Four ways to boost border intelligence with data and analytics

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With thousands of people worldwide crossing borders every day, how can security officials quickly and accurately uncover potential threats and determine which cases warrant further investigation?

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Four ways to boost border intelligence with data and analytics

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Risk management is increasingly becoming a strategic, executive-sponsored solution that many organizations view as providing a competitive advantage. When companies have an aggregated view of all the different kinds of risk and compliance data, they can start to generate insights about how to run the business better. In this presentation, learn why and how to empower business leaders to make more risk-aware decisions with visibility across controls and associated issues and actions throughout the organization.

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As they compete in the modern business environment, companies are increasingly looking to sophisticated analytics and cognitive capabilities to help them gain a deep understanding of what matters to their clients. By knowing their customers well, organizations can provide targeted, personalized service that adds value and heightens customer loyalty. When they do, they can avoid churn while generating additional revenue models by creating meaningful cross-selling opportunities in a customer-centric world. Explore this ebook to discover a wide array of uses for client insights in banking and wealth management.

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Some people think data scientists are mythical beings, like unicorns, or they are some sort of nouveau fad that will quickly fade. Not true, says IBM big data evangelist James Kobielus. In this engaging presentation, with artwork created by Angela Tuminello, Kobielus debunks 10 myths about data scientists and their role in analytics and big data. You might also want to read the full blog by Kobielus that spawned this presentation: "Data Scientists: Myths and Mathemagical Superpowers" - http://ibm.co/PqF7Jn For more information, visit http://www.ibmbigdatahub.com

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Presentation given by Dr. Diego Kuonen, CStat PStat CSci, on November 20, 2013, at the "IBM Developer Days 2013" in Zurich, Switzerland. ABSTRACT There is no question that big data has hit the business, government and scientific sectors. The demand for skills in data science is unprecedented in sectors where value, competitiveness and efficiency are driven by data. However, there is plenty of misleading hype around the terms big data and data science. This presentation gives a professional statistician's view on these terms and illustrates the connection between data science and statistics. The presentation is also available at http://www.statoo.com/BigDataDataScience/.

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Modern enterprises are vulnerable to a wide range of threats that can put customers, employees and even the organization’s brand at serious risk. Staying ahead of diverse threats as they evolve requires not only continuous monitoring and analysis of disparate data sets but also the fusing of the resulting insights into a single intelligence picture. This allows organizations to gain a comprehensive understanding of the diverse threats and vulnerabilities that can put the entire enterprise at risk. Noting that defense and national security agencies have employed this ongoing analysis and fusion approach for years, commercial organizations and civilian government agencies have begun adopting similar processes when setting up security operations centers and fusion centers. Whether you have a fusion center or are simply seeking to understand and mitigate your threats, IBM i2 Enterprise Insight Analysis can help you develop a comprehensive approach to enterprise intelligence with which you can neutralize the threats that menace your enterprise.

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Information is the principle driver of competitive advantage. How it is collected, analysed and communicated determines our success. No single resource is more critical to organisational survival. The amount of data in the world is exponentially increasing, to a point where companies capture significant amounts of information about their customers, suppliers, and operations. Millions of networked sensors are being embedded in everything from mobile phones to cars. Social networks and location data from mobile devices will continue to fuel this exponential data growth. These huge data pools are commonly being referred to as "big data". This talk examines how analytics and big data are exploiting information to drive competitive advantage.

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In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. Organizations can then use these insights to strengthen customer relationships, improve service delivery and drive new opportunities. To help guide the processes and activities within a given domain, data scientists and engineers need a foundational methodology that provides a framework for how to proceed with whichever methods or tools they will use to obtain answers and deliver results. In this presentation, we will share data science tips for data engineers. Join the Data Science Experience: http://ibm.co/data-science

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Enterprises are increasingly evolving their data infrastructures into entire cloud-facing environments. Interfacing private and public cloud data assets is a hallmark of initiatives such as logical data warehouses, data lakes and online transactional data hubs. These projects may involve deploying two or more of the following cloud-based data platforms into a hybrid architecture: Apache Hadoop, data warehouses, graph databases, NoSQL databases, multiworkload SQL databases, open source databases, data refineries and predictive analytics. Data application developers, data scientists and analytics professionals are driving their organizations’ efforts to bridge their data to the cloud. Several questions are of keen interest to those who are driving an organization’s evolution of its data and analytics initiatives into more holistic cloud-facing environments: • What is a hybrid cloud data services architecture? • What are the chief applications and benefits of a hybrid cloud data services architecture? • What are the best practices for bridging a logical data warehouse to the cloud? • What are the best practices for bridging advanced analytics and data lakes to the cloud? • What are the best practices for bridging an enterprise database hub to the cloud? • What are the first steps to take for bridging private data assets to the cloud? • How can you measure ROI from bridging private data to public cloud data services? • Which case studies illustrate the value of bridging private data to the cloud? Sign up now for a free 3-month trial of IBM Analytics for Apache Spark and IBM Cloudant, IBM dashDB or IBM DB2 on Cloud. http://ibm.co/ibm-cloudant-trial http://ibm.co/ibm-dashdb-trial http://ibm.co/ibm-db2-trial http://ibm.co/ibm-spark-trial

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Big data and analytics present many possibilities for emergency management specialists and first responders. Some of these benefits include pinpointing vulnerabilities, bringing in the right resources and maximizing existing resources to pave the way to adoption. However, these opportunities are not without challenges. Emergency management experts Adam Crowe, Director, Emergency Preparedness at Virginia Commonwealth University; William Moorhead, President of All Clear Emergency Management Group; and Gary Nestler, Associate Partner and Global Leader, Emergency Management solutions at IBM discuss these challenges and opportunities in this slideshare—which is intended to help disaster management stakeholders achieve the most accurate situational awareness using analytics. Discover analytics solutions for emergency management http://ibm.co/emergencymgmt

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Cognitive analytics is innovating and evolving rapidly. Expert predictions in this area are essential for organizations that plan to leverage cognitive analytics in their big data analytics strategies in 2016 and beyond. It is the core investment that organizations everywhere should make to stay relevant in the insight economy. IBM is the premier solution provider, with IBM Watson as its flagship cognitive analytics platform, for realizing the opportunities this innovative technology makes possible. Learn more about IBM Analytics at http://ibm.co/advancedanalytics

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Citizens today want to create a better tomorrow for our children and grandchildren. Looking at our world, Jen Q. Public sees the opportunity that analytics, the Internet of Things and the cognitive era bring to our cities, schools and governments. This collection of stories and cartoons explore use cases related to these advancements. Read the latest entry at http://ibm.co/jenqpublic and learn more about analytics for government today http://ibm.co/governmentanalytics

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Digital, social and mobile technologies have primed consumers to expect convenient, personalized interactions and fast, easy access to information. IBM Consumer Insights and Engagement integrates consumer data, analytics and marketing systems of engagement. For more information and to see how companies are using predictive analytics to engage customers and drive results, visit: http://ibm.co/consumeranalytics

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