data analytics

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Published By: Oracle     Published Date: Dec 19, 2018
The finance team’s data - analytics skills put CFOs in the driving seat of digital change. Read the Economist Intelligence Unit report now to learn: • How finance helps other business units meet their digital ambitions • Why finance need to make data visible across the business • Why it’s important to develop m etrics f or digital success
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Oracle
Published By: Oracle     Published Date: Dec 21, 2018
After talking to 27 leading CFOs, the Economist Intelligence Unit finds that the finance team’s data analytics skills put the CFO in the driving seat of digital change.The result is that the CFO has a new responsibility to: • Help other business units meet their digital ambitions•Make relevant data visible across the business• Develop goals and metrics for digital success
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Oracle
Published By: Oracle     Published Date: Mar 04, 2019
EIU: CFOs now in the Digital Driving Seat White Paper Published By: Oracle The finance team’s data analytics skills put CFOs in the driving seat of digital change. Read the Economist Intelligence Unit report now to learn: • How finance helps other business units meet their digital ambitions • Why finance needs to make data visible across the business • Why it’s important to develop metrics for digital success Download now
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Oracle
Published By: IBM APAC     Published Date: Nov 22, 2017
A user initiates the call and selects the source language, such as Spanish. (In this example, assume that the target language is set to English.) As the user is talking to the support representative, the audio is converted to text using the Speech to Text service. Then using Language Translator, the text is translated to English. English language text is then sent to the Text to Speech service as input. The output audio message is what the support representative hears. All of this happens in near real time. The text from Speech to Text and the Language Translator service also can be stored in a database for analytics. The same process is repeated in reverse for the audio message sent by support personnel.
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source, language, english, spanish, speech to text, database, analytics, audio message, support
    
IBM APAC
Published By: IBM APAC     Published Date: Nov 22, 2017
Using IBM Watson’s cognitive capabilities, companies can quickly differentiate their customer service quality by being more pro active and responsive to customer needs. Simply put, chatbots and virtual agents are the future of customer interactions. Building apps from scratch that incorporate natural language processing, speech to text recognition, visual recognition, analytics, and artificial intelligence requires broad expertise in these disciplines, large staffs, and a huge financial commitment. Making use of IBM Watson cognitive services brings these capabilities in-house quickly and without the capital investment that would be needed to develop the technologies within an organization.
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decision making, deeper data, insights, cognitive, analytics, ibm, watson, virtual agents
    
IBM APAC
Published By: Dell EMC     Published Date: Oct 08, 2015
Download this whitepaper to learn how Dell can help you realize the full value of your big data strategy—and to capitalize on all of your data, from enterprise systems to social media and the Internet of things.
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Dell EMC
Published By: TIBCO Software     Published Date: Jan 17, 2019
Over the past decade, businesses have made tremendous investments in information capture, storage, and analysis. But having a wealth of data isn’t the same as having valuable information. Data Virtualization products and services provide a way to turn your data stores into valuable information that improves decision-making and propels experimentation and innovation. This paper explains: What data virtualization is and its benefits When and when not to use data virtualization How to deploy data virtualization to benefit your business How to unlock the value of your SAP data
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virtualization, data, users, analytics, sql, application, access, directory, outcomes, costs
    
TIBCO Software
Published By: TIBCO Software     Published Date: Jan 17, 2019
Are you considering data virtualization for your organization today? In this paper you will learn 10 core truths about data virtualization and gain essential knowledge for overcoming analytic data bottlenecks and driving better outcomes.
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virtualization, data, analytics, datasets, software, access, integration, projects, tools, scalability
    
TIBCO Software
Published By: TIBCO Software     Published Date: Jan 17, 2019
Over the past decade, businesses have made tremendous investments in information capture, storage, and analysis. But having a wealth of data isn’t the same as having valuable information. TIBCO® Data Virtualization products and services provide a way to turn your data stores into valuable information that improves decision-making and propels experimentation and innovation. This paper explains: •?What data virtualization is and its benefits •?When and when not to use data virtualization •?How to deploy data virtualization to benefit your business
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virtualization, data, users, analytics, sql, application, access, directory, outcomes, costs
    
