data and analytics

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Published By: IBM     Published Date: Jul 22, 2016
This research report examines the key issues, and provides recommendations for leveraging data and analytics to help procurement drive greater enterprise value. Based on in-depth interviews with two dozen leading Chief Procurement Officers (CPOs), the report outlines pragmatic steps that every procurement organization can take to leverage analytics and improve engagement with suppliers and key business stakeholders across the enterprise.
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ibm, commerce, procurement, analytics, procurement analytics, data, big data, procurement organization, business technology
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. Download this white paper to learn how.
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database, big data, analytics, infrastructure, data management, data center
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, idc, big data, data, analytics, information governance, knowledge management, enterprise applications, data management, data center
    
IBM
Published By: IBM     Published Date: Oct 21, 2016
Between the Internet of Things, customer experience and loyalty programs, social network monitoring, connected enterprise systems and other information sources, today's organizations have access to more data than they ever had before-and frankly, more than they may know what to do with. The challenge is to not just understand that data, but actualize it and use it to recognize real business value. This ebook will walk you through a sample scenario with Albert, a data scientist who wants to put text analytics to work by using the Word2vec algorithm and other data science tools.
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ibm, analytics, aps, aps data, open data science, data science, word2vec, enterprise applications, business technology, data center
    
IBM
Published By: IBM     Published Date: Jan 05, 2017
This research report examines the key issues, and provides recommendations for leveraging data and analytics to help procurement drive greater enterprise value. Based on in-depth interviews with two dozen leading Chief Procurement Officers (CPOs), the report outlines pragmatic steps that every procurement organization can take to leverage analytics and improve engagement with suppliers and key business stakeholders across the enterprise.
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ibm, procurement, commerce, procurement analytics, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Jan 19, 2017
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, analytics, ecm, data, big data, information governance, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-c entric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
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IBM
Published By: IBM     Published Date: Jan 27, 2017
Analytics relies on BI, Big Data, and data discovery to provide reporting, trend what-if analysis. Analytics is transforming data into insight.
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ibm, analytics, business intelligence, data, data management
    
IBM
Published By: IBM     Published Date: Jan 30, 2017
Analytics has permeated, virtually, every department within an organization. It’s no longer a ‘nice to have’. It’s an organizational imperative. HR, specifically, collects a wealth of data; from recruiting applications, employee surveys, performance management data and it sits in systems that remain largely untapped. This data can help drive strategic decisions about your workforce. Analytic tools have, historically, been difficult to use and required heavy IT lifting in order to get the most out of them. What if an analytics system learned and continue to learn as it experienced new information, new scenarios, and new responses. This is referred to as Cognitive Computing and is key to providing an analytics system that is easy to use but extremely powerful.
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ibm, talent analytics, cognitive computing, analytics, engagement
    
IBM
Published By: IBM     Published Date: Apr 03, 2017
Businesses today certainly do not suffer from a lack of data. Every day, they capture and consume massive amounts of information that they use to make strategic and tactical decisions. Yet organizations often lack two critical capabilities when it comes to making the right decisions for the business: the ability to make accurate predictions about the future, and to then use those predicted insights in conjunction with organizational goals to identify the best possible actions they should take. The combination of predictive analytics and decision optimization provides organizations with the ability to turn insight into action. Predictive analytics offers insights into likely scenarios by analyzing trends, patterns and relationships in data. Decision optimization prescribes best-action recommendations given an organization’s business goals and business dynamics, taking into account any tradeoffs or consequences associated with those actions.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources, data optimization
    
IBM
Published By: IBM     Published Date: Apr 03, 2017
Predictive analytics is powerful. It can help drive significant improvement to an organization’s bottom line. Look for ways to use it to grow revenue, shrink costs and improve margins. Provide a platform that enables your data scientists to work efficiently using tools and algorithms they prefer. Enhance your analyses with internal and external data, structured and unstructured data. Then make the analytics accessible in order to reap the full benefits of these valuable analyses. Stay ahead of the curve in your market with predictive analytics, and give your organization a competitive advantage and an improved bottom line.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
The growing need for organizations to treat information as an asset is making metadata management strategic, driving significant growth for metadata management solutions. We evaluate nine vendors to help data and analytics leaders find the solution that best suits the needs of their organization.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection, metadata, business meta data, market data
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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customer analytics, data analysis, competitive advantage, understanding your customer base
    
IBM
Published By: IBM     Published Date: May 01, 2017
If you function like most IT organizations, you've spent the past few years relying on mobile device management (MDM), enterprise mobility management (EMM) and client management tools to get the most out of your enterprise endpoints while limiting the onset of threats you may encounter. In peeling back the onion, you'll find little difference between these conventional tools and strategies in comparison to those that Chief Information Officers (CIOs) and Chief Information Security Officers (CISOs) have employed since the dawn of the modern computing era. Their use has simply become more: Time consuming, with IT trudging through mountains of endpoint data; Inefficient, with limited resources and limitless issues to sort through for opportunities and threats; and Costly, with point solution investments required to address gaps in OS support across available tools. Download this whitepaper to learn how to take advantage of the insights afforded by big data and analytics thereby usher i
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ibm, endpoint management, mobile device management, enterprise mobility, os support, it organizations
    
IBM
Published By: IBM     Published Date: Jun 21, 2017
There are many types of databases and data analysis tools to choose from when building your application. Should you use a relational database? How about a key-value store? Maybe a document database? Is a graph database the right ft? What about polyglot persistence and the need for advanced analytics? If you feel a bit overwhelmed, don’t worry. This guide lays out the various database options and analytic solutions available to meet your app’s unique needs. You’ll see how data can move across databases and development languages, so you can work in your favorite environment without the friction and productivity loss of the past.
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data analysis, key value, document database, analytics
    
