx, Inc.
By: Group M_IBM Q1'18     Published Date: Feb 15, 2018
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
Tags : analytics assessment, business decisions, predictive analytics, analytics
     Group M_IBM Q1'18
By: IBM     Published Date: Jun 04, 2018
"What would you do if you didn’t have to rely on disparate analytics solutions to meet the needs of business users while following the rules of IT? View this 'Charting Your Analytical Future' webinar to learn about a world of innovation and independence for users that does not limit the confidence and controls of IT. With the cognitive-guided self-service features available in IBM business analytics solutions, more users than ever before can get the answers they need. Next-generation business analytics capabilities make it possible to access relevant data, prepare it for analysis and understand performance. But it doesn’t stop there. Users can package the results in a visually-appealing format and share them throughout the organization. Don’t miss this opportunity to hear how you can: * Benefit from advanced analytics without the complexity * Operationalize insights and dashboards from a collection of trusted data sources * Tell your story with rich visualizations and geospati
Tags : business analytics, analytics solutions
     IBM
By: IBM     Published Date: Jul 09, 2018
As the information age matures, data has become the most powerful resource enterprises have at their disposal. Businesses have embraced digital transformation, often staking their reputations on insights extracted from collected data. While decision-makers hone in on hot topics like AI and the potential of data to drive businesses into the future, many underestimate the pitfalls of poor data governance. If business decision-makers can’t trust the data within their organization, how can stakeholders and customers know they are in good hands? Information that is not correctly distributed, or abandoned within an IT silo, can prove harmful to the integrity of business decisions. In search of instant analytical insights, businesses often prioritize data access and analysis over governance and quality. However, without ensuring the data is trustworthy, complete and consistent, leaders cannot be confident their decisions are rooted in facts and reality
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     IBM
By: Group M_IBM Q119     Published Date: Mar 04, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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     Group M_IBM Q119
By: Group M_IBM Q119     Published Date: Mar 11, 2019
In this paper, we focus on the DWA and how it has evolved over the years since its introduction. The XDW architecture is then described, in which the need to maintain the data warehouse is documented while adding new components and capabilities to extend the analytical capabilities. This section also discusses the appropriate usage of appliances within the XDW. The rest of the paper covers the benefits from implementing the DWA, the selection considerations for them and what the future holds for them.
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     Group M_IBM Q119
By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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     Group M_IBM Q2'19
By: SAS     Published Date: May 24, 2018
Information on artificial intelligence (AI) is flooding the market, media and social channels. Without doubt, it’s certainly a topic worth the attention. But, it can be difficult to sift through market hype and grandiose promises to understand exactly how AI can be applied in practical and reliable solutions. Like most technological advances, incorporating new technology into business processes requires significant leadership and effective direction that all stakeholders can easily understand. Great leaders become great by balancing strategy with tactics, future vision with current reality and strengths with weaknesses – all with the goal of accomplishing a clearly defined objective. Great leaders also understand that people are the most valuable resources within their organization. To drive and inspire their success, you must optimize strengths while recognizing inherent weaknesses. Many of our daily human experiences and interactions involve machines or devices of some sort. Technolo
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     SAS
By: Oracle     Published Date: Nov 06, 2012
The purpose of this white paper is to take a time-to-business-value look at financial services data warehousing technologies with a focus on the selection process and how it should take deeper considerations of the real-world implementation hurdles.
Tags : oracle, data, analytical data, data marts, industry-specific data warehouse, financial services, business technology
     Oracle
By: Oracle     Published Date: Nov 06, 2012
The purpose of this white paper is to take a time-to-business-value look at financial services data warehousing technologies with a focus on the selection process and how it should take deeper considerations of the real-world implementation hurdles.
Tags : oracle, data, analytical data, data marts, industry-specific data warehouse, financial services
     Oracle
By: Oracle     Published Date: Jan 28, 2015
Retailers continue to collect this data and many have made good use of it, segmenting and targeting customers and rewarding loyal behavior with discounts and offers. Still, many sense that there’s untapped potential. They’re right. With the cost of data storage plummeting and the capabilities of analytical tools on the rise, this data’s value is set to skyrocket. John Bible, Senior Director of Retail Data Science and Insight at Oracle Retail shares his view on how insights from these vast data storehouses can scientifically inform retailers’ decision-making in critical strategic, tactical and operational areas, including category management, shelf space allocation and new product introductions.
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     Oracle
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