data analytics

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By: Pentaho     Published Date: Feb 26, 2015
This TDWI Best Practices report explains the benefits that Hadoop and Hadoop-based products can bring to organizations today, both for big data analytics and as complements to existing BI and data warehousing technologies.
Tags : big data, big data analytics, data warehousing technologies, data storage, business intelligence, data integration
     Pentaho
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.
Tags : pentaho, analytics, platforms, big data, predictive analytics, data management, data science
     Pentaho
By: Pentaho     Published Date: Nov 04, 2015
This report explains the benefits that Hadoop and Hadoop-based products can bring to organizations today, both for big data analytics and as complements to existing BI and data warehousing technologies based on TDWI research plus survey responses from 325 data management professionals across 13 industries. It also covers Hadoop best practices and provides an overview of tools and platforms that integrate with Hadoop.
Tags : pentaho, analytics, platforms, hadoop, big data, predictive analytics, data management, data science
     Pentaho
By: Pentaho     Published Date: Nov 04, 2015
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
Tags : pentaho, analytics, platforms, hadoop, big data, predictive analytics, data science
     Pentaho
By: Cisco     Published Date: Feb 13, 2015
Get your IDC report on how enterprises are adopting both private and hybrid cloud computing models for business. Learn about their challenges, and how Cisco Intercloud Fabric helps to address them.
Tags : hybrid cloud, cloud management, mobility, virtualization, data analytics, internet of things, it department, cloud computing, big data
     Cisco
By: Oracle     Published Date: Feb 24, 2015
To succeed in this new business climate, smart businesses are adapting and realizing that the next frontier is to read and respond to the “Digital Body Language” of their prospects. This new body language is revealed through online activities such as website visits, white paper downloads, and email responses. Find out more about Digital Body Language. Download “Reading and Responding to Your Prospects’ Buying Behavior in the Online World”
Tags : oracle, digital marketing, b2b, rfp, feedback, signals, data, behavior, prospect interest, intent, analytics, buying process, sales, online, efficiency
     Oracle
By: SurveyMonkey     Published Date: Oct 23, 2015
Watch our webinar, 4 Steps to Building a Customer Satisfaction Engine. SurveyMonkey's Director of Customer Success, Jeffrey Coleman, will show you how to: - Ask questions that yield actionable data - Scale follow-up actions and improvements - Analyze survey data and get key metrics - Close the loop by turning data into action
Tags : survey monkey, customer satisfaction, customer success, data analytics, survey data, client services, customer operations, salesforce, sfdc service
     SurveyMonkey
By: Oracle     Published Date: Oct 20, 2017
What do these market-defining trends have in common? · Analytics for all · Analytics as competitive differentiator · Internet of Things · Artificial intelligence/Machine learning/Cognitive computing · Real-time analytics/event management They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise? It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i
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     Oracle
By: AWS     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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     AWS
By: AWS     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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     AWS
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
Tags : interaction management, business technology, enterprise, forrester, best practices, pegasystems
     Pega
By: Adobe     Published Date: Nov 09, 2017
Marketing leaders are asking their analytics teams to provide better insights into customers, prospects and journeys, and a more accurate assessment of the impact of marketing tactics. Use this research to find a digital marketing analytics tool to support your needs. This Magic Quadrant is intended for chief marketing of?cers (CMOs), marketing analytics and data science practitioners, and other digital marketing leaders involved in the selection of systems to support marketing analytics requirements.
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     Adobe
By: Adobe     Published Date: May 04, 2018
Adobe is the only Leader in Digital Intelligence Platforms. Digital intelligence with scope and depth. Your customers come to you from different places, so your data insights should do the same thing. Adobe Experience Cloud’s digital marking and analytics solutions help you combine insights from existing, new, and emerging channels. Read the Forrester Wave™: Digital Intelligence Platforms, Q2 2017 to find out why we stand alone among DI platform vendors.
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     Adobe
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
By: Oracle CX     Published Date: Oct 19, 2017
The Software in Silicon design of the SPARC M7 processor, and the recently announced SPARC S7 processor, implement memory access validation directly into the processor so that you can protect application data that resides in memory. It also includes on-chip Data Analytics Accelerator (DAX) engines that are specifically designed to accelerate analytic functions. The DAX engines make in-memory databases and applications run much faster, plus they significantly increase usable memory capacity by allowing compressed databases to be stored in memory without a performance penalty. The following Software in Silicon technologies are implemented in the SPARC S7 and M7 processors: Note: Security in Silicon encompasses both Silicon Secured Memory and cryptographic instruction acceleration, whereas SQL in Silicon includes In-Memory Query Acceleration and In-Line Decompression. Silicon Secured Memory is the first-ever end-to-end implementation of memory-access validation done in hardware. It
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     Oracle CX
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
Tags : 
     Oracle CX
By: Oracle CX     Published Date: Oct 20, 2017
Oracle’s new cloud platform, included a new line of servers for cloud and scale-out applications: Oracle’s SPARC S7-2 and S7-2L servers. These servers are based on the breakthrough SPARC S7 processor and extend the outstanding features and capabilities of the SPARC T7 and M7 systems into scale-out form factors. With the combination of Oracle’s breakthrough Software in Silicon features and the efficiency of the SPARC S7 processor we can offer the most secure and economical enterprise clouds with the fastest infrastructure for data analytics. Here at Oracle we recognize our customers’ needs for increasing the security of their data, therefore we have taken security as one of the core values on the SPARC Servers. The new SPARC S7 processor leverages the revolutionary Security in Silicon features introduced on the SPARC T7 and M7 systems. Silicon Secured Memory is a unique hardware implementation that prevents unauthorized access to application data in memory and can prevent hacking explo
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     Oracle CX
By: Oracle CX     Published Date: Oct 20, 2017
On Thursday June 30th, we announced Oracle’s new cloud platform, including a new line of servers for cloud and scale-out applications: Oracle’s SPARC S7-2 and S7-2L servers. These servers are based on the breakthrough SPARC S7 processor and extend the outstanding features and capabilities of the SPARC T7 and M7 systems into scale-out form factors. With the combination of Oracle’s breakthrough Software in Silicon features and the efficiency of the SPARC S7 processor we can offer the most secure and economical enterprise clouds with the fastest infrastructure for data analytics. Here at Oracle we recognize our customers’ needs for increasing the security of their data, therefore we have taken security as one of the core values on the SPARC Servers. The new SPARC S7 processor leverages the revolutionary Security in Silicon features introduced on the SPARC T7 and M7 systems. Silicon Secured Memory is a unique hardware implementation that prevents unauthorized access to application data in
Tags : 
     Oracle CX
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
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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