IBM
Published By: IBM     Published Date: Jun 21, 2017
NoSQL databases and Apache Spark are a potent combination for rapid integration, transformation and analysis of all kinds of business data. With its data syncing and analytics capabilities, IBM Cloudant offers unique advantages as a NoSQL database for many Spark use cases. IT decision-makers, data scientists and developers need to know how and when to apply these technologies most effectively. IBM can offer a host of resources and tools to help your organization gain value from Cloudant and Spark quickly, and with minimal up-front investment.
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ibm, ibm cloudant, apache spark, nosql, database
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base. High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-centric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
Tags : 
customer analytics, data matching, big data, competitive advantage, customer loyalty
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
The headlines are ablaze with the latest stories of cyberattacks and data breaches. New malware and viruses are revealed nearly every day. The modern cyberthreat evolves on a daily basis, always seeming to stay one step ahead of our most capable defenses. Every time there is a cyberattack, government agencies gather massive amounts of data. To keep pace with the continuously evolving landscape of cyberthreats, agencies are increasingly turning toward applying advanced data analytics to look at attack data and try to gain a deeper understanding of the nature of the attacks. Applying modern data analytics can help derive some defensive value from the data gathered in the aftermath of an attack, and ideally avert or mitigate the damage from any future attacks.
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cyber attacks, data breach, advanced data analytics, malware
    
IBM
Published By: IBM     Published Date: Aug 24, 2017
Data governance is all about managing data, by revising that data to standardize it and bring consistency to the way it is used across numerous business initiatives. What’s more, data governance ensures that critical data is available at the right time to the right person, in a standardized and reliable form. A benefit that fuels better organization of business operations, resulting in improved productivity and efficiency of that organization. Thus, the importance of proper data governance cannot be understated. The concepts of data governance have evolved, where the first iteration of data governance, often referred to as version 1.0, focused on three simplistic elements: objectives, structure and processes; having a limited focus and scope due to its tactical usage. The opportunity from the growing value of data in the realm of analytics, business intelligence, and generating insights was left unrealized. Today, organizations are moving towards what can be called Data Governance 2.0,
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ibm, unified governance strategy, data management, data governance
    
IBM
Published By: IBM     Published Date: Sep 28, 2017
Here are the 6 reasons to change your database: Lower total cost of ownership Increased scalability and availability Flexibility for hybrid environments A platform for rapid reporting and analytics Support for new and emerging applications Greater simplicity Download now to learn more!
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scalability, hybrid environment, emerging applications, rapid reporting
    
IBM
Published By: IBM     Published Date: Oct 16, 2017
This white paper examines how some of the ways organizations use big data make their infrastructures vulnerable to attack. It presents recommended best practices organizations can adopt to help make their infrastructures and operations more secure. And it discusses how adding advanced security software solutions from IBM to their big-data environment can fill gaps that big-data platforms by themselves do not address. It describes how IBM® Security Guardium®, an end-to- end solution for regulatory compliance and comprehensive data security, supports entitlement reporting; user-access and activity monitoring; advanced risk analytics and real-time threat detection analytics; alerting, blocking, encryption and other data protection capabilities, as well as automated compliance workflows and reporting capabilities, to stop threats.
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security, big data, ibm, data protection
    
IBM
Published By: IBM     Published Date: Oct 17, 2017
The data quality tools market continues to show strong revenue growth, driven by cost, process optimization and digital business initiatives. Applying data quality tools to existing and emerging business scenarios will enable data and analytics leaders to deliver greater business value.
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IBM
Published By: IBM     Published Date: Nov 30, 2017
Analyst firm, Enterprise Strategy Group, examines how companies can leverage cloud-based data lakes and self-service analytics for timely business insights that weren’t possible until now. And learn how IBM Cloud Object Storage, as a persistent storage layer, powers analytics and business intelligence solutions on the IBM Cloud. Complete the form to download the analyst paper.
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analytics, technology, digital transformation, data lake, always-on data lake, ibm, cloud-based analytics
    
IBM
Published By: IBM     Published Date: Jun 04, 2018
"The appearance of your reports and dashboards – the actual visual appearance of your data analysis -- is important. An ugly or confusing report may be dismissed, even though it contains valuable insights about your data. Cognos Analytics has a long track record of high quality analytic insight, and now, we added a lot of new capabilities designed to help even novice users quickly and easily produce great-looking and consumable reports you can trust. Watch this webinar to learn: • How you can more effectively communicate with data. • What constitutes an intuitive and highly navigable report • How take advantage of some of the new capabilities in Cognos Analytics to create reports that are more compelling and understandable in less time. • Some of the new and exciting capabilities coming to Cognos Analytics in 2018 (hint: more intelligent capabilities with enhancements to Natural Language Processing, data discovery and Machine Learning)."
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data analysis, data analytics, dashboards
    
IBM
Published By: IBM     Published Date: Jun 04, 2018
"Today’s business users want to use all types of data to create compelling, shareable visualizations. But charts and graphs alone may not convey all the information, especially when they are part of a complex series. An audience can best understand analytic results when those results tell a story that connects all the pieces together. The right visuals can also reinforce the lessons buried in the data. Stories are powerful mechanism to communicate with people. Stories stick and make insights actionable, so it goes without saying that storytelling is a very powerful (soft) skill. In this webinar, you'll learn how to effectively apply storytelling best practices to get your message across. Especially in the world of BI, it is getting more and more important to effectively communicate business results. Watch this webinar to learn how to use IBM Cognos Analytics to: · Create the important elements of a good story · Put the data in context · Select the best type of ch
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data analytics, data storytelling, business intelligence
    
IBM
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