TIBCO Software
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: Acxiom Corporation     Published Date: Mar 12, 2014
In July 2013 Acxiom commissioned Forrester Consulting to evaluate how companies use the data they collect from their customers to make better decisions on their marketing campaigns by gauging their experiences and attitudes around their use of and future vision for using customer data across multiple marketing channels. In order to understand this topic, we conducted interviews with 11 executives representing a range of roles and perspectives, including consumer packaged goods companies, financial services organizations, and agencies.
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acxiom, forrester, data, marketing, marketing campaigns, cross channel, customer data, market research, targeting, data analytics, life cycle management, business intelligence, data management/analytics
    
Acxiom Corporation
Published By: Acxiom Corporation     Published Date: Mar 12, 2014
If you are responsible for online advertising, this report is going to change the way you look at your banner ads forever. It did for us. But, step one on the road to this transformation was deciding exactly what to measure. Download this whitepaper to learn about a new measurement approach that proves banner ads boost offline sales.
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acxiom, marketing, measurement, banner ads, display advertising, targeting, marketing campaigns, marketing analytics, data analytics, online engagement, customer experience/engagement, business intelligence, market research, branding, data management/analytics
    
Acxiom Corporation
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
In a panel discussion at the 12th annual SAS Health Analytics Executive Forum in May 2015, leaders from Dignity Health, Horizon Blue Cross Blue Shield of New Jersey, Janssen Pharmaceuticals and SAS shared what they have done to prove the value of analytics to their business leaders – and what has worked for them as they developed an analytic culture in their organizations and put analytic insights to work.
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sas, healthcare, healthcare models, episode analytics, analytics, data management, information technology, practice management
    
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: RMS     Published Date: Jul 25, 2019
U.S. Flood is a high-gradient, intricate peril incorporating various sources, and causing a variety of effects. It requires sophisticated models, data science, and analytics technology to properly understand and assess each risk.
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RMS
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: Oracle EMEA     Published Date: Apr 15, 2019
Forward-thinking enterprises understand what it takes to be successful in this data-rich, increasingly automated economy. According to the Harvard Business Review Analytic Services research report The Rise of Intelligent Automation: TurningComplexity into Profit, sponsored by Oracle, at least 7 in 10 executives understand that predictive analytics (80%) and AI and machine learning (68%) are important for the future of the business. Even as executives recognize the vital role data plays in their businesses, many are unable to take advantage of the value residing in their data. The old ways of collecting, managing, storing, and analyzing data are no longer effective, and are preventing businesses from extracting potential value. Many simply can’t execute on a data-driven vision.
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Oracle EMEA
Published By: Oracle EMEA     Published Date: Apr 15, 2019
Oracle Autonomous Data Warehouse Cloud is more than just a new way to store and analyze data; it’s a whole new approach to getting more value from your data. Market leaders in every industry depend on analytics to reach new customers, streamline business processes, and gain a competitive edge. Data warehouses remain at the heart of these business intelligence (BI) initiatives, but traditional data-warehouse projects are complex undertakings that take months or even years to deliver results. Relying on a cloud provider accelerates the process of provisioning data-warehouse infrastructure, but in most cases database administrators (DBAs) still have to install and manage the database platform, then work with the line-of-business leaders to build the data model and analytics. Once the warehouse is deployed—either on premises or in the cloud—they face an endless cycle of tuning, securing, scaling, and maintaining these analytic assets. Oracle has a better way. Download this whitepaper to f
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Oracle EMEA
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: Workday     Published Date: Sep 30, 2019
Whether informing talent strategy or building more effective teams, data-driven insights about your workforce can set you up for success. This eBook from Human Capital Institute explores how people analytics can empower your entire organization. Read now.
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workday inc (wday), career development, employee engagement, human capital management, human resource management
    
Workday
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