business analytics

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Published By: Hewlett Packard Enterprise     Published Date: Jul 12, 2016
Technology enables business transformation To thrive in today’s idea economy, small and midsize companies like yours are using technology to transform their business. Like your peers, you know that mobile applications, cloud-based solutions, and advanced analytics can help you increase productivity, reduce costs, and grow your business. Older servers, storage, and networking products weren’t built to handle the exploding amount of data that is being shared today. In order to take advantage of these modern applications, many companies have found that they need to close the gap between what their business demands and what their IT systems can deliver.
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best practices, business optimization, business management, application management, enterprise application, business intelligence, transformation
    
Hewlett Packard Enterprise
Published By: Cisco     Published Date: Jun 21, 2016
Transform your business with services that allow you to innovate faster, simplify operations, and reduce risk. Building on an open, software-driven approach that uses virtualization, automation, analytics, and cloud, our networkwide architecture prepares you to respond to new opportunities at digital speed.
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Cisco
Published By: SAS     Published Date: Jan 17, 2018
What can you see and discover when you’re able to explore trends and make predictions with your organization’s data? If you’re a midsize home delivery business, you can discover new ways to make customers happy. If you’re a local government agency, you can predict where your resources are needed most. And if you’re a growing hospital, you can bring life-changing patient data directly to doctors and nurses. In this e-book, we’ve profiled six organizations that are using self-service visual exploration to make big improvements in the way they work. From college administrators to professional sports teams, everyone makes better decisions with easy access to powerful, interactive analytics.
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SAS
Published By: SAS     Published Date: Jan 17, 2018
This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.
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SAS
Published By: Pentaho     Published Date: Feb 26, 2015
Ventana’s benchmark research on big data integration will help you become familiar with the tools and technologies you need to help your organization succeed with big data.
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benchmark research, big data integration, big data, business intelligence systems, business analytics, data integration
    
Pentaho
Published By: Pentaho     Published Date: Nov 04, 2015
Amid unprecedented data growth, how are businesses optimizing their data environments to ensure data governance while creating analytic value? How do they ensure the delivery of trusted and governed data as they integrate data from a variety of sources? If providing appropriately governed data across all your data sources is a concern, or if the delivery of consistent, accurate, and trusted analytic insights with the best blended data is important to you, then don’t miss “Delivering Governed Data For Analytics At Scale,” an August 2015 commissioned study conducted by Forrester Consulting on behalf of Pentaho.
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pentaho, analytics, platforms, big data, predictive analytics, data management, networking, storage, data center
    
Pentaho
Published By: Oracle     Published Date: Jan 12, 2017
Businesses today expect finance to play an extended role across departments, including IT, human resources, compliance, operations, sales, marketing, and most importantly, corporate strategy.To successfully deliver on this role, the finance function needs to play a bigger and visible role in real-time decision making and continuous planning. This report explores how, using cloud and analytics, finance leaders can leapfrog a few generations of technology and offer mature analytical feature/functionality and skills to the entire organization.
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Oracle
Published By: Amazon Web Services     Published Date: Dec 15, 2017
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time. AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance. In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences. Join this webinar to learn: How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development. How AWS supports BI solutions f
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
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Amazon Web Services
Published By: Pega     Published Date: May 25, 2016
IT leaders working on customer service projects must display an incredible amount of diligence. An organization’s CRM system has become its lifeline to customers, but as customer needs evolve so has the requirements of CRM. According to Gartner, today’s CRM solution must include a laundry list of capabilities outside its traditional core functionality including: native mobile support of the vendor's customer service and support business applications; real-time analytics; industry-specific functionality and workflow; context mining of voice and text; scalable cloud-based systems; social media engagement; suggested next agent action; multimodal capabilities, such as chat within mobile self-service; and even co-browsing. Gartner surveyed the CRM field and evaluated each vendor including Pegasystems. Download this Gartner Magic Quadrant analysis and gain a better understanding each vendors’ CRM Customer Engagement Center solutions.
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best practices, customer support, business intelligence, business optimization, customer engaement
    
Pega
Published By: Pega     Published Date: May 25, 2016
Customer insights professionals face the challenging task of delivering contextually relevant experiences across the customer life cycle. They need to work with their business technology counterparts to integrate enterprise marketing technologies that manage customer data, provide real-time analytics and insights, and automate cross-channel interactions. Here is where Real-Time Interaction Management (RTIM) is critical, according to The Forrester Wave™: Real-Time Interaction Management, Q3 2015 report, which identified the 11 most significant technology providers in this space across 35 criteria. Forrester defines RTIM as “Enterprise marketing technology that delivers contextually relevant experiences, value, and utility at the appropriate moment in the customer life cycle via preferred customer touchpoints,” and identifies Pegasystems as one a leader in this very diversified pack. Download this Forrester Wave report to
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interaction management, business technology, enterprise, forrester, best practices, pegasystems
    
Pega
Published By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • Optimal application performance and delivery is difficult to achieve in complex environments. • Many IT infrastructure and operations teams are stretched to the breaking point. • Predictive analytics and machine learning can be applied to great effect.
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Hewlett Packard Enterprise
Published By: Oracle CX     Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better
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Oracle CX
Published By: Oracle CX     Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle CX
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