data and analytics

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Published By: TIBCO Software GmbH     Published Date: Jan 15, 2019
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 no 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.
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TIBCO Software GmbH
Published By: TIBCO Software GmbH     Published Date: Jan 15, 2019
Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202
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TIBCO Software GmbH
Published By: TIBCO Software GmbH     Published Date: Jan 22, 2019
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution. Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze. Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform. Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing: • Reduced downtime • Minimized surplus and defects • Deep insights • End-to-end real-time visibility
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TIBCO Software GmbH
Published By: SAS     Published Date: Oct 22, 2015
The Internet of Things (IoT) presents an opportunity to collect real-time information about every physical operation of a business. From the temperature of equipment to the performance of a fleet of wind turbines, IoT sensors can deliver this information in real time. There is tremendous opportunity for those businesses that can convert raw IoT data into business insights, and the key to doing so lies within effective data analytics. To research the current state of IoT analytics, Blue Hill Research conducted deep qualitative interviews with three organizations that invested significant time and resources into their own IoT analytics initiatives. By distilling key themes and lessons learned from peer organizations, Blue Hill Research offers our analysis so that business decision makers can ultimately make informed investment decisions about the future of their IoT analytics projects.
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SAS
Published By: SAS     Published Date: Nov 04, 2015
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.
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data visualization, sas, big data, visual analytics, data exploration, analysis, networking, knowledge management, data management
    
SAS
Published By: IBM APAC     Published Date: Jul 09, 2017
Organizations today collect a tremendous amount of data and are bolstering their analytics capabilities to generate new, data-driven insights from this expanding resource. To make the most of growing data volumes, they need to provide rapid access to data across the enterprise. At the same time, they need efficient and workable ways to store and manage data over the long term. A governed data lake approach offers an opportunity to manage these challenges. Download this white paper to find out more.
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data lake, big data, analytics
    
IBM APAC
Published By: Amazon Web Services     Published Date: Jul 25, 2018
What is a Data Lake? Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes. This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Defining the Data Lake “Big data” is an idea as much as a particular methodology or technology, yet it’s an idea that is enabling powerful insights, faster and better decisions, and even business transformations across many industries. In general, big data can be characterized as an approach to extracting insights from very large quantities of structured and unstructured data from varied sources at a speed that is immediate (enough) for the particular analytics use case.
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Amazon Web Services
Published By: Sage EMEA     Published Date: Dec 19, 2018
Do you know your people as well as you know your customers? Your people’s expectations and the way they work is changing. Employees are more diverse, mobile and technologically-savvy than ever before. HR processes are changing from focusing on transactions to knowing and engaging people. Just as sales and marketing teams use data to develop actionable and informed insights about their customers, you need to do the same in HR to know your people. Everything, from attracting and keeping the best talent, to creating better workplace experiences and increasing employee engagement and productivity, depends on smarter decisions. These in turn rely on more actionable insights. These are only possible through accurate HR data and analytics. They are vital to address the people challenges you face, so you can make smarter decisions. Discover in this guide how to improve visibility of your workforce with data-driven and actionable insights. Ultimately, it will help you know your people better an
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Sage EMEA
Published By: Infor     Published Date: Jan 03, 2011
You need a path through this madness.In this recorded webicast, Steve Muran will take you through a case study of how he methodically built and managed a cross-enterprise, multichannel program that deepened the customer wallet share. Steve will discuss the why, where, and how his lead generation capabilities made customer cross-sell, up-sell, and retention easier by highlighting the critical importance of customer data and analytics.
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infor, cross-enterprise, lead generation, retention, customer data and analytics, social media
    
Infor
Published By: Infor     Published Date: Jan 06, 2011
You need a path through this madness.In this recorded webicast, Steve Muran will take you through a case study of how he methodically built and managed a cross-enterprise, multichannel program that deepened the customer wallet share. Steve will discuss the why, where, and how his lead generation capabilities made customer cross-sell, up-sell, and retention easier by highlighting the critical importance of customer data and analytics.
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infor, cross-enterprise, lead generation, retention, customer data and analytics, social media
    
Infor
Published By: SAP     Published Date: Dec 04, 2015
Download this whitepaper to see how advanced technologies such as big data, cloud computing, mobile devices, and enterprise access to in-memory platforms, predictive analytics, and planning software can help CFOs make better and more sophisticated use of data, influence decisions, and take practical, timely action.
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finance function, finance, cfo, big data, cloud computing, mobile, in-memory platforms, predictive analytics, planning software
    
