data report

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Published By: Group M_IBM Q2'19     Published Date: May 23, 2019
Defense and intelligence agencies want to leverage the data they collect so they can use artificial intelligence to enhance readiness – but most who run these programs don’t know how to get started and find it difficult to make the business case to their leadership. In this research report, created by GovLoop in partnership with IBM, which provides innovative technology solutions for national security and military intelligence, you’re going to learn where your peers stand—and some practical tips on how to get started—even if you think your data is “dirty” or not ready for advanced applications.
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Group M_IBM Q2'19
Published By: Oracle     Published Date: Oct 23, 2014
If you are a marketer and are looking to scale your efforts in an efficient and effective manner, data has quickly become the core of your strategy and will continue to drive your efforts for many years to come. This report will show you the amazing possibilities.
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data management, demystified, audience, targeting, scale, marketing, programs, actionable
    
Oracle
Published By: Palo Alto Networks     Published Date: Apr 25, 2017
SANS conducted this survey to explore how organizations are handling prevention. Breaking down possible preventive measures into four major categories or domains (business, architectural design and development, operational, and technology), the survey sought to answer three major questions: 1. What measures have respondents implemented that they believe will prevent breaches? 2. What measures not necessarily implemented do respondents consider preventive? 3. What barriers have stopped respondents from doing what they should be doing?
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Palo Alto Networks
Published By: SAS     Published Date: Jan 17, 2018
Delivering exceptional customer experiences has become a key differentiator for top organizations today. Now you can see where your peers and competitors stand in the new Forbes Insights report Data Elevates the Customer Experience. This report is a comprehensive follow-up to an October 2015 preliminary pulse survey conducted among 105 executives of large global organizations. It identifies three categories of organizations – leaders, explorers and laggards – and measures the progress they have made with the data-driven customer experience based on three key pillars: organization (people), openness (data) and orchestration (processes). Read the results, find out where you stand and glean some new ideas from your peers about how to elevate the customer experience.
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SAS
Published By: Veritas     Published Date: May 12, 2016
The Data Genomics Index is a first-of-its-kind benchmark analysis of data stored within a typical enterprise environment. This report reveals insights into data growth, data age, and data type thereby providing organizations with the comparison standard for beginning to take action on their data. In addition to the Index, Veritas has founded the Data Genomics Project. This community of likeminded data scientists, industry experts and thought leaders will come together to surface the true nature of enterprise environments, build the data-genome that matters for information management, and share the discussion with a world struggling to solve tremendous data growth challenges.
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Veritas
Published By: Veritas     Published Date: Oct 03, 2016
This benchmark report, the Data Genomics Index, encompasses a community of like-minded data scientists, industry experts, and thought leaders together with the purpose of better understanding the true nature of the unstructured data that we are creating, storing, and managing on a daily basis - a report on real storage environments’ composition.
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Veritas
Published By: Group M_IBM Q1'18     Published Date: Jan 04, 2018
As organizations seek to extract more strategic value from their data, many are starting to view data governance as an enabler of insight rather than an impediment to its creation. This report explores a leading approach to data governance and the impact it can have on today’s most data-rich organizations.
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data governance, data-rich organizations
    
Group M_IBM Q1'18
Published By: IBM Watson Health     Published Date: Nov 10, 2017
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
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population health management, big data, data, data analytics, big data solution, data infrastructure, analytic tools, predictive modeling
    
IBM Watson Health
Published By: NetApp     Published Date: Mar 05, 2018
Access to comprehensive, up-to-date information about your infrastructure is critical to meeting the challenges of a service-led IT organization. You need visibility into your entire IT infrastructure, including both multi-vendor and multi-cloud environments, so you can make data-driven decisions and improve IT services. Discover how you can manage, monitor, and report on IT services across your entire data infrastructure so you can drive intelligent business decisions and reduce costs.
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netapp, database performance, flash storage, data management, cost challenges
    
NetApp
Published By: SAS     Published Date: Aug 28, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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SAS
Published By: Datawatch     Published Date: Feb 03, 2016
Some companies estimate that up to 80 percent of their analysts’ time is spent on data preparation. Thorough, automated data preparation, however, can quickly transform raw information into reliable, consistent data sets ready for analysis. This report from Gartner details why information management and business analytics leaders must introduce data preparation into their big data initiatives in order to improve both the understanding of the data, and the productivity of analysts. Read the report now to learn more.
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datawatch, data preparation, data analytics, data analysis, analyst productivity, information management, business analytics, big data
    
Datawatch
Published By: Druva     Published Date: Sep 27, 2017
Wondering what data protection will look like in 2017? In this report, ESG provides new research on what is driving the need for better data protection and recovery in organizations of all sizes with major trends pointing to the cloud as the ultimate game changer.
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data protection, data recovery, cloud
    
Druva
Published By: Trend Micro, Inc.     Published Date: Apr 29, 2009
In January of 2008, a random sample of online technical newsletter subscribers at midsize companies (100-5,000 employees) received an email invitation to participate in a survey about data protection solutions use at their organizations. The goal of the survey was to identify sources of and/or reasons for information security breaches, and to better understand how businesses are planning to protect themselves against data leaks. The following report presents top line results of the study.
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trend micro, data breach, smb, midsize, breaches, data breaches, data loss prevention, dlp
    
Trend Micro, Inc.
Published By: Trillium Software     Published Date: May 19, 2011
Today financial services institutions must meet the standards for data quality attestation by the FFEIC regulators of risk reporting. This paper discusses the platform and domain expertise needed to support the rigorous demands of commercial and retail risk reporting.
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trillium software, data quality management, basel ii solution, data profiling, data monitoring, metadata, data supporting risk, grc
    
Trillium Software
Published By: Informatica     Published Date: Nov 21, 2011
This demo showcases the ease-of-use to replicate data sets, the process of connecting to a data source, defining a mapping, initial synchronization, extraction and finally applying to a destination.
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demo, data sets, data replication, replication, mapping, synchronication, reporting, loading
    
Informatica
Published By: Forcepoint     Published Date: Apr 19, 2016
In 2014, data breaches compromised over 700 million records with financial losses estimated to be at least $400 million – and security incidents grew up to 66 percent. But don’t allow fear to stifle growth. The “Data Theft Prevention” report focuses on how to stay secure while you innovate from a broader, in-scope, more intelligent in application perspective.
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Forcepoint
Published By: MicroStrategy     Published Date: Aug 28, 2019
The Constellation AstroChartTM supplies a visual guide of the trends impacting Data to Decisions. After assessing boardroom priorities, organizations should employ AstroCharts to inform portfolio management. This report contains two AstroCharts: one identifying Business Trends and one identifying Technology Trends. The AstroCharts’ vertical axes plot “Organizational Adoption” rates from Mainstream to Early Adopter to Bleeding Edge. Horizontal axes plot “Business Impact,” the impact of the trend on an organization’s business model, from Incremental to Transformational to Exponential. The Constellation AstroChart moves beyond both the hype and constraints of the standard 2 x 2 grid to identify the dynamics impacting the entire market. This report applies Constellation’s AstroChart to the Constellation’s business theme of Data to Decisions. This research domain examines the enablement of data-driven decisions across organizations. Holistic, data-informed decisions require a multidisciplin
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MicroStrategy
Published By: Pentaho     Published Date: Apr 28, 2016
As data warehouses (DWs) and requirements for them continue to evolve, having a strategy to catch up and continuously modernize DWs is vital. DWs continue to be relevant, since as they support operationalized analytics, and enable business value from machine data and other new forms of big data. This TDWI Best Practices report covers how to modernize a DW environment, to keep it competitive and aligned with business goals, in the new age of big data analytics. This report covers: • The many options – both old and new – for modernizing a data warehouse • New technologies, products, and practices to real-world use cases • How to extend the lifespan, range of uses, and value of existing data warehouses
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pentaho, data warehouse, modernization, big data, bug data analytics, best practices, networking, it management
    
Pentaho
Published By: Google     Published Date: Oct 26, 2018
Modernizing your data warehouse is one way to keep up with evolving business requirements and harness new technology. For many companies, cloud data warehousing offers a fast, flexible, and cost-effective alternative to traditional on-premises solutions. This report sponsored by Google Cloud, TDWI examines the rise of cloud-based data warehouses and identifies associated opportunities, benefits, and best practices. Learn more about cloud data warehousing with strategic advice from Google experts.
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Google
Published By: Google     Published Date: Jan 24, 2019
Modernizing your data warehouse is one way to keep up with evolving business requirements and harness new technology. For many companies, cloud data warehousing offers a fast, flexible, and cost-effective alternative to traditional on-premises solutions. This report sponsored by Google Cloud, TDWI examines the rise of cloud-based data warehouses and identifies associated opportunities, benefits, and best practices. Learn more about cloud data warehousing with strategic advice from Google experts.
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Google
Published By: Schneider Electric     Published Date: Jul 01, 2019
Data-driven asset performance management can help food & beverage manufacturers leverage tools such as equipment efficiency solutions, augmented reality and secure asset connection to transition from a reactive to a prescriptive approach. This will not only help reduce CapEx and OpEx, but also empower the workforce, whilst meeting manufacturing KPIs. This report from Frost & Sullivan shows how manufacturers can achieve 20-30% cost savings by changing their asset maintenance approach.
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asset performance, food and beverage, manufacturing
    
Schneider Electric
Published By: Veritas     Published Date: Oct 03, 2016
A study, conducted by research firm Vanson Bourne, covering some 2,550 respondents across 22 countries, looks at the issues surrounding the phenomenon of the Databerg and uncovers how organizations throughout the globe are on track to waste more than $3.3tn by 2020. This report is a must-read for IT executives.
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Veritas
Published By: Datastax     Published Date: Aug 03, 2018
With DataStax Enterprise 6 (DSE 6), we upped the bar substantially for us, our partners, our customers, and our competitors. We also came out and said that DSE 6 was twice as fast as open source Apache Cassandra™, and now, we have a third-party validation of this claim. Read this benchmark report from zData to get the results of their test of DSE 6 against Cassandra, for which they ran a different series of workloads on an AWS-built cluster.
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Datastax
Published By: Datastax     Published Date: Aug 27, 2018
With DataStax Enterprise 6 (DSE 6), we upped the bar substantially for us, our partners, our customers, and our competitors. We also came out and said that DSE 6 was twice as fast as open source Apache Cassandra™, and now, we have a third-party validation of this claim. Read this benchmark report from zData to get the results of their test of DSE 6 against Cassandra, for which they ran a different series of workloads on an AWS-built cluster.
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Datastax
Published By: IBM     Published Date: Nov 15, 2013
Analyst Wayne Kernochan of Infostructure Associates documents the analytics speed-up capability of DB2 with BLU Acceleration and explains how DB2 BLU compares with competitors. His conclusion after reviewing test results? Not surprisingly, the results verified a consistent, roughly order-of-magnitude speedup using BLU Acceleration, against DB2 pre-BLU and against some obvious competitors. What is his advice to readers about DB2 BLU? If your upcoming database needs analytics/BI/reporting-related, why would you not use BLU Acceleration for them? In other words, what are you waiting for?
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ibm, analytics, db2, blu acceleration, acceleration, speed, database, business intelligence
    
IBM
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