SAP
Published By: Teradata     Published Date: Jun 22, 2015
Passed on May 9, 2014, the Digital Accountability and Transparency Act (DATA Act) legislation requires federal agencies to report all expenditures—grants, loans, and contracts—in order to provide American citizens and policy makers better visibility into federal spending. At first glance, new federal requirements— which are scheduled to go in effect May 2017—can seem like imposed obligations with unknown benefits to the implementers. However, wise agencies and early adopters recognize how to transform this new compliance obligation into an opportunity to advance their federal agency by becoming more data driven. The Federal Government maintains vast amounts of data, and the DATA Act establishes data standards and sharing protocols that will help agencies exploit the benefits of data mining and analytics.
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Teradata
Published By: Teradata     Published Date: Jul 07, 2015
As cyber security challenges continue to grow, new threats are expanding exponentially and with greater sophistication—rendering conventional cyber security defense tactics insufficient. Today’s cyber threats require predictive, multifaceted strategies for analyzing and gaining powerful insights into solutions for mitigating, and putting an end to, the havoc they wreak.
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Teradata
Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
What’s the best analytic approach for your business? As technology has evolved, so has our ability to process data at an incredible rate, making it possible to perform what has become known as Anticipatory Analytics. While still a relatively new concept, anticipatory analytics is gaining prevalence as a methodology. If you’re seeking to understand the future needs of your business before they show obvious signs, anticipatory analytics can’t be ignored. In this document, you’ll learn: • The advantages of anticipatory analytics • The key enablers of anticipatory analytics • How anticipatory can be leveraged for your business • Why anticipatory can give you first-mover advantage • When to use anticipatory or predictive analytics, based on your goals
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Dun & Bradstreet
Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
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.
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Dun & Bradstreet
Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
Stories and statistics behind successful analytics projects The adoption of analytics across the enterprise is accelerating, and with good reason. Analytics can offer a competitive advantage by helping to identify growth opportunities, circumnavigate risk and improve customer relationships. These insights are becoming crucial parts of the business strategy for executives representing a wide array of industries. Check out our latest eBook to see how some of the world’s leading companies are using analytics to meet their needs. You’ll receive diverse examples of how organizations applied the latest statistical methodologies, such as: scorecard build, regression, decision trees, machine learning and material change to uncover meaning in data. The examples represent global brands across critical industries – Financial Services, Insurance, High-Tech, Aerospace, Manufacturing and others – where analytics helped answer their most challenging questions.
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Dun & Bradstreet
Published By: Oracle APAC ZO OD Prime Volume ERP ABM Leads June 2017     Published Date: Nov 22, 2018
It is easy to get overwhelmed by the plethora acronyms (RTBs, DMPs,DSPs, SSPs, 1PD, 2PD, 3PD) and knowing when each of them come into play. Driven by data, Programmatic empowers modern marketers with the intelligence required to serve highly personalized ads. By bringing together First, Second and Third Party data at scale, you can target with increased precision and optimize campaigns in real-time. With tech platforms consistently pushing the boundaries of what’s possible in digital advertising, the time for marketers to lean into programmatic is now. Watch this 20 minute webinar with Mandar Dadegaonkar, an award-winning digital marketer and learn from his experience-based advise on: • how to get started and use programmatic tactics that work • insider secrets to boost ROI and improve campaigns • potential pitfalls to watch out for • guidelines for measurement and analytics
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Oracle APAC ZO OD Prime Volume ERP ABM Leads June 2017
Published By: Hewlett Packard Enterprise     Published Date: Jul 12, 2018
Forward-looking organizations are looking to next-generation all-flash storage platforms to eliminate storage cost and performance barriers. Advancements in all-flash technology have led to remarkable priceperformance improvements in recent years. The latest all-flash solutions from HPE deliver breakthrough economics, speed and simplicity, while improving availability and data durability. All-flash storage can help you reduce TCO and boost the performance of traditional applications as well as accelerate the rollout of new initiatives like IoT, big data and analytics. But moving data to a new storage architecture introduces a variety of organizational and technical challenges.
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Hewlett Packard Enterprise
Published By: Prophix     Published Date: Jun 03, 2016
For an increasing number of organizations, enterprise performance management (EPM) tools are enabling senior finance executives to integrate plans, understand where they're losing money, move from annual budgets to rolling forecasts, and identify opportunities for strategic improvements. During this Webcast, a panel of experts will explore: • Why business intelligence and business analytics are each important to your business; • How Big Data and analytics can help your organization answer more questions and ask even better ones; • The capabilities that enterprise performance management software offers organizations; and • How to evaluate what your organization can gain by implementing enterprise performance management software.
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enterprise management, best practices, productivity, opportunities, strategic improvements, software management
    
Prophix
Published By: Riverbed     Published Date: Jul 17, 2013
Your business is complex. Big data promises to manage this to make better decisions. But the technology services that run your business are also complex. Many are too complex to manage easily, causing delays and downtime. Forrester predicts this will worsen. To combat this onslaught, you need machines to analyze conditions to invoke automated actions. To perform adaptive automation, you need IT analytics, a disruption to your monitoring and management strategy. This report helps leaders prepare for IT analytics that turn big data efforts inward to manage the technology services that run your business. Register to get the full report.
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analytics, big data, forrester
    
Riverbed
Published By: Infomatica     Published Date: Jul 15, 2015
Being effective at collecting data is not enough; decision makers require meaningful and trustworth analytics, survey finds.
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Infomatica
Published By: Dell Server     Published Date: Aug 07, 2018
Today’s digital businesses are managed using critical business analyses that provide far greater insight into the business and how to maximize results. However, these high-value applications that use the latest software tools demand far more from IT infrastructure, as they utilize an order of magnitude more data and demand more compute resources than legacy applications. Legacy systems are no longer capable of meeting the present and future needs of the organization. Forward-thinking IT organizations are developing new infrastructure strategies to better support high-value analytics workloads with Dell EMC PowerEdge Servers powered by Intel® Xeon® Platinum processor.
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Dell Server
Published By: Microsoft     Published Date: Oct 06, 2017
After rapid expansion of vendors and features, players in the operational DBMS market continue converging toward feature parity. Data and analytics leaders will be interested in the lack of Visionaries, competition in the Challengers quadrant and the maturing cloud capabilities among these vendors.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
Microsoft
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